notableReviewed Tue Nov 03

Ctrip study finds shopping AI chat and conventional search often interleave

Yan and colleagues analyze anonymized Ctrip travel-platform activity from 31.1 million logged-in users and document adoption, chat-search sequencing and exploratory intent in the Wendao assistant.

Context

Yan and colleagues analyze anonymized Ctrip travel-platform activity from 31.1 million logged-in users and document adoption, chat-search sequencing and exploratory intent in the Wendao assistant.

What changed

An original longitudinally linked behavioral study of platform-embedded AI shopping interactions provides observed user, search, chat and booking patterns, including chat-search interleaving.

Why it matters

Shopping AI discovery can coexist with conventional keyword search during the same purchase journey; AI visibility measurement should track both channels and intent progression.

Visibility OS interpretation

Visibility OS interpretation: measure AI-assisted exploratory discovery, search interleaving and downstream product consideration separately. These descriptive associations are not evidence that AI chat causes sales or determines citation rankings.

What remains uncertain

Do these patterns replicate beyond Chinese travel commerce? Does AI assistant access causally shift consideration, conversion or conventional search behavior? How do different entry points affect usage?

Evidence claims

supports

In a cohort of 31,142,353 Ctrip users logged in during July 10–24, 2025, 1,904,368 (6.1%) had initiated at least one Wendao AI chat by July 10, 2025.

supports

Among Ctrip shopping journeys in the study containing both AI chat and conventional search, the most common sequence was interleaving, accounting for 53% of those journeys.

supports

Attraction-related questions represented 42% of observed Wendao AI chat requests in the Ctrip study.

supports

In the Ctrip cohort, Wendao adoption was 10.7% for users aged 50 or older and 4.6% for users under 24.