How AI Recommends Hotels
Original research into AI search behavior. We run thousands of queries, analyze millions of citations, and publish what we find — so hotels can understand the new landscape.
AI Hotel Landscape 2026
1.2M+ citations across ChatGPT, Gemini, Perplexity & Grok
The definitive analysis of how AI assistants recommend hotels. Which sources do they trust? Which hotels win visibility?
Completed Studies
Google AI Mode Study
How does AI Mode route hotel traffic?
4,000 queries, 84K+ references, 1,146 unique hotels. Intermediaries get 47% of references, suppliers 21%.
Hotel Blog Study
49% have a blog — only 1 in 4 is active
Analysis of 15,155 French hotels reveals an untapped content opportunity. Hotel blogs are becoming a knowledge layer for the AI era.
In Progress
Anatomy of ChatGPT Hotel Search
What actually happens when someone asks ChatGPT for a hotel
Technical teardown of the 12 systems behind ChatGPT hotel recommendations: entity linking, fan-out engines, provider ecosystem, RRF fusion, and the Google lawsuit threatening it all.
ChatGPT Consistency Study
How consistent are hotel recommendations?
Replicating SparkToro's AI consistency research for hotel queries. Testing recommendation stability across 4,000 runs.
When Web Search Is Triggered
What makes AI models search the web for hotel queries?
Investigating which hotel queries trigger real-time web search in ChatGPT, Gemini, and Perplexity — and which get answered from training data alone.
Yelp in ChatGPT
ChatGPT quietly started pulling hotel data from Yelp — then stopped
On Jan 22, Yelp appeared as a new data provider in ChatGPT hotel results, peaking at 2,235 entities and 31.6% share. By Jan 27 it dropped below 4%. Was it a test? Is it live in other countries? We're investigating.
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