通过自然实验分析时机对优惠券效果的影响，无需复杂系统即可优化投放策略。
Estimating the Effect of Timing on Coupon Effectiveness
- 利用自然随机对照实验进行因果推断，评估优惠券发放时机的影响。
- 在用户入门和留存场景中验证框架有效性，提升决策数据化水平。
- 方法可复现，适用于多种营销场景，适合运营与数据团队使用。
优惠券是营销中常用的激励工具，可用于客户生命周期的多个阶段。影响其效果的因素众多，其中时机至关重要。我们假设在用户活跃时精准发放优惠券能提升效果。传统验证需实时触发系统，成本较高。本文提出一种基于因果推断的框架，利用‘自然随机对照实验’来评估时机对优惠券效果的影响，无需专用A/B测试系统。我们在公司内部用户入门优惠券活动中验证该框架，并展示其如何支持数据驱动的业务决策。为进一步验证通用性与可复现性，我们还将该框架应用于公开数据集上的用户留存活动。
原文摘要 · Abstract (English)
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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