POSGen: Personalized Opening Sentence Generation for Online Insurance Sales

TL;DR

POSGen is a novel AI-based system that generates personalized opening sentences for online insurance chatbots, improving customer engagement and significantly increasing insurance sales.

Contribution

It introduces a user embedding transfer and topic ordering mechanism for personalized sentence generation in online insurance sales chatbots.

Findings

Achieved 2.33x increase in total insurance premiums during deployment.

Effectively recommends and orders conversation topics based on user behavior.

Demonstrates practical effectiveness in a real-world online insurance platform.

Abstract

The insurance industry is shifting their sales mode from offline to online, in expectation to reach massive potential customers in the digitization era. Due to the complexity and the nature of insurance products, a cost-effective online sales solution is to exploit chatbot AI to raise customers' attention and pass those with interests to human agents for further sales. For high response and conversion rates of customers, it is crucial for the chatbot to initiate a conversation with personalized opening sentences, which are generated with user-specific topic selection and ordering. Such personalized opening sentence generation is challenging because (i) there are limited historical samples for conversation topic recommendation in online insurance sales and (ii) existing text generation schemes often fail to support customized topic ordering based on user preferences. We design POSGen, a personalized opening sentence generation scheme dedicated for online insurance sales. It transfers user embeddings learned from auxiliary online user behaviours to enhance conversation topic recommendation, and exploits a context management unit to arrange the recommended topics in user-specific ordering for opening sentence generation. POSGen is deployed on a real-world online insurance platform. It achieves 2.33x total insurance premium improvement through a two-month global test.