championing the seamless shopping experiencemedia.dmnews.com/documents/320/dmn_ebook_shopp… ·...

From platforms that deliver location-based content, to predictors of what customers will buy, technology is primed to deliver personalized, unique interactions to the delight of customers

Championing the Seamless Shopping Experience

Sponsored by

dmnews.com | SHOPPER ANALYTICS 2

SHOPPER ANALYTICS

TABLE OF CONTENTS

T oday’s retail customer, that 21st century consumer of mobile, tablet, and computer technology, is not all that different from customers of days gone by.

It turns out that whether you were a 1950s customer pur-chasing dresses from the local shop on Main Street, or are a modern customer using your mobile phone to purchase from an online website, you basically want the same thing: a person-alized service and a shopkeeper that understands your prefer-ences and habits.

That 1950s shopkeeper knew his or her customers’ prefer-ences, habits, and information and used this data to personalize the shopping experience, explained Traci Milholen Inglis, in the article “Learning From Retailers Past: How TechStyle Modernizes Personalization.” “And while e-commerce retailers house this same information in their databases today,” she wrote, “few use it to replicate this level of personalization.”

TechStyle’s brilliant use of data puts them in a much desired position: It has a 95% accuracy rate for predicting inventory demand. This drastically reduces obsolescence of product — one of the big enemies in traditional retail.

Of course, there are big differences in the modern shopping experience. Customers expect to move seamlessly between dig-ital and physical channels — ordering online to pick up in-store; browsing in-store to order online.

Today’s in-store shopper will soon be every bit as connected as the shopper online — if he or she isn’t there already. This level of connectivity offers marketers an opportunity, using cutting-edge location intelligence, to track customers’ trajecto-ries and purchase intentions, and to offer targeted content as they browse in a store.

In this eBook, you’ll learn how analytics is revolutionizing retail marketing, helping to create those unique, personalized experiences today’s customers crave.

Kim Davisexecutive editorDMN

The analytics of shopping

Learning From Retailers Past: How TechStyle Modernizes Personalization

Five Lessons Marketers Can Learn from Airbnb’s Data Science Manager

Locye’s Location-Based Social Media Platform Brings Marketing Capabilities into the Mix

Blis Brings its Location Intelligence to U.S. Shores

Data and Optimization are T.O by Lipton’s Cup of Tea

3

5

6

7

9

9

SHOPPER ANALYTICS


P ersonalization may be the buzzword du jour, but it isn’t something modern marketers invented. Just look at shopping in the

United States in the 1950s.Imagine a small dress store in a typi-

cal town, next to the soda shop and the Kodak store. When a female customer walked into the shop, the shopkeeper would greet her: “Good morning, Ms. Inglis. We haven’t seen you in a few weeks — welcome back. I have a new shipment of dresses that you’ll love, and they’re in your price range.”

That shopkeeper knew his custom-ers’ preferences, habits, and informa-tion and used this data to personalize the shopping experience.

And while e-commerce retailers house this same information in their databases today, few use it to replicate this level of personalization.

Unique human connections are hard to replace, but digital personalization

Learning From Retailers Past: Modernizing PersonalizationHow TechStyle leverages data to tap into customers’ preferences and habits By Traci Milholen Inglis, CMO, TechStyle

can produce similar interactions and create benefits that never existed in commerce before. We know who likes magenta dresses and how often they shop. We recognize them by name and are aware of their price sensitivities. Let’s start using this data to give cus-tomers a better shopping experience.

Here’s how we do it at my company.

NEW MARKETING INNOVATIONAt JustFab, a membership-based global fashion retailer owned by Tech-Style, we personalize the customer experience from her first brand en-gagement. We start with a quiz and ask her about style preferences, cloth-ing and shoe sizes, her color prefer-ences, and her ZIP Code. We try to replicate the ways of that shopkeeper of the 1950s, with a per-sonalized welcome and information gathering with the Q&A.

From there, we continue to observe and record the customer’s preferences

by examining browsing and purchase activity, much like a retail employee would do for their regular customers. We then use that information to refine and personalize her shopping experi-ence on the site, such as with targeted emails and print catalogs.

