Eric Schwartz is a graduating PhD student, and as of July 2013, he will be an Assistant Professor of Marketing at the Stephen M. Ross School of Business, University of Michigan.
Eric is interested in how firms can best learn to manage their customer relationships through interactive marketing and digital media. He is a quantitative modeler and uses a range of techniques, including field experiments, Bayesian statistics, and dynamic programming. His dissertation work addresses the problems facing marketers as they decide how to adaptively allocate their resources to test the effectiveness of their outbound marketing, and maximize profit along the way. The work broadens this class of problems, so that marketers can now solve problems not addressable with prior methods. Nearly every outbound marketing activity (e.g., sending emails, serving display ads, customizing websites, recommending products) can be framed as adaptive experiments to “test and learn” on a continuous basis. But as these A/B/C and multivariate testing practices become more integrated into a firm’s day-to-day operations, it is more important than ever to ensure that testing is done in a profitable manner. It is no longer acceptable to merely “test and learn” with the hope of making greater profits in the future; today’s digital marketers must “earn while they learn.”
Eric received a B.A. in Mathematics and in Hispanic Studies from the College of Arts and Sciences of the University of Pennsylvania.