Please join us for a
Lehigh Marketing Speaker Series Event

Tuesday, November 30, 2021

Presenter:  Hema Yoganarasimhan, Foster School of Business, University of Washington
Topic:  "Design and Evaluation of Optimal Free Trials"

Time:  4:30 PM to 6:30 PM
Location:  Via Zoom

https://lehigh.zoom.us/j/96992398210

Abstract
Free trial promotions are a commonly used customer acquisition strategy in the Software as a Service (SaaS) industry. We use data from a large-scale field experiment to study the effect of trial length on customer-level outcomes. We find that the 7-days trial is the best average treatment that maximizes customer acquisition, retention, and profitability. In terms of mechanism, we rule out the demand cannibalization theory, find support for the consumer learning hypothesis, and show that long stretches of inactivity at the end of the trial are associated with lower conversions. We then develop a framework for personalized targeting policy design and evaluation. We first learn a lasso model of outcomes as a function of users’ pre-treatment variables and treatment. Next, we use individual-level predictions of the outcome to assign the optimal treatment to each user. We then evaluate the personalized policy using the inverse propensity score reward estimator. We find that a personalization based on lasso leads to 6.8% improvement in subscription compared to a uniform 30-days for all policy. It also performs well on long-term customer retention and revenues in our setting. Segmentation analysis suggests that skilled and experienced users are more likely to benefit from longer trials. Finally, we show that personalized policies do not always outperform uniform policies, and one should be careful when designing and evaluating personalized policies. In our setting, personalized policies based on other outcomes and heterogeneous-treatment effects, estimators (e.g., causal forests, random forests) perform worse than a simple 7-days for all policy.

Bio
Dr. Hema Yoganarasimhan is a Professor of Marketing at the Foster School of Business, University of Washington. She also holds affiliate appointments in Computer Science and Engineering, Department of Economics, and Center for Statistics in the Social Sciences. Hema serves as a co-editor at Quantitative Marketing and Economics and as an Associate Editor at Marketing Science and Management Science.

She is recognized as one of the leading experts in quantitative marketing. Hema’s research brings together large-scale marketing data, economic theory, and econometric and machine learning tools to help firms optimize and automate their marketing decisions.

For more information and to view her CV, visit her website.