This approach not only helps us create a personalized shopping expe-rience for our customers, but it also eliminates waste: We have a 95% ac-curacy rate for predicting inventory demand. This drastically reduces ob-solescence of product — one of the big enemies in traditional retail.

JustFab, one of four TechStyle Fash-ion Group brands (Fabletics, JustFab, FabKids, ShoeDazzle), collects, an-alyzes, and parses its data through TechStyle’s global fashion commerce platform.

Our system, which integrates mem-bership commerce and personaliza-tion with data science, is focused on presenting customers with the right

Unique human connections are hard to replace, but digital personalization can produce similar interactions and create benefits that never existed in commerce before

Traci Milholen Inglis, TechStyle

SHOPPER ANALYTICS

message and the right product at the right time.

LESSONS LEARNEDPersonalized communication: delivering the right messageRecently, we launched a test that of-fered the same promo to three groups of VIP customers who were shopping less frequently.

One group, the control group, re-ceived the promo alone; the second group received the same promo with a message saying they were “one of our best customers;” and the third group received the same promo with a message stating: “We miss you.”

While all three delivered nice reve-nue lifts, the “We miss you” message hit home and drove a 103% revenue spike compared to the control group. By simply adding a relevant message, we saw a substantial pickup in en-gagement and revenue.

Remember, relevant messaging must be tailored to the customer.

Personalized merchandising: delivering the right productOur messaging strategy now offers personalized product recommenda-tions for each customer. These rec-ommendations are based on the deep data analysis we do, which includes examining everything from what a customer buys, to what she isn’t in-terested in, to what she may want in the future.

We saw an 84% lift in revenue once we began deploying personalized

product messaging in our emails. We’re now advancing this successful approach and testing videos that high-light products a customer abandoned in her cart.

Customers want to see relevant products through a curated selection tailored to them.

Timing is everything: delivering at the right momentClearly, a personalized experience requires the right product and the right message, but it also requires the right timing.

Like most retailers, we know the av-erage amount of time it takes before a customer is deemed “lapsed.” But we also know that while averages are great for reporting, they don’t always translate to marketing campaigns.

After six months of customer in-activity, we could set up a standard lapsed campaign that would trigger an email or a direct mail piece saying “We miss you.” However, this would be an odd message to receive if you’re

a customer who shops every six months. And for customers who shop weekly, this message is far too late.

To remedy this issue, we developed an algorithm that can determine the average shopping cycle for each indi-vidual and calculate, in real time, how far away she is from her typical shop-ping pattern.

“Lapsed” could mean two weeks for one customer and eight months for another. Whatever her frequency, we deliver the right message at the right time for her. This algorithm-based, data-driven strategy pleased shoppers — driving a 22% lift in best customer retention.

The key is to schedule your messages when consumers want to receive them.

Value of retail customer data keeps expandingDeep customer data and analysis don’t just benefit marketing conversions; they also benefit product merchan-dising and design. Customer feedback and insight help improve products and stimulates new innovation

Personalization has evolved over the past five decades, and surviving in re-tail will require the same level of at-tention that shopkeepers once showed new and loyal customers.

The future of retail is about devel-oping a rapport and continuing the conversation, all while using emerging data science tools and platforms that react dynamically, on an individual level, to provide each customer with the best experience possible. n

— Traci Milholen Inglis, TechStyle

Customers want to see relevant products through a curated selection tailored to them



SHOPPER ANALYTICS

D uring a measurement event held earlier this year at Facebook’s New York office, Airbnb’s data science manager Alok

Gupta joined Facebook’s VP of global marketing solutions Carolyn Everson to discuss performance measurement trends with customers. Here are five key performance measurement take-aways based on insights from Gupta.

1. Justify your marketing spend with data. And be upfront when you can’tWhen it comes to determining which channels to invest in, there’s only one way to know for sure: test and mea-sure. “We will only spend where we are able to measure,” Gupta said.

While measuring digital channels such as email has become easier, many marketers still struggle with tracking the effectiveness of traditional chan-nels, such as billboards or TV. Gupta still views these channels as “strategic” and said Airbnb does try to run tests on these channels and invest in them. However, he’s upfront in terms of ex-pressing these channels’ measurement limitations, especially when compar-ing traditional channels’ performance metrics to those of digital channels.

