Doubly Adaptive Cascading Bandits with User Abandonment

Knowing When to Hold Back: Smarter Messaging Keeps Customers Marketers often assume that reaching customers more often produces better results. A new study suggests the opposite can be true. Junyu Cao, Wei Sun, and Zuo-Jun (Max) Shen examine how digital platforms can boost engagement without driving customers away through marketing fatigue. They develop a family of “doubly adaptive” learning algorithms that learn across users while also adjusting the messages sent to each individual in real time, weighing relevant content against the risk that one poorly targeted message prompts a customer to unsubscribe or delete an app. The authors prove their methods come close to the best possible performance and test them on real e-commerce data spanning tens of millions of interactions, where the approach retained far more users than standard benchmarks. The lesson is that sometimes sending fewer, better-timed messages is what keeps customers around.