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 Germany — ChatGPT
ChatGPT's top picks specifically in Germany. 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 | 286 |
| 2 | trivago | 41 |
| 3 | Booking.com | 27 |
| 4 | IHG Hotels & Resorts | 8 |
| 5 | GetYourGuide | 7 |
| 6 | Skyscanner Limited | 6 |
| 7 | Super.com | 5 |
| 8 | Airbnb | 4 |
| 9 | Radisson Hotels | 3 |
| 10 | Navan Edge | 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.
OTA & Aggregator booking.com 52% · expedia.com 33% · hotels.com 15% | 28.7% | 29 |
Review Site tripadvisor.com 75% · tripadvisor.co.uk 15% · tripadvisor.ca 9% | 24.8% | 25 |
Other hanoitourism.org 35% · lucalvry.com 35% · blog.hotelslash.com 29% | 16.8% | 17 |
Editorial thehotelguru.com 43% · timeout.com 35% · cntraveler.com 22% | 10.9% | 11 |
Community hotelierschoice.com 86% · budgetyourtrip.com 10% · hostelworld.com 4% | 9.9% | 10 |
Meta-search kayak.com 44% · hotelscombined.com 35% · momondo.com 21% | 4.0% | 4 |
Government / DMO neworleans.com 47% · miamiandbeaches.com 29% · visitdublin.com 24% | 2.0% | 2 |
AI Tool staygenie.app 95% · italyplanner.ai 3% · topratedplaces.ai 3% | 2.0% | 2 |
Chain all.accor.com 35% · fourseasons.com 33% · marriott.com 32% | 1.0% | 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 | One&Only | 5 → 10 | +100% |
| 2 | Iberostar | 7 → 11 | +57% |
| 3 | Taj | 23 → 32 | +39% |
| 4 | Radisson | 16 → 22 | +38% |
| 5 | Meliá | 11 → 14 | +27% |
| 1 | Mandarin Oriental | 62 → 42 | -32% |
| 2 | Peninsula | 28 → 20 | -29% |
| 3 | Capella | 18 → 13 | -28% |
| 4 | Wyndham | 21 → 16 | -24% |
| 5 | Aman | 14 → 11 | -21% |
| # | Brand | Mentions | Hotels | W/W | |
|---|---|---|---|---|---|
| 1 | Marriott | 319 | 179 | ↑ 6.3% | |
| 2 | Accor | 172 | 106 | ↑ 5.5% | |
| 3 | Hilton | 131 | 92 | ↑ 10.1% | |
| 4 | Hyatt | 119 | 76 | ↑ 3.5% | |
| 5 | Four Seasons | 112 | 36 | ↓ 10.4% | |
| 6 | IHG | 103 | 73 | ↑ 4.0% | |
| 7 | Mandarin Oriental | 42 | 19 | ↓ 32.3% | |
| 8 | Taj | 32 | 14 | ↑ 39.1% | |
| 9 | Kempinski | 29 | 11 | ↓ 9.4% | |
| 10 | Minor | 27 | 17 | ↓ 12.9% | |
| 11 | Shangri-La | 24 | 12 | ↓ 17.2% | |
| 12 | Radisson | 22 | 18 | ↑ 37.5% | |
| 13 | Peninsula | 20 | 9 | ↓ 28.6% | |
| 14 | Oberoi | 20 | 5 | ↑ 25.0% | |
| 15 | Rosewood | 20 | 8 | ↓ 9.1% | |
| 16 | Langham | 17 | 5 | ↓ 5.6% | |
| 17 | Wyndham | 16 | 16 | ↓ 23.8% | |
| 18 | 1 Hotels | 14 | 6 | ↓ 6.7% | |
| 19 | Meliá | 14 | 10 | ↑ 27.3% | |
| 20 | Capella | 13 | 7 | ↓ 27.8% |
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.