IceBreaker for Conversational Agents: Breaking the First-Message Barrier with Personalized Starters

TL;DR

IceBreaker introduces a novel method for initiating conversations with personalized starters, effectively overcoming the first-message barrier in conversational agents and enhancing user engagement.

Contribution

The paper presents a new two-step approach for cold-start conversation initiation, combining resonance-aware interest distillation and interaction-oriented starter generation.

Findings

Online A/B tests show +0.184% increase in user active days.

Click-through rate improved by +9.425%.

IceBreaker has been deployed in production.

Abstract

Conversational agents, such as ChatGPT and Doubao, have become essential daily assistants for billions of users. To further enhance engagement, these systems are evolving from passive responders to proactive companions. However, existing efforts focus on activation within ongoing dialogues, while overlooking a key real-world bottleneck. In the conversation initiation stage, users may have a vague need but no explicit query intent, creating a first-message barrier where the conversation holds before it begins. To overcome this, we introduce Conversation Starter Generation: generating personalized starters to guide users into conversation. However, unlike in-conversation stages where immediate context guides the response, initiation must operate in a cold-start moment without explicit user intent. To pioneer in this direction, we present IceBreaker that frames human ice-breaking as a two-step handshake: (i) evoke resonance via Resonance-Aware Interest Distillation from session summaries to capture trigger interests, and (ii) stimulate interaction via Interaction-Oriented Starter Generation, optimized with personalized preference alignment and a self-reinforced loop to maximize engagement. Online A/B tests on one of the world's largest conversational agent products show that IceBreaker improves user active days by +0.184% and click-through rate by +9.425%, and has been deployed in production.