next generation merchandise recommendation slides 2009
DESCRIPTION
A vendor presentation on adding a recommender to e-commerce website.TRANSCRIPT
Next Generation RecommendationsThe Four Keys To Successful Merchandising Automation
Ryan HoppeDirector Marketing ATG Optimization Services
Tom DavisDirector of Ecommerce
Tommy Hilfiger
2
Agenda
ATG Background
Why Recommendations
Recommendations or Merchandising Automation
The Four Keys To Successful Automation
Case Study Tommy Hilfiger
Next Steps
QampA
3
The leader in e-Commerce solutions
Over 900 customers worldwide
Headquarters in Cambridge MA with offices throughout North America and Europe
Approximately 500 employees
2008 revenue $1646 million with profitability
1991
Founding
2006
Acquired
1999
IPO
2004
Acquired
(ARTG)
2008
Acquired
ATG Background
4
ATG Product Suite At-a-Glance
Shopping Cart amp Product Catalog
Merchandising amp Searchandising
Commerce Search
Multivariate Testing
Marketing Campaign Manager
Business amp Customer Analytics
Integrated Customer Service
KnowledgeIncident Management
On Demand Commerce Platform
Commerce SuiteLicensed or OnDemand
Automated Recommendations
Click to Call
Click to Chat
Call Tracking
Save amp Send
Form to Phone
Video Connect
e-Commerce Optimization ServicesPlatform-Neutral Services
5
ATG Powers the Worldrsquos Top Brands Online
6
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
What Are Automated Recommendations
7
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
What Are Automated Recommendations
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
2
Agenda
ATG Background
Why Recommendations
Recommendations or Merchandising Automation
The Four Keys To Successful Automation
Case Study Tommy Hilfiger
Next Steps
QampA
3
The leader in e-Commerce solutions
Over 900 customers worldwide
Headquarters in Cambridge MA with offices throughout North America and Europe
Approximately 500 employees
2008 revenue $1646 million with profitability
1991
Founding
2006
Acquired
1999
IPO
2004
Acquired
(ARTG)
2008
Acquired
ATG Background
4
ATG Product Suite At-a-Glance
Shopping Cart amp Product Catalog
Merchandising amp Searchandising
Commerce Search
Multivariate Testing
Marketing Campaign Manager
Business amp Customer Analytics
Integrated Customer Service
KnowledgeIncident Management
On Demand Commerce Platform
Commerce SuiteLicensed or OnDemand
Automated Recommendations
Click to Call
Click to Chat
Call Tracking
Save amp Send
Form to Phone
Video Connect
e-Commerce Optimization ServicesPlatform-Neutral Services
5
ATG Powers the Worldrsquos Top Brands Online
6
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
What Are Automated Recommendations
7
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
What Are Automated Recommendations
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
3
The leader in e-Commerce solutions
Over 900 customers worldwide
Headquarters in Cambridge MA with offices throughout North America and Europe
Approximately 500 employees
2008 revenue $1646 million with profitability
1991
Founding
2006
Acquired
1999
IPO
2004
Acquired
(ARTG)
2008
Acquired
ATG Background
4
ATG Product Suite At-a-Glance
Shopping Cart amp Product Catalog
Merchandising amp Searchandising
Commerce Search
Multivariate Testing
Marketing Campaign Manager
Business amp Customer Analytics
Integrated Customer Service
KnowledgeIncident Management
On Demand Commerce Platform
Commerce SuiteLicensed or OnDemand
Automated Recommendations
Click to Call
Click to Chat
Call Tracking
Save amp Send
Form to Phone
Video Connect
e-Commerce Optimization ServicesPlatform-Neutral Services
5
ATG Powers the Worldrsquos Top Brands Online
6
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
What Are Automated Recommendations
7
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
What Are Automated Recommendations
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
4
ATG Product Suite At-a-Glance
Shopping Cart amp Product Catalog
Merchandising amp Searchandising
Commerce Search
Multivariate Testing
Marketing Campaign Manager
Business amp Customer Analytics
Integrated Customer Service
KnowledgeIncident Management
On Demand Commerce Platform
Commerce SuiteLicensed or OnDemand
Automated Recommendations
Click to Call
Click to Chat
Call Tracking
Save amp Send
Form to Phone
Video Connect
e-Commerce Optimization ServicesPlatform-Neutral Services
5
ATG Powers the Worldrsquos Top Brands Online
6
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
What Are Automated Recommendations
7
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
What Are Automated Recommendations
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
5
ATG Powers the Worldrsquos Top Brands Online
6
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
What Are Automated Recommendations
7
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
What Are Automated Recommendations
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
6
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
What Are Automated Recommendations
7
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
What Are Automated Recommendations
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
7
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
