用智能消息提升用户留存，减少退订，提前促发报税行为
Behavioural Effects of Agentic Messaging: A Case Study on a Financial Service Application
- 用自主决策的智能系统替代规则化推送，动态调整沟通策略
- 实验显示退订率降低21%，报税提前量显著增加
- 适合关注用户留存与行为激励的金融类应用开发者
营销与产品个性化是信息检索技术在多个商业领域的重要应用。近年来，基于代理（agentic）的方法逐渐兴起。本研究在2025年全国报税期期间，对一款金融服务应用的客户沟通系统开展为期两个月的随机对照试验，评估代理式个性化消息对用户行为与留存的影响。对比传统规则驱动的业务常态（BAU）系统，重点考察退订行为与转化时间两个核心指标。实证结果表明，代理主导的消息系统使退订事件减少21%（±0.01），并显著提升了临近全国截止日期前几周的提前报税行为。研究证明，具备用户级自适应决策能力的系统可在增强参与强度的同时，有效改善长期留存表现。
原文摘要 · Abstract (English)
Marketing and product personalisation provide a prominent and visible use-case for the application of Information Retrieval methods across several business domains. Recently, agentic approaches to these problems have been gaining traction. This work evaluates the behavioural and retention effects of agentic personalisation on a financial service application's customer communication system during a 2025 national tax filing period. Through a two month-long randomised controlled trial, we compare an agentic messaging approach against a business-as-usual (BAU) rule-based campaign system, focusing on two primary outcomes: unsubscribe behaviour and conversion timing. Empirical results show that agent-led messaging reduced unsubscribe events by 21\% ($\pm 0.01$) relative to BAU and increased early filing behaviour in the weeks preceding the national deadline. These findings demonstrate how adaptive, user-level decision-making systems can modulate engagement intensity whilst improving long-term retention indicators.
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