This document discusses predictive marketing and its importance. It provides examples of how predictive models can be used in marketing for customer acquisition, management, and other areas. Specific use cases are presented, such as segmentation and prioritizing leads, identifying cross-sell opportunities, and predicting freemium conversions. Predictive marketing is becoming more important as data and technology advance and customer expectations increase.

1. Predictive Marketing:
Competitive Advantage for Today,
Survival for Tomorrow
Host:
Tony Yang
Director of Demand Gen at Mintigo
@tones810
tyang@mintigo.com
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com
Guest Presenter:
David Raab
Principal at Raab Associates
@draab
draab@raabassociates.com

2. HouseKeeping
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3. Mintigo
Enterprise Predictive Marketing
© 2014 Mintigo. All Rights Reserved.
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4. Our Guest Presenter Today
David Raab
Principal at Raab Associates
• More than 30 years in marketing & analyst
• Consulted for major corporations in financial
services, healthcare, telecom & technology
• Author of “Guide to Customer Data Platforms”
and “B2B Marketing Automation Vendor
Selection Tool”
© 2014 Mintigo. All Rights Reserved.
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5. Definition: Predictive Modeling
• Wikipedia:
– “Predictive modeling is the process by which a model is created or chosen to try
to best predict the probability of an outcome. Most often the event one wants to
predict is in the future, but predictive modeling can be applied to any type of
unknown event, regardless of when it occurred.”
• Practical Features:
– Based on patterns in data
– Requires known previous outcomes
– Output may be binary, value, classification
– May use regression, clusters, trees, neural nets, etc.
– Not perfect!
© 2014 Mintigo. All Rights Reserved.
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6. Predictive Models in Marketing
• Traditional applications
– Incremental (business could exist without them)
– B2C examples: mix models, customer support triage
– B2B examples: list segmentation, lead scoring
• Predictive marketing applications
– Foundational (business can’t exist without them)
– B2C examples: real time bids for ads, airline yield optimization, credit
scores, real time fraud detection
– B2B examples: lead generation, customer experience
© 2014 Mintigo. All Rights Reserved.
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7. Poll
Have you applied predictive modeling to your
marketing efforts?
• No, I’m just starting learn about it now
• No, but I want to know how I can apply it
• Not at my current company, but I have some prior experience
• Yes, we’re starting to apply predictive modeling at our company
• Yes, we’ve been using predictive modeling successfully for awhile
© 2014 Mintigo. All Rights Reserved.
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8. The Predictive Marketing Syllogism
Business success depends on customer
experience, and
Customer experience depends on predictive
marketing.
Therefore, business success
depends on predictive marketing.
© 2014 Mintigo. All Rights Reserved.
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9. Why Now?
• More data
• Automated technology
• New applications
• Customer expectations
• Platforms
© 2014 Mintigo. All Rights Reserved.
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10. Predictive Marketing Applications
• Acquisition
– Prospecting
– Lead scoring
– Segmentation
© 2014 Mintigo. All Rights Reserved.
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11. Predictive Marketing Applications
• Customer Management
– Recommendations
– Contact optimization
– Next product prediction
– Churn prediction
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com

12. Predictive Marketing Applications
• Beyond Marketing
– Sales
– Service and support
– Risk and fraud
© 2014 Mintigo. All Rights Reserved.
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13. Predictive Marketing Applications
• Measurement
– Attribution
– Forecasting
© 2014 Mintigo. All Rights Reserved.
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14. Summary
• Predictive marketing includes many apps
• Customer experience is key driver
• Advantage is cumulative
© 2014 Mintigo. All Rights Reserved.
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15. USE CASE #1
SEGMENTATION & PRIORITIZING LEADS
© 2014 Mintigo. All Rights Reserved.
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16. • B2B
SaaS
Core
Product:
VisitorTrack
• Global
clientele
across
various
industries
such
as
tech,
manufacturing,
HR,
&
retail
• Lots
of
leads,
no
scoring
system
previously
© 2014 Mintigo. All Rights Reserved.
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17. Segmentation Identifies Great Leads
• A:
Great
fit!
Both
company
&
prospects
match
netFactor’s
CustomerDNATM
• B:
Company
fit,
but
prospect
doesn’t
match
buyer
profile
• C:
Company
does
not
match
CustomerDNA
• D:
Low
quality
data
(i.e.,
bad
emails)
© 2014 Mintigo. All Rights Reserved.
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18. USE CASE #2
SEGMENTATION, CROSS-SELL & UPSELL
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19. © 2014 Mintigo. All Rights Reserved.
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20. They Have A Lot Of Great Data
Explicit-Demo/Firmographic
• Contact data
• Job title
• Industry
• Custom fields
Implicit-Behavioral
• Web visits
• Email engagement
• Content downloads
• Webinar reg/attendance
• Trial downloads/activations
• Product usage
• Form completions
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com

