-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.

1. Predictive Analytics for Marketers
Managing 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
2© IDC 2013

3. The Business Impact of Predictive Analytics
 A major enterprise software vendor added 200 million Euros to its revenue
line
3© 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
4© 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.
5© 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
6© IDC 2013
45%
Return
%
Incremental
Sales/Mktg Spend
$

7. 2.15
1.92
2.42
2.33
2.40
2.62
2.78
2.13
3.23
CLV data
Proposal data
Deal data
Sales outreach
Sales forecast
Sales qualification steps
Sales revenue potential
Inbound/social
Outbound campaign performance
Four Stages of Data Driven Customer
Creation
7© 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

8. Maturity Model for Predictive Analytics
8© IDC 2013
Departmental Enterprise
Strategic
Tactical
Levelofimpact
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, an
d 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 Availability
Source: IDC 2012

9. Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers

10. 10
Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013

11. 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
11© IDC 2013

12. 12
Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013

13. 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
13© IDC 2013
Marketing Ops
Mgr
+
Intern

14. Growing the Team (15 ppl)
14© IDC 2013
Marketing Ops
or Sales Ops
Systems (6)
Manage
marketing
automation, cam
paigns,
and the CRM
interface
Data (3)
Marketing
data
quality, governan
ce,
and record
enrichment
Analytics (2)
Statisticians
doing descriptive
and predictive
analysis
Process (3)
Interface with
business
sponsors, modeli
ng, and
marketing
operations

15. 15
Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013

16. 16
Lead nurturing
Marketing mix optimization
Enhanced lead scoring
White space analysis
Web UX optimization
Social marketing
Content marketing
Marketing
Lead prioritization
Sales enablement
Opportunity identification
Up selling optimization
Mktg + Sales
Share of wallet
Coverage models
Territory optimization
Pipeline optimization
Compensation modeling
Sales

17. Territory Optimization
17© 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

18. 18
Manage Your Suppliers
Staff Your Kitchen
Develop Your Menu
Serve Your Customers
© IDC 2013

19. 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
19© IDC 2013

20.  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
20© IDC 2013

21. Contact me:
Gerry Murray
Research Manager
IDC CMO Advisory
gmurray@idc.com
© IDC 2013
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