What Are Automated Recommendations
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
8
Utilize data from the
catalog historical
shopping information
click-stream data
Web site and more to
predict each
shopperrsquos intent in
each session
Deliverpersonalized
recommendations
amp merchandise on
your Web site and
in other online
channels
ldquoLearnrdquo from
customers as they
navigate your site and
refine products based
on changing intent
What Are Automated Recommendations
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
9
Online Retailers With Personalized Recommendations
100
Why RecommendationsCustomers Like Them
27
Customers Who Like Online Recommendations
76Customers Who Like Personalized Emails
100
63
100
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
10
November 2008 ldquoThe Impact Of The Economic Crisis On eCommerce Technology Investmentrdquo
Itrsquos a Quick Win
Why Recommendations
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
11
Why Recommendations
Convert browsers into
buyers by predicting
intent and presenting the
most relevant products
Increase order values
by automating and
personalizing
cross-sells amp up-sells
Retain customers by
personalizing the
cross-channel
shopping experience
Increase Revenue amp Loyalty
Lift Online Revenue Quickly Easily amp Measurably by
Personalizing Product Discovery
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
12
You Might
Also Likehellip
Others Who
Looked At This
Bought That
Recommendations
Engine
First Gen RecommendersReal Value But Limited Applications
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
13
Fear of Automating More Than Cross-Sells amp Recommendations
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
14
Cross-Sells amp
Up-Sells
Personalized
Recommendations
Top Sellers
Gift Guides
Whatrsquos New
On Sale
Automated
Merchandising
Engine
Next Gen RecommendersAutomated Merchandising With Merchants At The Controls
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
15
Value of Automated Merchandising
Customer Use Case
Conversion Rate
Increase Over
Site Average
AOV Increase
Over Site
Average
Retailer 1Cross-Sells on Product
Detail Pages76 8
Retailer 2
Automated Cross-Sells
Up-Sells Top Sellers Null
Search Results Pages
Shopping Cart Cross-
Sells etc
160 20
More Than Double The Impact Of Automating Cross-Sells
Data from two ATG Recommendations customers over a three month period
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
16
Four Keys To Success For Next Gen Recommendations
3
2
4
1
Reach
Can the solution reach across my catalog site and channels
Relevancy
How relevant are the products to each visitor
Relationship
Does the provider offer a relationship focused on my needs as a retailer
Refinement
Can I refine or ldquofilterrdquo products before they are shown
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
17
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
18
1
First Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Fail To Utilize All Data
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
19
1
First Gen Recommenders Fail To Utilize All Data
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
20
1
Second Gen Recommenders
Product
Details
Session
Stats
Historical
Data
Visitor
Behavior
Relevancy
Utilize All Data To Make Predictive Choices
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
21
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Second Gen Recommenders Understand Your Catalog amp Shoppers
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
Relevancy
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
22
Products Viewed
Ratings
Brand amp Manufacturer
Descriptions
Product in Catalog Location
Type of URL Page
Refer URL
Broadband Speed
IP AddressGeography
Past Shopping Behavior
Visitorrsquos Past Searches
Aggregated Past Behavior
Searches
Clickstream
Order of Page Views
Duration of Page Views
Visitor
Behavior
Historical
Data
Product
Details
Session
Stats
1
RelevancySecond Gen Recommenders Get Smarter Over Time
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
23
First Gen Recommenders2
Refinement
Canrsquot Control
The Science
or Execute
Merchandising
Strategy
ldquoBlack Boxrdquo With Limited or No Control
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
24
1
Second Gen Recommenders
CatalogRefinements
Rich Merchant Control amp Refinement
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
25
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
Second Gen RecommendersRich Merchant Control amp Refinement
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
26
1 2
Cross-sell
Up-sell
Page Type
Keyword
Cart Value
Product Value
CatalogRefinements
Blended Refinements
2
Refinement
Category
Brand
Price
Collection
Top Seller
New
Fixed
SessionRefinements
3
Second Gen RecommendersRich Merchant Control amp Refinement
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
2727
3Reach
First gen solutions canrsquot reach into the product catalog
ndash Only learn products through shoppersrsquo activity
ndash Canrsquot recommend new
ndash Biased towards popular items
Or reach customers wherever they shop
ndash Across the site
ndash Across formats
ndash Across channels
First Gen Solutions
