AI Hotel Landscape
How leading AI assistants recommend hotels — 616 prompts across 56 destinations, refreshed every Monday.
+ 44 more
The 616 prompts we ask ChatGPT every week
56 destinations × 11 templates. Each prompt has structured dimensions: city, country, region, persona (couples / families / solo / business), budget (luxury / mid / budget), and location zoom (wide city vs neighborhood vs landmark). Control prompts are unmodified baselines.
Every destination below gets the same 11 question types — just with the city name swapped in. That's how 56 destinations × 11 templates = 616 prompts per platform per week.
- luxury hotels in <city>
- family friendly hotels in <city>
- hotels in <city> with rooftop pool
- hotels near <neighborhood>, <city>
- boutique hotels in <neighborhood>, <city>
- best hotels in <city> for solo travelers
- best hotels in <city>
- affordable hotels in <city> under $200
- best hotels in <city> for couples
- best hotels in <city> for business travelers
- best hotels in <neighborhood>, <city>
- hotels near <city> National Park
africa4 destinations · 44 prompts
americas14 destinations · 154 prompts
Each destination is asked the 11 prompt patterns above (11 prompts × 14 cities = 154 prompts in this region).
asia16 destinations · 176 prompts
europe17 destinations · 187 prompts
oceania5 destinations · 55 prompts
Each destination is asked the 11 prompt patterns above (11 prompts × 5 cities = 55 prompts in this region).
Named hotels in China — ChatGPT
ChatGPT's top picks specifically in China. Switch country at the top to filter, or clear to see worldwide.
Most-mentioned hotel by ChatGPT this week.
When ChatGPT hands out a hotel link, where does it go?Worldwide
Every URL the AI returned for a named hotel, classified into direct (the hotel's own site), OTA (Booking / Expedia / …), chain page (marriott.com / hilton.com / …), or other. Chain folds into direct in the headline number because chain pages are still brand-controlled.
Sponsored placementsWorldwide
OpenAI is rolling out paid sponsor placements in the US, Australia, New Zealand, and Canada — testing may expand. We detect real single-advertiser ad units (organic shopping cards excluded) and pull the brand.
| # | Advertiser | Captures |
|---|---|---|
| 1 | Expedia | 275 |
| 2 | Booking.com | 43 |
| 3 | Luxury Escapes | 22 |
| 4 | trivago | 16 |
| 5 | Super.com | 14 |
| 6 | Radisson Hotels | 13 |
| 7 | IHG Hotels & Resorts | 5 |
| 8 | Apple Vacation | 5 |
| 9 | Ocean Signature Resorts | 3 |
| 10 | Viator | 3 |
Where ChatGPT pulls hotel information from
Every URL ChatGPT retrieved classified into 12 buckets: OTAs, editorial, chain sites, direct hotel pages, social, meta-search, AI tools, community, government, directory consortia, and other.
Other destination.com 43% · tripexpert.com 36% · hotelscombined.com.au 21% | 25.1% | 56 |
Review Site tripadvisor.com 69% · tripadvisor.ca 16% · oyster.com 15% | 22.4% | 50 |
OTA & Aggregator booking.com 56% · expedia.com 27% · hotels.com 17% | 20.2% | 45 |
Social Channel reddit.com 98% · youtube.com 2% | 9.0% | 20 |
Community hotelierschoice.com 76% · therooftopguide.com 12% · boutiquehotel.guru 12% | 7.2% | 16 |
Editorial timeout.com 40% · thehotelguru.com 37% · cntraveler.com 23% | 5.8% | 13 |
Meta-search hotelscombined.com 62% · google.com 19% · kayak.com 19% | 5.4% | 12 |
Chain marriott.com 51% · hilton.com 28% · all.accor.com 21% | 3.6% | 8 |
Independent Hotel grandferdinand.com 40% · lasiestahotels.com 30% · vdara.mgmresorts.com 30% | 0.9% | 2 |
Government / DMO esmadrid.com 37% · newzealand.com 33% · choosechicago.com 30% | 0.4% | 1 |
Top hotel parent groups by ChatGPT mentionsWorldwide
Each ChatGPT mention matched against Google Places, then rolled up to parent group (Marriott = Ritz-Carlton + Westin + Sheraton + EDITION + …, etc.). WoW delta vs last week. Detection via 175+ brand-domain rules.