“Be realistic about the decisions that need to be made,” he said.

2. Understand that the lines between brand marketing and direct marketing are blurredBrand marketing and direct market-ing can sometimes be viewed as sep-

arate. One focuses on top-of-funnel metrics, such as awareness, while the other focuses on bottom-of-the- funnel metrics, for example, conver-sion. However, Gupta noted that the divisions between these two areas are beginning to dissolve.

“We have some notion of advertising or marketing for the purpose of brand awareness over the long term and a strategy for performance we want to measure,” he explained. “But, these lines are being increasingly blurred.”

3. Adopt a systematic test-and-learn mentality and experiment oftenAirbnb’s data science team works with marketing to take a “systematic ap-proach to evergreen experimentation,” Gupta said, which includes creating hypotheses, testing them rapidly, and then rejecting or confirming them.

In one Airbnb test, for instance, Gupta and his team tried to determine whether creatively targeting new users would actually generate a ROI, hypoth-esizing that it would give new users with high intent the nudge they needed to convert. The test showed otherwise, demonstrating that the amount of mon-ey generated from this creative was not as much as the brand had spent.

While the ROI was negative, Gupta and his team identified a “sweet spot of intent.” When they targeted this specif-ic group, the brand was able to spend “just enough dollars” to produce a pos-itive ROI. “It’s called marketing science for a reason,” he said in regards to his experimentation philosophy.

4. Be open to collaborationAirbnb’s data science team works with marketing throughout the purchase funnel. The brand also works with third-party vendors, such as Facebook.

While Facebook has been “very re-ceptive” to the brand’s needs, Gupta admitted that, as an advertiser, there’s always more Airbnb would like Face-book to do. In terms of data logging and customization — Gupta would like to see more household data versus

individualized data since most people in the same household go on vacation together. “The key message is that the requests will never end,” he added.

5. Know that measurement mistakes will happenFacebook made headlines in 2016 for miscalculating its average duration of video viewed metric. However, as long as bugs are identified quickly, corrected thoughtfully, and happen infrequently, that’s really the best advertisers can expect. As Gupta put it, “We’re never going to build the perfect system.” n

Five Lessons Marketers Can Learn from Airbnb’s Data Science ManagerThe marketplace for short-term home rentals relies on data and testing and learning to drive ROI By Elyse Dupré

— Alok Gupta, Facebook

We have some notion of advertising or marketing that we want to measure, but these lines are blurred

SHOPPER ANALYTICS


L ocye’s location-aware, social- media platform allows us-ers to observe social activity at real-time hotspots and to post content so that those

who are nearby can see. And for those who don’t want to give

too much away, there is an option to post anonymously. The platform will soon offer B2C marketing capabilities with three defining characteristics:

1. New types of location-based ads Locye is a location-based social media platform where all user interactions and content have a geographic element.

“Our marketing engine will be able to leverage our capabilities of extremely quick and precise analysis and delivery of location-based content to offer new types of location-based ads and other content for marketers,” explained Locye founder and CEO, Sajjad Mustehsan.

While content can include traditional radius or polygon-based ads — the kind that retailers draw on to get the attention of shoppers passing nearby — Locye takes it further. Tapping into the power of AR, Locye can guide interested shop-pers to the exact location of where the product is physically located within the store, helping to drive the purchase.

2. Precise ad targetingSocial media marketing efforts don’t always result in the ROI brands want, often the result of ineffective targeting. “Most social media platforms,” noted Mustehsan, “rely on user-entered infor-mation, browsing and usage histories,

Locye’s Social Platform Brings Marketing Capabilities into the MixComing soon: delivery of location-based content for new types of location-based ads By Ariella Brown

and imprecise estimates of their location — all three of which could be inaccurate and be non-representative of the user’s actual interests” — or budget.

Locye counters the false impression users can create from their search histo-ry by contextualizing it with other data.

“By leveraging our expertise in fusing demographic and place data with an-onymized logs and then applying AI to the resulting dataset, our marketing en-gine will be able to accurately paint a pic-ture of the consumer’s current and past interests, capabilities, and what segment of the community tapestry to which they belong,” said Mustehsan.

