This document discusses how marketers can use customer data and analytics to better target and market to consumers. It emphasizes connecting customer insights across both digital and traditional data to optimize marketing efforts. Some key points discussed include using digital data to refine customer understanding, investing marketing proportional to existing customer value, and connecting customer insights with partner data for more contextual targeting. The document provides several examples of how data and analytics can inform marketing strategies and campaigns, such as identifying lookalike audiences, assessing marketing impact, and optimizing pricing and promotions. It also discusses how data management platforms and analytical models can power integrated online and offline marketing programs by leveraging behavioral, transactional, and modeled consumer insights.

1. The Data Connection:
Marketing to the Empowered
Consumer
Dr. Phil Mui
Chief Product Officer,
Acxiom

2. Must Have

3. Essential Requirements
Refine insight about
customers across all
relevant data points…
multiple signals
Invest proportionally to
existing customer value
then find lookalikes
Use digital data to
optimize CRM, traditional
and all media
Connect your customer
insight with your partners’
contextual insight
Are you doing for
customers or to? Value is
not just short-term results
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4. For Example

5. 5

6. Relevance
and
Precision

7. Cookie-Based Lookalikes Addressable Audience
PII-Based Extended Audience
Known Audience
1M 10M 100M 1B
Scale
Relevance and Precision (performance)
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8. How?

9. Making the Connections
ONLINE
OFFLINE
UNIQUE
AbiliTec
INSIGHTS
Connections emerge and remain consumer-friendly
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10. Holistic Marketing View
MARKETING SAFE HAVEN ONLINE MARKETING
DATABASE SYSTEMS ENVIRONMENTS ECOSYSTEM
Personally Identifiable Where PII and segments are Anonymous and Personally
Information (PII): integrated but not shared Identifiable Information (PII):
Customer and Prospect between partners Customer and Prospect
segmentation data behaviors and insights
Analytics / Modeling and Consumer Propensity Scoring
Third-Party Consumer Insight Data
Focus on Data Quality and Superior Customer Recognition
Consistent Focus on Privacy and Compliance
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11. Making It Real
MARKETING CUSTOMER PRICING
PROFITABILITY
What is the optimal Which customers hold the How do I better defend
marketing spend / mix? highest future value and how do my pricing?
I capture it?
How do I better assess How can I become less
marketing’s impact? Which prospects act / look / reliant on discounts to
think like my best customers? drive activity?
How should I reach them?
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12. Making It Real
DATA MANAGEMENT PLATFORMS BEHIND THE SCENES
• Integrating disparate data sources • Real-time data integrations
• Identify audience behaviors keep audience feedback
• Act faster: Manage online audience updated
• Leverage 1st-party offline data
elements and segmentation
including purchase history
• Use media and other content
interactions to inform follow-
up impression serving
• Integrate behavioral and
browsing data sources
• Inform content management
systems to target dynamic
offers
• Fast and easy tag
management tools
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13. Making It Real
PARTNER MARKETING BEHIND THE SCENES
• Engage the right audience with online display • Leverage your best customer
• Identify your best prospects models and you can target ad
• Target with specific offers in preferred channels units with precision
• Activate offline consumer
insights and segments, online
• Collaboratively target audiences
with publisher partners in
interactive channels – online,
mobile, and TV
• Invest in display advertising
only when your audience is
also tagged for later retargeting
through other properties in the
publisher ecosystem
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14. Making It Real
3rd PARTY DATA & ANALYTICAL MODELS BEHIND THE SCENES
• Integrate online / offline targeting • Effectively reach audiences of
• Offer relevant products / brands based on affinity interest and develop
• Better predict in-market timing / best channel coordinated online and offline
marketing programs
• Identify high-profile events
through life-stage elements
and in-market timing models
• Use modeled insights to
determine specific audiences
channel preferences and
usage to optimize spend
• Leverage analytical models to
determine audience brand
affinity and other propensities
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15. Predictive Scoring
Modeled Intelligence across Five Dimensions
Retail Product Retail
Credit
Categories Healthcare Communications
Communications
Automotive Credit Cards
Auto Purchase
In-Market Timing Brand Affinity
Insurance
Savings and Investment
Electronics Traditional
Vehicle Type Channels Emerging
Channels
Travel
Retail Product Propensity Purchase
Channel Preference
(ownership and usage)
Telecomm
Communication Shopping
Healthcare Savings and Mobile
Investments Attitudes and
Behaviors Social
Technology Fashion Conscious
Economic Sensitivity Price Sensitivity Spend Levels
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16. What’s Next?

17. Thank You. Questions?
@philmui Discover more at:
www.acxiom.com/dma12