Is your organization challenged by the explosion of data and increasing expectations for results? Unica Campaign Management and IBM Netezza appliances can provide capabilities to address and overcome them. This presentation offers customer case histories and performance studies that provide insights in today's world where digital and traditional channels are increasingly intertwined.

1. Big Data, Bigger Campaigns
Using IBM’s Unica & Netezza Platforms
to Increase Marketing ROI

2. Agenda
1) Observations on “the empowered
customer” and “big data”
2) IBM Netezza & IBM Unica in the age
of big data: good on their own, great
together
© 2012 IBM Corporation

3. • IBM’s statements regarding its plans, directions, and intent are subject to
change or withdrawal without notice at IBM’s sole discretion.
• Information regarding potential future products is intended to outline our
general product direction and it should not be relied on in making a purchasing
decision.
• The information mentioned regarding potential future products is not a
commitment, promise, or legal obligation to deliver any material, code or
functionality. Information about potential future products may not be
incorporated into any contract. The development, release, and timing of any
future features or functionality described for our products remains at our sole
discretion.
Performance is based on measurements and projections using standard IBM benchmarks in a
controlled environment. The actual throughput or performance that any user will experience
will vary depending upon many factors, including considerations such as the amount of
multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and
the workload processed. Therefore, no assurance can be given that an individual user will
achieve results similar to those stated here.
© 2012 IBM Corporation

4. The age of the “empowered customer”
86% 78%
use multiple of consumers
channels trust peer
61% recommendations
4 in 10
trust friends’ Smart phone
reviews more users search for
than experts’ an item in a store
75% 44%
do not of companies
believe use crowd
companies sourcing from
tell the truth customers
in ads
58% 4-5x
are more price-
conscious today
than they were a 80% 8% more than
average is
spent by multi-
year ago of CEOs think of their
channel buyers
they deliver a customers
superior agree
customer
4 experience

5. Empowered marketers need a “system of
engagement”
Analyze Decide
marketing data to find on the best
actionable insights marketing action
Collect Deliver
data that augments engaging messages
each customer profile and capture reactions
heavily impacted Manage
by big data marketing processes and
measure results
© 2012 IBM Corporation

6. Support calls
Platform Capabilit
Transactions
Clickstream
Marketeer’s objectives
Events
CRM
1 Single view of customer
Matrix computations Feature Selection
Single Value Decomp.Associations
Clustering
Matching algorithms Scoring
2 Increased Targeting Precision
Personalized message
Consolidation
3 Improved Relevance
4 Higher campaign profitability Segmentation
Forecasting
Optimization
Predictive algorithms
Decision trees
Linear Regression
D I G I T A L M E D I A | Page 6
Matching

7. Support calls
Platform Capabilit
Transactions
Clickstream
Marketeer’s objectives
Events
CRM
1 Single view of customer
Matrix computations Feature Selection
Single Value Decomp.Associations
Clustering
Matching algorithms Scoring
2 Increased Targeting Precision
Big Data
Personalized message
Consolidation
3 Improved Relevance
4 Higher campaign profitability
Complex Analytics
Segmentation
Forecasting
Optimization
Predictive algorithms
Decision trees
Linear Regression
D I G I T A L M E D I A | Page 7
Matching

8. Digital Media firms leverage Big Data analysis to
deliver relevance and discover insights
Right message.
Right person.
Right time.
Right price.
© 2012 IBM Corporation

9. The Information to Audiences White Paper
• IBM & Acxiom Sponsored Research
– Research conducted by Winterberry Group
– In association with the Interactive
Advertising Bureau (IAB)
– Interviewed 175 advertising and marketing
thought leaders
– Findings published at http://bit.ly/x5g1dW
– Infographic on AnalyzingMedia.com at
http://bit.ly/HYJUwb
© 2012 IBM Corporation

10. To What Extent Do You Believe The Following Solutions Will Be Focal
Points of Your Future Data-Driven Marketing Activity?
Not likely to be a Likely to be a
focus of our future significant focus of our
data utilization future data utilization
Source: Winterberry Group survey © 2012 IBM Corporation

11. To What Extent Do You Believe The Following Solutions Will Be Focal Points
of Your Future Data-Driven Marketing Activity?
1. Audience
1. Audience
1. Audience
2. Content 2. Content
2. Content
3. Channel
3. Channel
3. Channel
4. Yield
4. Yield
Not likely to be a Likely to be a
focus of our future significant focus of our
data utilization future data utilization
Source: Winterberry Group survey © 2012 IBM Corporation