These form the basis of precise ad tar-geting, providing a better ROI for the marketer and an improved experience for the end-user, who only sees market-ing content that appeals to her taste, po-sition, and purchasing abilities.

This precision in targeting leads to more effective marketing. For example: A high-end resort precisely shows its ad at around dinner time to high-income consumers who are taking a road trip, heading in the direction of the resort, and are less than 30 minutes away.

3. Private label and co-branding opportunitiesAlthough most businesses have their own app these days, “most offer the same content and capabilities to the end user as to what’s on existing websites, and don’t really add a marketing bene-fit,” observed Mustehsan.

Instead of trying to do it themselves, brands can “leverage Locye’s capabilities

of gathering, analyzing, and delivering location-based content.”

For example, if a user is near an amuse-ment park, the park could send out tar-geted content for its activities, or for spe-cific establishments that operate within it. Not only can general promotions for the park or coupons be sent, but so could content such as information about wait times for particular rides.

That level of real-time information is key for marketing at the moment of deci-sion, and it also has additional value.

“Locye will provide real-time analyt-ics on what parts of the park are seeing the most crowds and how long patrons are willing to wait for an attraction be-fore moving on,” said Mustehsan. These analytics go beyond improving the customer experience, delivering data- driven insights for marketers. n

SHOPPER ANALYTICS


B lis, the mobile location and behavioral advertis-ing vendor, which runs its product and engineering out of London, has been

around for approximately 10 years in the U.K. “We’ve always been in the location business — even before Blue-tooth,” said Amy Fox, head of product at Blis.

“We have our own technology, in-house,” explained Fox, “and we’re location-first.” Blis is also making a splash with Blis Futures, an AI- powered product that not only pre-dicts, but also guarantees future consumer behavior. In practice, that means that participating brands are only charged if consumers do what Blis predicts they’ll do. That’s certain-ly a differentiator — and it’s a bold bet on the power of location-based predictive analytics.

“Where people go defines who they are,” is Blis’ mantra.

BEHIND THE TECHBlis mines location data from vari-ous sources to track consumers’ tra-jectories. “A large number of IPs are incredibly unstable,” Fox explained, “but there is a significant subset that is static enough for a long enough pe-riod of time.”

Blis’ IP database updates in real- time, breaking connections with IP addresses if instability is detected “Other databases in the market update maybe once a month,” said Fox.

GPS tracking is permission-based,

Blis Brings Its Location Intelligence to U.S. ShoresMaking a splash: AI-powered Blis Futures, which guarantees future consumer behavior By Kim Davis

and is “fairly restrictive,” explained Fox. Travel and weather apps are the best source. There’s also Wi-Fi data, which is much more widely available from major networks.

Publishers’ data is added to the mix, along with data purchased from big data vendors: Blis processes almost two terabytes of data per day. The product of the process: addressable audiences, enhanced with contextual location data — where they’ve been, where they are, and where they’re going.

The data flows through two pro-prietary technologies, Smart Pin and Smart Scale. Smart Pin is a multi- level filtering process that eliminates inaccurate location data. Smart Scale matches Wi-Fi, GPS, and stable IP data with specific geo-locations. Blis maintains a significant POI — points of interest — geo database.

The data layer powers a large range of advertising tech capabilities, including PrivateExchange, a programmatic trad-ing desk; Proximity, which targets audi-ences based on distance from defined lo-cations; Audiences, which targets based on location and contextual data; and Fu-tures, which uses AI to identify consum-ers most likely to visit defined locations, and targets ads to drive them there.

WHO IT’S FOR“Agencies are currently our focal point. However, our approach to work-ing with marketers is collaborative and we will work with them in the capaci-ty they prefer,” explained Gil Larsen, VP, Americas. “Whether they’d like to

work through their agency, or directly with Blis, we meet marketers’ demands where it makes most sense for their company in order to help them achieve their business goals.”

Looking to be adaptive to the U.S. market, Blis is offering agencies and other customers different ways to use its services. There’s a self-service op-eration, specifically for trading desks,

Agencies are currently our focal point, however, our approach to working with marketers is a collaborative one and we will work with them in the capacity they prefer

Gil Larsen, Blis

SHOPPER ANALYTICS


whereby Blis delivers an agreed au-dience and reach via a chosen DSP. There’s integration with Blis’ own programmatic trading desk, Private-Exchange. And there’s the full-service option, with Blis working alongside a customer to achieve business objec-tives, delivering expert advice.

