Shopping with a Platform AI Assistant: Who Adopts, When in the Journey, and What For

TL;DR

This study analyzes how consumers adopt and utilize an AI shopping assistant embedded in a large e-commerce platform, revealing adoption patterns, usage timing, and task types, highlighting its role in exploratory product discovery.

Contribution

It provides the first large-scale descriptive evidence on consumer adoption, usage patterns, and task types for embedded shopping AI in e-commerce, based on data from 31 million users.

Findings

Adoption is higher among older, female, and highly engaged users.

AI chat occurs mainly during the exploration phase, before order placement.

Consumers use AI for exploratory, hard-to-keyword tasks like attraction queries.

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.