| Abstract: |
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. |