Education: PhD University Of Pennsylvania 2013; BA University Of Pennsylvania 2008
Professor Eric Schwartz's expertise focuses on predicting customer behavior, understanding its drivers, and examining how firms actively manage their customer relationships through interactive marketing. His research in customer analytics stretches managerial applications, including online display advertising, email marketing, video consumption, and word-of-mouth. The quantitative methods he uses are primarily Bayesian statistics, machine learning, dynamic programming, and field experiments. His current projects aim to optimize firms A/B testing and adaptive marketing experiments using a multi-armed bandit framework. As marketers expand their ability to run tests of outbound marketing activity (e.g., sending emails/direct mail, serving display ads, customizing websites), this work guides marketers to be continuously earning while learning.
Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments. (2016) Eric M. Schwartz, Eric T. Bradlow, and Peter S. Fader. Marketing Science. forthcoming.
Model Selection Using Database Characteristics: Developing a Classification Tree for Longitudinal Incidence Data. (2014) Eric M. Schwartz, Eric T. Bradlow, and Peter S. Fader. Marketing Science. 33:2, 188-205.
What Drives Immediate and Ongoing Word of Mouth? (2011) Jonah Berger, and Eric M. Schwartz. Journal of Marketing Research. 48:5, 869-880.