THE FUTURE: GUARANTEEDBelgian brewer Stella Artois is an early adopter of Futures, working with me-dia network Vizeum. Based on large volumes of historic data, Blis uses AI to identify the “pool” most likely to drive foot traffic: and charges a cost per visit.

“The interesting thing about Fu-tures,” said Fox, “is that we don’t set the rules ourselves.” The AI layer gets

“incredibly detailed guidelines, but we don’t dictate how it gets there.”

One condition of success with Fu-tures is leveraging data from a broad audience pool, such as lager drinkers. “If a client is incredibly picky about segments, Futures isn’t for them,” Fox explained. “It isn’t going to have enough volume.”

Clients also need to be prepared for Futures to contradict their long-held beliefs. One client, a diaper brand, was targeting women until Blis data told them that the purchases were be-ing made by men on their way home from work. “We have to get brands to think differently,” Fox said. They need to “let the technology find the audiences for them.” n

Striking Matches with MaxPointOrganizations can now mix product acquisitions

MaxPoint’s unified platform for multi-channel marketing (not including email automation), built around the Customer Catalyst software product, strikes matches between physical addresses and household devices, surfacing real- time interest and thus generating meaningful engagement with in-market audience segments. In simple terms, it ties digital activity to CRM data — currently for some 100 million U.S. households, explained Amy King, director of product marketing for MaxPoint, a Raleigh, North Carolina-based marketing technology company.

The resulting identity graph is also tied to location intelligence,

based on dividing the country into 44,000 neighborhood geo- locations (“digital zips,” an ap-proach MaxPoint has also expand-ed to Europe). This is sourced not only from device GPS, but also from the sub-set of relatively sta-ble IP addresses associated with the 80 billion daily programmat-ic bid opportunities. This data enables hyper-local cross-channel campaigns, aimed at digital zips that signal interest and intent with respect to advertisers’ offerings.

MaxPoint also announced en-hanced matching and list-building capabilities recently, including linking email addresses with physical households, and the

use of propensity models to add lookalike individuals to existing, CRM-based household lists.

While MaxPoint’s full service offering includes activating audi-ence intelligence through digital advertising and social channels, the audience segments can also be exported to partners such as Oracle, Adobe, and LiveRamp to be activated for any purpose.

Matching CRM data with real- time indications of interest and location intelligence is powerfully enriching: the profiles on Max-Point’s graph feature around 1,300 variables, King said. — Kim Davis

Amy Fox, Blis

We have to get brands to think differently. They need to let the technology find the audiences for them

SHOPPER ANALYTICS


How the loose-leaf tea machine brand uses consumer data and AI to drive optimization and conversion By Elyse Dupré

I n marketing, it is good to have a strong intuition. But for Mathieu Bernard, intuition only goes so far. The head of e-commerce for Unilever brand

T.O by Lipton said he backs up his intuition by looking at the data.

“We have a lot of data to process coming from thousands of consumers,” Bernard added. “The challenge is to put the focus on data we trust and can leverage and transform into opportunity.”

While Bernard’s main mission is to acquire new T.O by Lipton customers and ultimately retain them, it can be difficult to decipher why one customer bought a tea machine or tea capsule and why one did not. He wanted to find a turnkey solution that would allow him to gather analytics quickly. So a few years ago, he and his team implemented UX analytics solution ContentSquare.

DIVING INTO THE DATAT.O by Lipton started working with ContentSquare in 2015 before the brand even launched. The company inserted a line of code on its website and then used cookies to record, compute, and analyze customers’ data, like mouse movements and clicks. Before its debut, the brand invited about 500 people to shop its website, Bernard said, and then used ContentSquare to gather insights and optimize its site before launch.

Since then, T.O has continued to use the solution for analytics and A/B

Data and Optimization are Lipton’s Cup of Tea

testing. For instance, the company ran an A/B test on its product page to optimize conversion. For the test, Bernard created about 15 different product page layouts and altered the placement of ratings and reviews in each one.