21. Great Rates, but wait…
Sales
Promo
CR
by
Lead
Score
0.05
%
0.14
%
0.81
%
2.15
%
2.50%
2.00%
1.50%
1.00%
0.50%
0.00%
Great conversion rates, but:
• Limited to track-able implicit behavior and explicit form completions
• Scoring data = time to collect, build, maintain
• We are only human!
© 2014 Mintigo. All Rights Reserved.
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22. Predictive Model Identifies Target & Cross-Sell
Opportunities In Real Time
Test
Dev
© 2014 Mintigo. All Rights Reserved.
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Ops
42
82
19
24
11
95
77
79
35
6

23. “A Leading File Sharing/Cloud Storage Provider”
USE CASE #3
FREEMIUM CONVERSION
© 2014 Mintigo. All Rights Reserved.
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24. 1st Goal –
Identify Needles In The Haystacks
Challenges:
• Freemium & Free Trial SaaS Provider
• Large database (millions of contacts)
• Large amount inbound (free user,
inquiries)
• Very few sales reps
• No current lead scoring system
What They Need
• Better way to look for potential buyers of premium subscriptions
within free user base & inbound
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com

25. Predictive Model Found Common Traits Of
Converted Freemium Users
2.5X
Li4
Privacy/Security
related
aNributes
(Truste,
SSL,
Hiring
security
compliance
posi8ons)
2.2X
Li4
Manufacturing
related
aNributes
(CAD
and
CAM
usage,
supply
chain)
1.6X
Li4
Tools
That
Integrate
With
Their
Product
(Salesforce.com,
MS
Exchange
or
SharePoint)
1.4X
Li4
Remote
Workforce
aNributes
(BYOD,
field
workforce)
© 2014 Mintigo. All Rights Reserved.
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26. Potential Next Steps?
• Export data from their product on user behaviors, usage data and
features accessed by converted free users
• Run predictive model on this data set to find common behaviors that
correlate to the most lift
• Create a rules-based behavior scoring in MAP to identify activities of
free users that perform these activities
• Modify nurture programs to drive users towards accessing these
features in the product
© 2014 Mintigo. All Rights Reserved.
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27. USE CASE #4
LEAD SCORING, EXPANDING INTO NEW MARKET
© 2014 Mintigo. All Rights Reserved.
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28. Mintigo’s Sweet Spot
– Job Titles:
• Demand Gen, Marketing Operations
• General Marketing Management
– Company Size of 1,000 employees and above
– Users of Eloqua, Marketo and/or Salesforce.com
– High Tech vertical, companies such as:
© 2014 Mintigo. All Rights Reserved.
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29. Expanding Into Financial Services
© 2014 Mintigo. All Rights Reserved.
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30. Traditional Scoring based on:
– Job Titles:
• Demand Gen, Marketing
Operations
• General Marketing Management
– Company Size of 1,000
employees and above
– Users of Eloqua, Marketo and/or
Salesforce.com
– Industry = Financial Services
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com
Predictive Scoring based on:
Traditional firmo/demographic score to determine fit for new market,
Predictive score to determine propensity to buy

31. © 2014 Mintigo. All Rights Reserved.
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Predictive Score identifies
propensity to buy
Traditional Score shows fit based
on demo/firmographic data

32. Q&A
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com

33. Want To Learn More? Go to www.mintigo.com/resources
New
eBook:
“Why
Modern
B2B
Marketers
Need
Predic3ve
Marke3ng”
By
David
Raab
Webinar
Replay:
“Demys3fying
Predic3ve
Lead
Scoring”
Guest
Presenter
from
SiriusDecisions
Webinar
Replay:
“Predic3ve
Marke3ng:
The
Science
Behind
Marke3ng”
Presented
by
Min8go
Chief
Data
Scien8st
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com

34. THANK YOU!
Host:
Tony Yang
Director of Demand Gen at Mintigo
@tones810
tyang@mintigo.com
© 2014 Mintigo. All Rights Reserved.
www.mintigo.com
Guest Presenter:
David Raab
Principal at Raab Associates
@draab
draab@raabassociates.com