Research
AI Search & Hotel Tech Research
Data-driven studies on how AI models discover, rank, and recommend hotels. All research is open and independently published.
Completed Studies
ChatGPT 5.3 Halved Its Hotel Sources
March 5, 2026 cutover — URLs/answer 24 → 12
Hotel YouTube Channels — Activity Study 2026
Only 10.0% of hotels have YouTube; 43.7% are ghost accounts
ChatGPT Hotel Ads Are Live
Booking.com owns 43.5% of all ad slots
ChatGPT Hotel Index vs Live Web
83% of cited domains change between modes
How Dirty Is Google Maps Hotel Data?
17% of 179K listings fail quality checks
ChatGPT Hotel Data Sources
Google fell from 100% to 70.3% in 90 days
What Hotel Footers Reveal
Instagram in 40.8%, stale copyrights in 24%
Hotel llms.txt Adoption Study
Only 6.3% have a llms.txt file
Hotel robots.txt & AI Blocking Study
Only 3.3% block any AI crawler
What Hotels Are Actually Called
A naming study of 121,425 hotels
Hotel Schema.org Adoption Study
36.3% of hotels have no schema at all
How Consistent Are AI Hotel Rankings?
Only 50.5% position stability across reruns
Anatomy of a ChatGPT Hotel Search
12 systems, 7 providers, 424 A/B tests
Yelp in ChatGPT: Hotel Data Study
33% Yelp rate in US hotel queries
Google AI Mode: Where Do Hotel Clicks Go?
79% of clicks go to Google Business Profiles
Do French Hotels Blog?
49.3% have blogs, only 1 in 4 are active
In Progress
The Palace Bias
62% palace share in 5-star AI recommendations
Do AI Models Link Differently?
6 models, 2 providers compared
Hotel Page Speed Study
Core Web Vitals audit
Location & Language Bias
2 languages, US vs FR compared
GPT-5.1 to GPT-5.2: Winners & Losers
How model updates shift hotel rankings
How to Measure AI Hotel Traffic and Bookings
GA4 referrers, branded queries, booking-form prompts, ChatGPT Apps