Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice

Tanner Fiez, houssam nassif, Yu-Cheng Chen, Sergio Gamez, Lalit K Jain

Keywords: experimentation, multi-armed bandits, A/B testing, online learning, counterfactual inference

TL;DR: We developed an adaptive experimental design framework for counterfactual inference and tested it in a commercial environment.

Abstract: Adaptive experimental design (AED) methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/N testing methods. However, the behavior and guarantees of such methods are not well-understood beyond idealized stationary settings. This paper shares lessons learned regarding the challenges of naively using AED systems in industrial settings where non-stationarity is prevalent, while also providing perspectives on the proper objectives and system specifications in such settings. We developed an AED framework for counterfactual inference based on these experiences, and tested it in a commercial environment.

Track: User Modeling and Recommendation

Submission Guidelines Scope: Yes

Submission Guidelines Blind: Yes

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Submission Guidelines Authorship: Yes

Student Author: No

Submission Number: 1172