12. 1. Solution: Audience Optimization
(Ad Targeting)
Business Effectiveness: Identifying customers
Benefit and likely prospects through the
integration of first- and third-party data
sources
Customer Low: Despite technology advances,
Maturity Level uncertainty around the optimal
approach to structured integration of
data
Core E-commerce Marketers, Digital
Beneficiaries Advertisers, DSP, SSP, DMP, Lead
Generation Portals, Publishers
IBM Big Data Customers
Long-Term High: The ability to define high-
Opportunity potential audiences and facilitate
Potential multichannel communication
represents a fundamentally new way of
marketing
High Impact 1. Behavioral Segmentation
Use Cases 2. Real-Time Ad Targeting
3. Social Data Analytics
© 2012 IBM Corporation

13. 2. Solution: Content Optimization
(Website Analytics)
Business Effectiveness/ Efficiency: Enabling
Benefit “right message, at the right time, via
the right content” targeting; drive
content monetization via personalized,
relevant and engaging content
Customer Low: Content optimization is limited to
Maturity Level usage analysis via SaaS based web
analytics tools; disconnected
experience
Core E-commerce Marketers, Lead
Beneficiaries Generation Portals, Publishers
IBM Big Data Customers
Long-Term High: The ability to analyze granular
Opportunity level click-stream data and integrate
Potential that information with actionable
systems presents an opportunity to
unlock greater business value than
traditional SaaS based tools
High Impact 1. Path analysis
Use Cases 2. A/B Testing
3. Rich Media Engagement
© 2012 IBM Corporation

14. 3. Use Case: Yield Optimization
Business Efficiency: Maximizing the value of
Benefit available advertising inventory by
identifying and “selling” high-value
audiences across individual publisher
properties
Customer Low: Though technological advances are
Maturity Level rapidly allowing audiences to be “sold”
across distinct online media platforms, the
use case demands true cross-channel yield
optimization
Core Publishers, SSP
IBM Big Data Customers Beneficiaries
Long-Term High: For a publisher community struggling
Opportunity to effectively monetize content, the
Potential identification and optimization of audience-
centric inventory has the potential to
deliver substantial revenue opportunities
High Impact Use 1. Ad Inventory Yield Optimization
Cases 2. Price optimization
3. Ad Inventory forecasting
© 2012 IBM Corporation

15. 4. Solution: Channel Optimization
(Attribution Analysis)
Business Efficiency/Effectiveness: Enabling the
Benefit economical, value-oriented purchase of
advertising media; understanding value
of channels higher up in the funnel
Customer Intermediate: Attribution is primarily
Maturity Level driven by “last-click”; ability to harness
and analyze data across different touch
points in the funnel, across channels, is
lacking
Core Marketers (via Demand-Side Platforms),
Beneficiaries CRM providers, Digital Agencies/Trading
IBM Big Data Customers Desks
Long-Term High: Meaningful media-buying
Opportunity efficiencies are already accruing to
Potential sophisticated users; coordinated use of
channels and the targeted
messaging/offer will deepen value
High Impact 1. Media Mix Modeling
Use Cases 2. Conversion funnel analysis
3. Search Engine Optimization
© 2012 IBM Corporation

16. To What Extent is Your Company Realizing
Value From the Following Data Sources?
We (or our clients) are We (or our clients) are
realizing no value from realizing significant from
these data sources these data sources
Source: Winterberry Group survey © 2012 IBM Corporation

17. Big data challenges Netezza and Unica customers
ask for help with
• Regular data warehouses • Ordinary approaches to
are challenged with dealing marketing don’t enable
with big data marketers to scale
 Nearly 70% of data  Too much IT effort to design
warehouses experience database campaigns
performance-constrained  Cannot scale to the number of
issues monthly campaigns needed
 Too much IT cost and DBA  Cannot be agile with creating
effort to maintain ad hoc campaigns
performance
 Too difficult to make
 Many of these ‘large’ marketing relevant, i.e.
conventional data targeted messages to past and
warehouses are simply current behavior of each
holding pens. individual
© 2012 IBM Corporation

