Awakening Dormant Users: Generative Recommendation with Counterfactual Functional Role Reasoning

TL;DR

This paper introduces RoleGen, a novel recommendation framework that models user intent evolution and simulates diverse conversion paths using counterfactual reasoning, significantly improving dormant user activation in e-commerce.

Contribution

RoleGen combines a functional role reasoner with a generative model, employing counterfactual inference to better predict user conversion trajectories and enhance recommendation effectiveness.

Findings

Achieved 6.2% increase in Recall@1

Realized 7.3% growth in online order volume

Validated effectiveness through offline and online experiments

Abstract

Awakening dormant users, who remain engaged but exhibit low conversion, is a pivotal driver for incremental GMV growth in large-scale e-commerce platforms. However, existing approaches often yield suboptimal results since they typically rely on single-step estimation of an item's intrinsic value (e.g., immediate click probability). This mechanism overlooks the instrumental effect of items, where specific interactions act as triggers to shape latent intent and drive subsequent decisions along a conversion trajectory. To bridge this gap, we propose RoleGen, a novel framework that synergizes a Conversion Trajectory Reasoner with a Generative Behavioral Backbone. Specifically, the LLM-based Reasoner explicitly models the context-dependent Functional Role of items to reconstruct intent evolution. It further employs counterfactual inference to simulate diverse conversion paths, effectively mitigating interest collapse. These reasoned candidate items are integrated into the generative backbone, which is optimized via a collaborative "Reasoning-Execution-Feedback-Reflection" closed-loop strategy to ensure grounded execution. Extensive offline experiments and online A/B testing on the Kuaishou e-commerce platform demonstrate that RoleGen achieves a 6.2% gain in Recall@1 and a 7.3% increase in online order volume, confirming its effectiveness in activating the dormant user base.