| 1 | Aman | 8 → 14 | +75% |
| 2 | 1 Hotels | 9 → 15 | +67% |
| 3 | Belmond | 9 → 13 | +44% |
| 4 | Wyndham | 15 → 21 | +40% |
| 5 | Rosewood | 18 → 24 | +33% |
| 1 | Meliá | 23 → 11 | -52% |
| 2 | Design Hotels | 12 → 6 | -50% |
| 3 | Radisson | 30 → 16 | -47% |
| 4 | Langham | 33 → 18 | -45% |
| 5 | Shangri-La | 41 → 27 | -34% |
| # | Brand | Mentions | Hotels | W/W | |
|---|---|---|---|---|---|
| 1 | Marriott | 295 | 150 | ↓ 17.1% | |
| 2 | Accor | 164 | 92 | ↓ 11.4% | |
| 3 | Four Seasons | 125 | 39 | ↑ 19.0% | |
| 4 | Hilton | 120 | 67 | ↓ 14.3% | |
| 5 | Hyatt | 114 | 63 | ↓ 10.9% | |
| 6 | IHG | 99 | 68 | ↓ 13.2% | |
| 7 | Mandarin Oriental | 60 | 19 | ↑ 9.1% | |
| 8 | Kempinski | 33 | 9 | ↑ 26.9% | |
| 9 | Minor | 31 | 18 | ↓ 11.4% | |
| 10 | Peninsula | 27 | 10 | ↑ 3.8% | |
| 11 | Shangri-La | 27 | 11 | ↓ 34.1% | |
| 12 | Taj | 26 | 13 | · 0% | |
| 13 | Rosewood | 24 | 11 | ↑ 33.3% | |
| 14 | Wyndham | 21 | 18 | ↑ 40.0% | |
| 15 | Langham | 18 | 5 | ↓ 45.5% | |
| 16 | Oberoi | 16 | 5 | ↑ 14.3% | |
| 17 | Radisson | 16 | 12 | ↓ 46.7% | |
| 18 | Capella | 15 | 6 | · 0% | |
| 19 | 1 Hotels | 15 | 5 | ↑ 66.7% | |
| 20 | Aman | 14 | 7 | ↑ 75.0% |
Of the hotels named this week: how many resolved to a chain (Marriott / Accor / …), an independent property, a vacation rental, or stayed unmatched.
What every metric means
Plain-English definitions for each number on this page. For deeper visuals + examples, see the annual landscape report linked at the bottom.
- Captures
- Number of AI responses we collected this week. Target = 616 per platform (one per prompt). Less when there are upstream errors.
- Web search
- Did the response trigger a live web fetch? Detected from the underlying response stream’s search-result events, not the unreliable top-level flag. We do NOT force web search — this is organic model behavior.
- Map widget
- Did the response render a hotel-card map (the Google-Maps-style widget ChatGPT shows for travel queries)? Each card is a "map entity" with its own provider.
- Sponsored placements
- Paid sponsor placements. Detected from real single-advertiser ad units in the response stream. Excludes ChatGPT’s organic shopping cards (which are unpaid product carousels). US/AU/NZ/CA only as of May 2026.
- Sources / response
- Distinct URLs the model consulted while answering — the URLs that show up in its retrieval log, regardless of whether it cited them inline. Computed only over web-search responses (otherwise the answer is from training data, no sources to count).
- Citations / response
- Subset of sources that the model rendered as inline footnote pills in the answer. A source becomes a citation when the model explicitly references it.
- Fanouts / response
- Number of sub-queries the model spun up internally to answer the prompt (e.g. "best hotels Paris" might fan out to "hotels Paris Marais", "luxury hotels Paris", "rooftop hotels Paris", …).
- Map entities / response
- Hotel cards inside the map widget. Each carries a provider (Google Places, TripAdvisor, Yelp, Foursquare, SERP) and a place ID where applicable.
- OTA
- Online travel agency (Booking, Expedia, Hotels.com, Agoda, Trip.com, Priceline, etc.) — commission-based booking sites.
- Direct
- A hotel’s own website. Computed at request time by matching the cited domain against Google Places.
- Chain
- A hotel chain’s brand website (hilton.com, marriott.com, ihg.com, …). 175+ chain-domain rules.
- Editorial
- Travel media (Condé Nast Traveler, Time Out, Lonely Planet, Forbes Travel Guide, NYT, etc.) and city-specific travel blogs (santorinidave.com, theurbanlist.com, etc.).
- Directory
- Multi-property hotel consortia / brand collectives (Small Luxury Hotels of the World, Design Hotels, Preferred Hotels, Virtuoso, …). Aggregate hotels under one umbrella but aren’t a single OTA.
- Review
- TripAdvisor, Oyster, Yelp, Trustpilot, Holidaycheck — review-first platforms.