18. How Netezza and Unica help – on their own
IBM Netezza Appliance IBM Unica
• Purpose-built analytics Marketing Interaction Optimization
engine using integrated solution
database, server & • Scalable: Deliver 30x as
storage many marketing programs
• Scalable: Low total cost • Fast: Reduce prep time for
of ownership campaigns to 25 - 50%
• Speed: 10-100x faster • Empowering: Put marketers
than traditional systems in control & minimize IT
• Simplicity: Minimal needs
administration and tuning • Smart: Increase marketing
• Smart: High-performance relevancy and success
advanced analytics
© 2012 IBM Corporation

19. How Netezza and Unica help – together
Common pairing over the years: Unica Campaign + Netezza
Marketing interactions
• Are executed as defined by
1 marketers
2 3 2 • Are refined with self-learning
algorithms
• Can also be refined by
importing analytical output from
IBM Netezza and Business
Analytics solutions
Marketing data mart is key for Unica
1. Stores customer + marketing data,
2. Enables scalable performance because
Unica can have queries executed inside the
database to leverage database speed
19
© 2012 IBM Corporation

20. Customer example:
Large US department store retailer
• IBM Netezza benefits
– Campaign execution time
faster by 300%
– Complex campaigns
accelerated by 600%
– No longer dependent on
vendor help to manage
• IBM Unica benefits
– Able to execute 40x
times as many marketing
programs as before
– New marketing team
members can easily be
on-boarded and pick up
“Very little to do for optimization. I have seen existing marketing
nothing as easy as Netezza and Unica” programs
- Marketing IT Manager:
© 2012 IBM Corporation

21. Customer example:
Marketing Service Provider
“The IBM Netezza data warehouse appliance helps us deal with the volume and capture
click stream transactions at the lowest level and aggregate it into a single customer view.
Combined with IBM Unica® campaign management software, we can now help the
brands quickly understand customer preferences and communicate the relevant
messages in both online and offline campaigns.”
-Russ Pearlman, Chief Information and Technology Officer, Merkle
• Joint benefits at Merkle:
• Regularly received a 70 percent reduction in processing
time for complex marketing campaigns—decreasing
time from hours to minutes
• 25-90 percent revenue lift for one client through use of
new analytic models
• 50 percent decrease in end-to-end run time for
marketing campaign execution—from sample to test to
final version
© 2012 IBM Corporation

22. How Netezza and Unica help – together
New offering: Unica Interaction History (on Netezza) & Attribution Modeler
Cross-channel Interaction History Attribution Modeler
• Provides singular Leverages statistical method to give
database of marketing (partial) credit to “stimuli” based on:
audience interactions
• Combinations of promotions and
channels
their response data
•Provides structured
data model for cross- • Power law or polynomial
channel attribution and
distribution algorithms to
reporting
measure relationship
•Supports customer
interaction data via • Expectation-Maximization (E-M)
IBM EMM and non- algorithm to iteratively tune
IBM platforms model parameters
(future)
• Store Interaction • Enable complex statistical queries for
IBM Netezza Appliance History = “Big Data” attribution with high speed on “Big Data”
Benefit: With these capabilities, attribution is allocated more rationally than
traditional methods allow © 2012 IBM Corporation

23. Benefits of using Netezza and Unica together
• Faster identification of key opportunities in
customer data
• Be quick-to-market with ad hoc campaigns to
capture hot opportunities
• Be agile with experimenting and optimizing
campaigns
• Faster execution of marketing campaigns
• Ability to benefit from full, detailed customer
data in designing campaigns
• Less time spent on data management issues,
more time for marketing
© 2012 IBM Corporation

24. Typical business results reported by EMM users
More effective marketing: More efficient marketing:
Improved customer value, More campaigns with the same
loyalty & retention resources
5-15% increase is typical 2-5x increase is typical
Higher online marketing ROI Reduced cycle time for
15x-25x increase is typical marketing efforts
40%-80% reduction is typical
Higher campaign ROI Reduced marketing costs
15-30% increase is typical 20-40% reduction is typical
Increased response rates Lower customer acquisition
10-50% increase is typical costs
25%-75% reduction is typical
Increased order value Other business metrics
15-20% increase is typical revenue, profit, others vary by industry (assets under
management, ARPU, #products owned, etc.)
24 © 2012 IBM Corporation

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© 2012 IBM Corporation

26. Copyright and Trademarks
© IBM Corporation 2012. All Rights Reserved.
IBM, the IBM logo, ibm.com are trademarks or registered trademarks of
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Other product and service names might be trademarks of IBM or other companies. A
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© 2012 IBM Corporation