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:
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.
Tuesday, February 23, 20214:30-5:30 p.m. ETVirtual Program
All participants must register for this event. A Zoom login link will be provided before the virtual program in a confirmation email.
Register by Monday, February 22Questions? Contact ENAiBLE
Andrew Li is an Assistant Professor of Operations Research at CMU’s Tepper School of Business. His research develops new methods in optimization and statistics, for problems in retail and personalized medicine. He also teaches and consults frequently in both spaces.Andrew holds a B.S. in Operations Research (Columbia) and a Ph.D. in Operations Research (MIT).