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© 2013 Acxiom Corporation. All Rights Reserved.
The Evolution of CRM in the Era of Big Data & Digital Technology
Making Better Connections
to Deliver Better Results:
Presentation to
April 18, 2013

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Who Do We Work With?
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Consumers
Brands
Media
Partners
What Are We Trying to Connect?
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Agenda
 Changing Landscaping
 Resulting Paradigm Shift
 Challenges for Direct Marketing
 How You Might Address It
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What’s Changing ?
Email Usage
DM Opens
Telemarketing
Conversion Rates
Sourcess: David Kay and Mark van Harmelen, (2012)
D
E
C
I
S
I
O
N
I
N
G
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globalastrologyblog.blogspo.com (2012)

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Our data lacks the detail
needed to drive effective
marketing solutions
What data will help drive
better business decisions.
Where to get it? How to
use it?
Our data stored in
different locations in
different format
With different usage
permissions
Not every record has a
prefect ‘match’
Data Chaos Analysis Chaos Decision Chaos
 How do you translate
results into actions
 In a timely manner
 In a way that makes a
difference

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Trouble Is…
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1
TOO MUCH
DATA
2
NOT ENOUGH
INSIGHTS
3
TOUGH TO
CONNECT WITH
THE RIGHT
CONSUMERS

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Why BAU Is So Hard?
 Many companies prefer all components of its
database to remain behind firewalls
- Good Luck with that
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So What’s Shifting ?
> Get More Data  Use the Right Data
> Mass Media  Addressable Media
> Advertising $$$  CRM $$$
> Push Messaging  Triggered Messaging
---------- CRM Role within Organizations --------
> Attitudinal Data  Behavioral Data
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The CEO’s
Challenge What set of
corporate actions
will best increase
shareholder value?
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The CMO’s
Challenge
How can I optimize
my marketing plans
this year so they
deliver higher sales at
a terrific ROI?
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The CRM Manager’s Challenge
How can we unlock the
value within our
customer database to
increase share of wallet
and market share?
My Share
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3 keys to growing your business via CRM :
(1) get the most from current customers
- up-selling and cross-selling
(2) protect your existing share of market
- avoid defection
(3) profitably cultivate new customers
- focusing on consumers with high LTV
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So how you get there?
Robust Understanding Of Current Customers / Segments
Mapping Customers’ Path to Purchase / Brand Touchpoints
Identifying & Isolating Factors Related to Purchase
Ideating Customer Recognition & Decisioning Scenarios
Specifying the Data, IT & Business Requirements to Achieve the Vision
Creating a Roadmap to Get There
Developing a Business Case for the Investment
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Better Targeting
More Relevant Messaging
Better Channel Selection
Improved Consumer Experience
Better Response Rates
Media Efficiencies
Higher Customer Satisfaction
Higher ROMI
Expected Outcomes
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IRI Panel
Crossmark
Store Sales
Volume Metrics
MRI
SpendingMedia
Cross-category
Purchases
Client
Cross-category
Brand propensities Hoovers
Market Size
Forrester
Big Research
Omniture
Cart Activity
Site Activities
Com Score
Pages Visited
Compete
Time Spent
Social Media
Collective Intellect
Radian 6 Sentiment
tracx
Network Connectivity
KloutInfluence
HH Activity
Technographics
Demographics
Psychographics
Econometrics
Lifestyle Interest
INFOBASE
Data Providing the Best Speed to Value
Merge – Segment – Score
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What You Can Do With It
Online
Habits
E-Commerce
Activity
Trad.
Media
Habits
Sales
Data
Social
Media
DM
Email
Response
Demos
&
HH Info
Rewards
Program
Activity
Audience Segmentation
B/O Product Interests
Channel Utilization
B/O Media Habits
CRM Messaging for NBO
B/O Website Behaviors
Offer Management
B/O Estimated LTV / Defection Risk
Dynamic Site Experiences
B/O Customer Recognition
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What Next?
Take what you know
about registered
consumers and use
that information to
interact with people
that are unknown
Registered
Consumers
Unknown Consumers
High Value
Look-Alikes
Previously
Unaddressed
Segments
Competitive
Conquests
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Analytics Platform
Consistent Recognition
How You Manage & Deliver It
Inventory Partners
& Ad Serving
Site Analytics
AnonymousKnown
Anonymize
Segments & Models
Onboard
Associate
Manage
Analyze
Segment
Distribute
Receive/Cleanse
Recognize
Manage
Analyze
Segment
Fulfill
Content Delivery
Platforms
Safe Haven
PC Data Onboarding
Premium Pub Partners
Online/Offline
Enhanced IB,
Predictive
Models,
Triggers
Data/Models
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Real-time Decisioning
Outbound Channels
Inbound / Interactive Channels
“Trigger”
Targeting
“Push”
Targeting
Campaign
Management
Marketing
Databases
Content
Middleware,
Business Rules
Analysis,
Planning &
Budgeting
Customer
History
> Client Data
> Third-Party Data
> ETL Processes
> Grouping Rules
> Triggers
Campaign Execution
Customer
PerceptionProduct
Pricing
Availability
Operational
History
Content
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How You Deliver It
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https://romeo.blkbx.com

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Analytics 2.0
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1
Attribution
2
Optimization
3
Allocation
Analytics Engine
Source: Market Share (2013)
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“VARS
GA
Neural Nets .. Oh my”

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MEDIA MIX OPTIMIZATION
Response curves
14.60
14.80
15.00
15.20
15.40
15.60
15.80
16.00
$0
$5
$10
$15
$20
$25
$30
$34
$40
$45
$50
$55
$60
$65
$70
$75
$80
$85
$90
$95
$100
$105
$110
$115
$120
$125
$130
$135
$140
$145
$150
$155
$160
$165
$170
$175
$180
$185
$190
$195
$200
$205
TotalProductUnits
Millions
Media Investment($M)
ResponseCurves
Direct Mail
TV
OOH
E-mail
Display
Print
Radio
Search
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Points of Entry
Real-time Dynamic Marketing Engine
Automated File
Generation
Automatically trigger
marketing files, in real-
time, when changes
occur.
Multi-Channel Execution
Coordinated, trigger
communications via Web, ad
targeting, phone, direct
mail, e-mail, SMS or other
retail CRM system
Delta Monitoring
Best-in-class tools to
continuously monitor your
data to detect changes based
on timing, events,
transactions and or thresholds
Ongoing Optimization
Continuous marketing mix
optimization to improve
targeting, offer and channel
performance.
Real-time Consolidation
Leading edge capabilities
to consolidate data
streams from numerous
sources in a real-time
environment
Prospects LeadsSite Visitors Customers
Behavior Monitoring
Lead
Sources
Call
Centers
Sales
Database
Websites Preference
Centers
Social Loyalty Customer
Care Interactive
Aspire Learn Shop
Own /
Service
Experience Re-Up-Cross-SellBuy
E.I.M. Dynamic Life-Cycle Marketing
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Thank You
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