DMA: Data and Marketing Association
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Art of Targeting & Personalization


Proper personalization is possible only when data management, analytics, content management, and content delivery techniques work together seamlessly. Too often, marketers rely on software solutions only using SKU level data that are not suitable for customized messaging. Personalization must be about the person, and data players should transform all types of data - old and new - to describe the target first, instead of just reacting to hotline data on a product or channel level. The ultimate goal should be personalizing every message for everyone through every channel, instead of reacting to real-time data only for a fraction of the audience.

Sponsored by the DMA Analytics Community. DMA members who sign-up for this webinar will automatically be included in this Community to stay informed of future calls. Participate as much or as little as your time allows. Cancel at any time.

Stephen H. Yu

Associate Principal, Analytics & Insights Practice Lead

Stephen H. Yu is a world-class database marketer with proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from over 28 years of experience in best practices of database marketing.

Currently he is Associate Principal, Analytics & Insights Practice Lead for eClerx. He served as VP, Data Strategy & Analytics at Infogroup, and previously he was the founding CTO of I-Behavior Inc.

What You'll Learn

  • checkmark Importance of personalization in the multi-channel environment
  • checkmark How to transform product- or channel-centric data into descriptors of target individuals (and why such transformation is necessary in the age of Big Data)
  • checkmark How to overcome limitations of hotline data and traditional segmentation, which is only one-dimensional
  • checkmark How to create data and analytics road map for more holistic personalization
  • checkmark How to define targets for models
  • checkmark Importance of defining comparison universe as well as the target universe
  • checkmark Multiple targets
  • checkmark Multi-step approach
  • checkmark Inversely related targets
  • checkmark Mixing multiple model scores
  • checkmark How to develop multi-dimensional personas for everyone in the target universe
  • checkmark How to match marketing messages for each individual based on hotline data and personas
  • checkmark Other non-data or analytics elements to consider for automation of proven processes.

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