He discovered that when the ratings and reviews were placed near the top of the page and were more visible, they generated higher engagement and higher conversion rates.

EFFECTIVE MEASUREMENTThe brand also used the vendor to examine consumers’ web interactions and measure the efficiency of zones or elements on T.O’s web pages.

This helped the brand pinpoint which areas led to decreased engage-ment and performance. Based on this behavioral data, T.O identified two customer segments: returning cus-tomers and new visitors, explained Patricia Césaire, senior solution con-sultant for ContentSquare.

The brand’s digital team then isolated each segment’s customer journey and saw that the returning customers were showing “back-and-forth browsing activity,” she noted, which suggested confusion.

After reviewing metrics such as hesitation rate on its various page zones, she added, T.O pinpointed which areas were causing this confusion and ended up streamlining the purchase process, such as by including related purchase items on its pages with distinct calls-to-actions

to help consumers avoid cross-referencing multiple pages.

This year, the brand started leveraging ContentSquare’s latest develop-ment: an AI-powered bot named Arti.

By leveraging ContentSquare’s ana-lyzed data, machine learning, and

After reviewing metrics such as hesitation rate on its various page zones, T.O pinpointed which areas were causing confusion among customers and ended up streamlining the purchase process — Patricia Césaire, ContentSquare

SHOPPER ANALYTICS

customer feedback, Arti can make recommendations to various members of the T.O team for how they can optimize the brand’s customer journey or content. T.O’s CRM manager might receive recommendations on funnel optimization while an acquisition manager might receive recommendations on how to drive web conversion, Bernard explained. It can also notify different team members of changes in metric performance.

“This is really helping us prioritize our actions,” Bernard said.

GENERATING RESULTSSince implementing ContentSquare, T.O has increased its conversion rate by “more than 100%,” Bernard said — 105% by the vendor’s count. Con-tentSquare also reported that Arti has helped the T.O team save time by up to 30%. In addition to these measurable wins, Bernard noted that implement-ing the solution has helped encourage this test-and-learn mentality — even when the tests aren’t always successful.

“Failure is part of the progress,” he explained.

Still, Bernard isn’t completely satis-fied. When asked about where he’d like to improve, his reply was simple: “Be-ing faster” and continuing to test and learn. As he put it, “It’s very important when you do analytics on anything to work at a quick pace.” n

We have a lot of data to process coming from thousands of consumers. The challenge is to put the focus on data we trust and can leverage and transform into opportunity

Mathieu Bernard, T.O by Lipton


7,500 + Attendees • 2,500+ Companies • 700+ CEOs • 400+ Speakers • 60+ Countries

SHOPTALK'S HOSTED RETAILERS

& BRANDS PROGRAM OFFERS

QUALIFYING RETAILERS AND BRANDS:

FRIEIE TDCIIIET providing access to all aspects of

SHOPTALK

& TRAVEL$750 &HOTEL Allowance

All meetings are curated and double opt-in to ensure they're valuable to retailers and brands as well as our exhibitors and sponsors. There's no ·catch' or 'fine print'--it's a

win-win-win for us, retailers & brands as well as exhibitors and sponsors.

APPLY NOW FOR THE

HOSTED RETAIL & BRANDS PROGRAM

- SPACES ARE LIMITED -

www.shoptalk.com

ANN INC. JCPenney ANTHROPOLOGIE

IMARC JACOBS

��-CLINIQUE

*macys GUESS MICHAEL KORS

PERRY ELL IS ToYsJlus Gap Inc.

fD. west elm

HERE ARE THE 10 MOST COMMON WORDS PROCiRAM PARTICIPANTS

USED TO DESCRIBE THE PROCiRAM IN A POST-EVENT SURVEY:

! Awesom£) �elpful ! ! ExcellenSJ

! worthwhiliJ ! 1nformat1v€) �onvenient !

LEfficient ! ! Useful J .... l5'a1uable I

! Beneficia(J

AND HERE IS THE KEY QUANTITATIVE FEEDBACK THEY SHARED

.

• Were your meetings worthwhile?

Has there been any follow upor do you plan to follow up onany of the meetings?

http://www.shoptalk.com

championing the seamless shopping experiencemedia.dmnews.com/documents/320/dmn_ebook_shopp… ·...

Documents