APAILGJun 17

Estimating the Effect of Timing on Coupon Effectiveness

arXiv:2606.30664
Originality Synthesis-oriented
AI Analysis

For marketers and businesses, it provides a cost-effective method to evaluate timing effects in coupon campaigns using natural experiments.

The paper proposes a causal inference framework to estimate the effect of coupon timing on effectiveness without requiring expensive real-time event-triggered systems, demonstrating its utility on an internal onboarding campaign and a public retention dataset.

The coupon incentive is one of the most common tools marketers use to court users to engage with a business at various stages of the customer life cycle. A variety of factors can affect the effectiveness of a coupon incentive on users, timing being one of them. We hypothesize that coupons can be more effective when delivered at critical times in the customer journey, right when a user is engaging with the platform. Verifying such a hypothesis would typically require real time event-triggered coupon distribution software that may be too expensive to implement. In this paper, we propose a framework in which we apply causal inference on "natural randomized control trial experiments" to measure the effectiveness of sending coupons at the right time to users without requiring a dedicated AB test. We demonstrate the usefulness of our framework in the case of a user onboarding coupon campaign held in our company and show how the results can lead to correct data-driven decisions for the business. Furthermore, in order to test the generalizability of our framework, and to make our research more reproducible, we apply our framework on a user retention campaign with a publicly available dataset.

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