Working Papers

Design and Evaluation of Personalized Free Trials

Hema Yoganarasimhan

Abhishek Pani

Adobe Systems Inc.

Ebrahim Barzegary

University of Washington

Oct 12, 2020

Develops a multi-stage machine-learning framework for personalized targeting policy design and evaluation analyzing data from a field experiment by a leading SaaS firm where new users were randomly assigned to 7, 14, or 30 days of free trial. Uses an Inverse Propensity Score (IPS) reward estimator to evaluate the reward or gain from each targeting policy.

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