First Gen Recommenders Lack of Reach
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
2828
3Reach
Reach across and understand the complete catalog
ndash Form detailed product relationships
ndash Categories brands prices descriptions
ndash Can recommend any product (new niche popular)
Reach customers wherever you sell
ndash Across the online store
ndash Into emails
ndash Into rich media
ndash Across channels
New
Niche
Second Gen Recommenders Reach Across The Catalog Site amp Channels
Second Gen Solutions
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
29
Canrsquot Provide a Total eCommerce
Solution
Start-ups With Limited Resources
Focused On Multiple
Industries
4RelationshipFirst Gen Recommenders Lack a Retail-Focused Relationship
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
30
Tune relevancy
Measure results with AB testing
Demonstrate impact with Web-based reports
Retail-Focused Roadmap
Retail-Focused Client Service
Retail-Focused Statisticians
Monitor impact to improve performance
Analyze trends to inform merchandising strategy
Focused on needs of online retailers
Family of Web optimization services
Next generation personalized cross-channel commerce
4RelationshipSecond Gen Recommenders The Retail Relationship You Need
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations
Shoptommycom Holiday 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Tommy Hilfiger
Tom Davis
Director of Ecommerce
tomdavistommy-usacom
Went live with ATG in November 2007
ndash OnDemand client
ndash ATG Recommendations Fall 2008
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Business Case
Shoptommycom represented several full collections including
Sportswear Collection (men and women)
Hilfiger Denim Collection (men and women)
Kids Collections (boys and girls)
Various accessories (men women and kids)
Each new style required recommended products (cross sells up-sells recommendations) associated to it and we didnrsquot have the manpower to keep up
Wanted to take advantage of the holiday season (2008)
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Challenge
THUSA needed an efficient process to offer recommended products to customers -- (cross sells up-sells recommendations)
How could the ecommerce team unlock the hidden value of their entire catalog and create more appropriate recommendations (Reach)
How could the ecommerce team automate the process for improving and introducing updates to their recommendations ie create value (Refinement)
The end goal should be to provide relevant results to the customer (Relevancy)
How could the ecommerce team minimize time and effort inside the BCC by working with ATG and their recommendation team (Relationship)
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Product Page
Included ATG recommendation engine on every product page
Optimized the code and catalog feed for 30 days (Fall 2008)
After one month analyzed data and engaged in next steps
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 1 Results
Implementation time was less than four weeks
Two weeks to create and approve data feed between our site catalog and the
recommendation engine
Two weeks to gather sitecustomer behavior
Impact was immediate
13 of revenue ldquotouchedrdquo the recommended products
AOV lift was 12
Conversion rate lift was 163
Contributed incremental +135 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo
checkout
ldquoNo Resultrdquo Search
results page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 2 Reach
Spent two weeks analyzing data
and developing new campaigns
Top sales products
Top Sellers
Accessories
Gift Guide
ldquoLast chancerdquo checkout
ldquoNo Resultrdquo Search results
page
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Phased 2 Results
Impact was immediate
35 of revenue ldquotouchedrdquo the recommended products
AOV lift was flat
Conversion rate lift was 204
Contributed incremental +30 top line revenue
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Phase 3 Offsite Programs
Integrating recommendation engine into
ldquooff siterdquo programs
Confirmation emails
Newsletter sign ups
etc
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Conclusion
Reach
Ability to unlock entire catalog
beyond the product pages
Offering recommendations in email
and other outreach programs
Refinement
ATG recommendations ldquolearnsrdquo
constantly refining based on dozens
of variables
Relevancy
Timely and relevant
recommendations creates value in
product relationships that are not
intuitive to merchants
Relationship
Recommendation team works in
tandem to identify and define future
campaigns (rule sets)
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
ATG Recommendations Webinar | June 18 2009 | Confidential
Questions to ask yourself
How are you going to determine
success
AOV
Contribution margin
Conversion
Time on site
Investment
How to measure ROI
Man power v technology
Control
How much control do you want
How far do you want to reach
Product pages
Category pages
Automated campaigns social
media etc
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You
View the ATG Recommendations Demo at
wwwatgcomrecommendations-demo
Or contact us at salesatgcom
Thank You