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.” While interacting with students and managers, Professor Schwartz works to illustrate how today's marketers bridge the gap between technical skills and data-driven decision making. He earned his Ph.D. in Marketing from the Wharton School and a B.A. in Mathematics and Hispanic Studies, all from the University of Pennsylvania.
The Flint, Mich., water crisis began in 2014 when the Flint River became the drinking water source for the city of Flint, Michigan. Due to insufficient water treatment, 100,000+ residents were potentially exposed to high levels of lead in the drinking water. As of early 2017, the water quality had returned to acceptable levels, but residents were instructed to continue to use bottled or filtered water until all the lead pipes have been replaced, which is expected to be completed no sooner than 2019.
Questions abound: Who is most at risk? Where are the harmful sources of lead? Where should resources be allocated?
In this session, attendees will hear the fascinating story of how two University of Michigan professors, sing big-data tools, answered these questions and help inform the response to this public health crisis.