#mitxdata "predictive analytics for marketers" presented by idc
DESCRIPTION
-Gerry Murray, Research Manager, CMO Advisory, IDC How did a major sports and entertainment website boost subscription revenue by 45% without increasing its marketing spend? How did one of the web's most popular financial services sites drive $10Ms of new revenue with simple changes to its user experience? How did a major enterprise software vendor add 200M EUs of revenue without adding sales staff? With predictive analytics for marketing of course. During this session, Gerry Murray (Research Manager, CMO Advisory at IDC) will reveal how to start and grow an analytics team; how to identify the best applications for measurable impact; how to assess and manage issues on the critical path for successful analytics; and how to nurture cultural acceptance of the analytical approach to marketing and sales.TRANSCRIPT
Predictive Analytics for MarketersManaging the Restaurant at the
End of the Big Data Universe
2
Agenda Examples of Business Impact Intro to Predictive Analytics Data Driven Deals Four Stages of Data Driven Maturity Managing Predictive Analytics
• Suppliers• Staff• Models• Customers
IDC recommendations Q&A
© IDC 2013
3
The Business Impact of Predictive Analytics
A major enterprise software vendor added 200 million Euros to its revenue line
© IDC 2013
€200M
Return Incremental Sales/Mktg Spend
€ €
4
The Business Impact of Predictive Analytics
An intern using a .edu license for analytical software doubled the conversion rate from sales lead to oppty justifying a seven figure investment in analytics and data infrastructure
© IDC 2013
200%
Return
% $Incremental
Sales/Mktg Spend
5
The Business Impact of Predictive Analytics
One of the Web's most popular financial services sites drove $10 million of new revenue with simple changes to its customer experience road map.
© IDC 2013
$10M
Return
$ $Incremental
Sales/Mktg Spend
6
The Business Impact of Predictive Analytics
A major sports and entertainment Web site boosted subscription revenue by 45% without increasing its multi-million dollar marketing program spend
© IDC 2013
45%
Return
%
Incremental Sales/Mktg Spend
$
7
CLV data
Proposal data
Deal data
Sales outreach
Sales forecast
Sales qualification steps
Sales revenue potential
Inbound/social
Outbound campaign performance
2.15
1.92
2.42
2.33
2.40
2.62
2.78
2.13
3.23
Four Stages of Data Driven Customer Creation
© IDC 2013
Q. How effectively is marketing able to use the following data sources to inform marketing decisions?
Very Ineffectively
Very Effectively
EffectivelyIneffectively
Stage One:Mktg Funnel
Stage Two:Sales Pipeline
Stage Three: Finance
Stage Four: CLV
Source: IDC 2012
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Maturity Model for Predictive Analytics
© IDC 2013
Departmental Enterprise
Strategic
Tactical
Le
ve
l of
imp
ac
t
STAGE ONE – START
SMALL Marketing
driven by marketing
data alone. Limited to
response based
decision making.
STAGE TWO –
CONNECT TO SALES
Add data from sales.
Marketing driven by
sales pipeline
performance.
Conversion based
decision making.
STAGE THREE –
MEASUREABLE
SUCCESS. Revenue
based decision
making. Add data from
finance, fulfillment,
and services.
Marketing driven by
strategic business
objectives.
STAGE FOUR –
MARKET MASTERY.
Profitability based
decision making. Add
data from support and
account mgmt.
Marketing driven by
customer lifetime value
(CLV).
Scope of Data AvailabilitySource: IDC 2012
Big Data
Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
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Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013
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Manage Your Suppliers Get to know your suppliers and their
production processes. • Where and how often do they source
their data? • What are their QA processes? • Synchronization
Make sure they keep you informed of updates and changes
Differentiate your data from general customer data if necessary
Communicate quality data story to your customers
© IDC 2013
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Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013
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Getting Started (2 ppl)
You can start with a small team Keys to success
• Select small scale starter projects• Work within your own domain• Stealth mode
© IDC 2013
Marketing Ops Mgr
+Intern
14
Growing the Team (15 ppl)
© IDC 2013
Marketing Ops or Sales Ops
Systems (6)Manage
marketing automation, campaigns, and the CRM
interface
Data (3)Marketing
data quality, governance, and record enrichment
Analytics (2) Statisticians
doing descriptive and predictive
analysis
Process (3)Interface with
business sponsors,
modeling, and marketing operations
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Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013
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Lead nurturingMarketing mix optimization
Enhanced lead scoringWhite space analysisWeb UX optimization
Social marketingContent marketing
Marketing
Lead prioritizationSales enablement
Opportunity identificationUp selling optimization
Mktg + Sales
Share of walletCoverage models
Territory optimizationPipeline optimization
Compensation modelingPartner performanceProfitability analysis
Sales
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Territory Optimization
© IDC 2013
- MFG
- TME
- High Tech
- Financial Service
- Government
- Retail
- Transportation
- Media
- Energy
- Services
Summary Analysis
21 Reps Covering 151 accounts. Average 7 of accounts per Rep 9 reps cover 7 or more accounts Average Opp. $ per Rep : $XXM 50% Reps vertically Aligned
Account Vertical
Note: Each name = territory, each circle = an account. Size of circle illustrates size of Opportunity (AMO) Courtesy of EMC
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Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013
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Serve Your Customers Creating a data driven culture
Respect the cautious, their KPIs are on the line
Expect resistance, especially from the powerful
Let your users be the champions It’s all about performance but
models do not sell themselves Socialize your success
© IDC 2013
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Find winnable, measurable projects Engage in controlled exploration Market the models Brand your data Sponsorship and collaboration are essential:
• Senior business leader support is key to acceptance and fostering a culture of data-driven decision making.
• Data analysts and business users need to be embedded in the team.
• Agile process keeps communications open, accelerates delivery, and creates community
IDC Recommendations
© IDC 2013
