嵌入电商平台的AI助手更受中老年女性和高活跃用户欢迎，用于探索性购物发现。
Shopping with a Platform AI Assistant: Who Adopts, When in the Journey, and What For
- 基于大模型的AI助手在旅行平台中被广泛用于探索性查询，而非简单搜索替代。
- 42%的聊天请求用于景点查询，且使用时机与购买品类密切相关。
- 适合希望提升购物体验的电商用户，尤其关注发现新商品的消费者。
本文基于携程平台3100万用户的使用数据，研究了其集成的LLM驱动AI助手Wendao的采用与使用行为。研究发现：第一，采纳率最高的是年龄较大、女性及高活跃用户，与通用AI工具的年轻男性主导特征相反；第二，AI聊天功能出现在购买旅程的早期阶段，与传统搜索并行，多数用户在搜索与聊天间来回切换；第三，用户主要用该助手处理难以用关键词表达的探索性任务，如景点查询占聊天请求的42%，且聊天意图随搜索时间与后续购买品类系统性变化。结果表明，嵌入式购物AI更像探索性发现的补充界面，而非传统搜索的替代品。
原文摘要 · Abstract (English)
This paper provides some of the first large-scale descriptive evidence on how consumers adopt and use platform-embedded shopping AI in e-commerce. Using data on 31 million users of Ctrip, China's largest online travel platform, we study "Wendao," an LLM-based AI assistant integrated into the platform. We document three empirical regularities. First, adoption is highest among older consumers, female users, and highly engaged existing users, reversing the younger, male-dominated profile commonly documented for general-purpose AI tools. Second, AI chat appears in the same broad phase of the purchase journey as traditional search and well before order placement; among journeys containing both chat and search, the most common pattern is interleaving, with users moving back and forth between the two modalities. Third, consumers disproportionately use the assistant for exploratory, hard-to-keyword tasks: attraction queries account for 42% of observed chat requests, and chat intent varies systematically with both the timing of chat relative to search and the category of products later purchased within the same journey. These findings suggest that embedded shopping AI functions less as a substitute for conventional search than as a complementary interface for exploratory product discovery in e-commerce.
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