With ANDREW LI, Assistant Professor of Operations Research

Customer personalization should in principle be straightforward -- collect data, build a predictive model, predict customer preferences, done. Unfortunately, retailers often find the reality to be messier: 

• How do you stitch together multiple disparate sources of data on your customers?
• How do you do this when the data you have on an individual customer is tiny?
• How do you avoid the endless cycle of re-collecting data and re-building models?

Andrew will describe a new paradigm for organizing and learning from the exact kinds of data retailers collect, and discuss success cases from e-commerce and content personalization.

This talk is aimed at a non-technical, non-academic audience.

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ENAiBLE: A CMU Retail & Services Collaborative —  We bring the world-class expertise of CMU faculty into collaborative conversations with industry professionals with roles in management, R&D, and operations, from major retailers and service providers across the US. The result is a vibrant community that can clearly articulate today’s challenges and develop unique solutions that work across the technical, managerial, operational, and consumer dimensions to deliver a successful market offering.