This document discusses Experian's approach to harnessing big data to drive organizational understanding of customers and more effective marketing. It introduces their customer intelligence perspective and insight platform, which includes three hubs: an execution hub, intelligence hub, and integration hub. The presentation then covers Experian's views on data integration and customer intelligence, examining historical, recent, and future approaches to leverage all available customer data for analysis and targeted campaigns.
2. WHAT WE HEARD
1.View on customer data integration
2.View on extracting intelligence from the
customer hub
3.View on delivering measurable lift with
this intelligence
4.Reflect on what has and hasn’t worked
in client environments
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9. CUSTOMER ENGAGEMENT FRAMEWORK
STORE MODELING CAMPAIGN DESIGN
DIRECT MAIL
TV
SYNDICATED
CALL CENTER
INTEGRATED
EMAIL PROFILES CONSUMER OPTIMIZED
INSIGHTS OFFERS
WEBSITES
BEHAVIORAL ANALYSIS TARGETING
SEARCH
SOCIAL MEDIA
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10. INSIGHT PLATFORM - THREE HUBS
EXECUTION
HUB
INTELLIGENCE COLUMNAR
HUB
INTEGRATION HADOOP
HUB
DATA RDBMS
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11. Looking to future of multi-channel identity resolution.
“It’s all ball bearings these days…”
DATA INTEGRATION
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12. DATA INTEGRATION OVERVIEW
Historical
• Mainframe based
• Referential based terrestrial linkage
Recent Past / Today
• SOA based
• Mixed mainframe / database based
• Cross media linkage (email, web,
terrestrial, etc.)
What’s Next
• SOA / No-SQL Based
• Cross channel referential repositories
(social, mobile, web, traditional, etc.)
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13. Data is only as valuable as what it enables you to do
“Pork Bellies and the GI Joe with Kung Fu Grip…”
CUSTOMER INTELLIGENCE
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14. CUSTOMER INTELLIGENCE OVERVIEW
Historical
• IT Centric
• EDW Type of analysis
• Heavy lifting campaign management
• Light analytics
Recent Past / Today
• OLAP and Cube Based BI
• Trigger based + Batch CM
• Heavy analytical pull
• Highly disparate communications
What’s Next
• MAD (Magnetic, Agile, Deep) Data
concepts **
• Consistent customer definitions
** MAD Skills: New Analysis Practices for Big Data, Joseph Hellerstien, UC Berkely 14