Business Policy Experiments using Fractional Factorial Designs: Consumer Retention on DoorDash.
CoRR(2023)
摘要
This paper investigates an approach to both speed up business decision-making
and lower the cost of learning through experimentation by factorizing business
policies and employing fractional factorial experimental designs for their
evaluation. We illustrate how this method integrates with advances in the
estimation of heterogeneous treatment effects, elaborating on its advantages
and foundational assumptions. We empirically demonstrate the implementation and
benefits of our approach and assess its validity in evaluating consumer
promotion policies at DoorDash, which is one of the largest delivery platforms
in the US. Our approach discovers a policy with 5% incremental profit at 67%
lower implementation cost.
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