Speaker: Pantelis Loupos (UC Davis Graduate School of Management)

Title: Starting Cold: The Power of Social Networks in Predicting Non-Contractual Customer Behavior

Abstract: The last decade has seen a rapid emergence of non-contractual networked services. The standard approach in predicting future customer behavior in those services involves collecting data on a user's past purchase behavior, and building statistical models to extrapolate a user's actions into the future. However, this method fails in the case of newly acquired customers where you have little or no transactional data. In this work, we study the extent to which knowledge of a customer's social network can solve this “cold-start” problem and predict the following aspects of customer behavior: (1) activity, (2) transaction levels and (3) membership to the group of most frequent customers. We conduct a dynamic analysis on approximately one million users from the most popular peer-to-peer payment application, Venmo. Our models produce high quality forecasts and demonstrate that social networks lead to a significant boost in predictive performance primarily during the first month of a customer's lifetime. Finally, we characterize significant structural network differences between the top 10% and bottom 90% of most frequent customers immediately after joining the service.

Roundtable Discussion will start immediately after this talk. The topics include: Data science needs and issues in Business Schools. For example, we will discuss:

• How the students in business school/school of management are trained in data science/machine learning now? Are they also taking some of the courses offered by our 4 departments (CS/ECE/Math/Stat)?
• What opportunities (problems, projects) in data science/machine learning could the business school provide us in CS/ECE/Math/Stat faculty, postdocs, and graduate students?
• How about potential collaborations between your school and our 4 departments?

So, please attend both the seminar and the roundtable discussion!