AI Hotel Landscape
How leading AI assistants recommend hotels — 616 prompts across 56 destinations, refreshed every Monday.
+ 44 more
The 616 prompts we ask Google AI Mode 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 Vienna — Google AI Mode
Google AI Mode's top picks specifically in Vienna, AT. Pick a different destination above, or clear to see worldwide.
Most-mentioned hotel by Google AI Mode this week.
When Google AI Mode 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.
Where Google AI Mode pulls hotel information from
Every URL Google AI Mode retrieved classified into 12 buckets: OTAs, editorial, chain sites, direct hotel pages, social, meta-search, AI tools, community, government, directory consortia, and other.
Meta-search google.com 100% · kayak.com 0% · trivago.com 0% | 71.2% | 213 |
OTA & Aggregator expedia.com 40% · booking.com 31% · agoda.com 30% | 6.4% | 19 |
Other foratravel.com 44% · secretplaces.com 32% · akbartravels.com 24% | 4.7% | 14 |
Editorial cntraveler.com 41% · thehotelguru.com 37% · forbestravelguide.com 22% | 4.0% | 12 |
Social Channel youtube.com 54% · reddit.com 25% · facebook.com 21% | 2.7% | 8 |
Review Site tripadvisor.com 93% · tripadvisor.co.uk 4% · oyster.com 3% | 2.7% | 8 |
Government / DMO neworleans.com 43% · discoverzermatt.com 30% · myswitzerland.com 26% | 2.0% | 6 |
Community myboutiquehotel.com 46% · santorinidave.com 36% · therooftopguide.com 19% | 2.0% | 6 |
Independent Hotel scottdunn.com 50% · cordishotels.com 25% · meritelhanoi.com 25% | 1.7% | 5 |
Chain marriott.com 37% · all.accor.com 35% · fourseasons.com 28% | 1.7% | 5 |
Hotel Directory designhotels.com 49% · hotelsforkings.com 25% · slh.com 25% | 0.7% | 2 |
AI Tool staygenie.app 100% | 0.3% | 1 |
Top hotel parent groups by Google AI Mode mentionsWorldwide
Each Google AI Mode 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 | 1 Hotels | 4 → 10 | +150% |
| 2 | Langham | 22 → 25 | +14% |
| 3 | Minor | 23 → 25 | +9% |
| 4 | Belmond | 13 → 14 | +8% |
| 1 | Rosewood | 18 → 13 | -28% |
| 2 | Shangri-La | 25 → 20 | -20% |
| 3 | Kempinski | 24 → 20 | -17% |
| 4 | Taj | 23 → 20 | -13% |
| 5 | Hyatt | 85 → 76 | -11% |
| # | Brand | Mentions | Hotels | W/W | |
|---|---|---|---|---|---|
| 1 | Marriott | 210 | 128 | ↓ 2.8% | |
| 2 | Accor | 100 | 65 | ↓ 4.8% | |
| 3 | Hilton | 95 | 61 | ↑ 2.2% | |
| 4 | Four Seasons | 80 | 36 | ↑ 1.3% | |
| 5 | Hyatt | 76 | 47 | ↓ 10.6% | |
| 6 | IHG | 68 | 43 | ↓ 2.9% | |
| 7 | Mandarin Oriental | 37 | 15 | · 0% | |
| 8 | Radisson | 27 | 15 | ↓ 3.6% | |
| 9 | Minor | 25 | 16 | ↑ 8.7% | |
| 10 | Langham | 25 | 8 | ↑ 13.6% | |
| 11 | Taj | 20 | 8 | ↓ 13.0% | |
| 12 | Kempinski | 20 | 8 | ↓ 16.7% | |
| 13 | Shangri-La | 20 | 13 | ↓ 20.0% | |
| 14 | Belmond | 14 | 3 | ↑ 7.7% | |
| 15 | Capella | 14 | 6 | · 0% | |
| 16 | Rosewood | 13 | 7 | ↓ 27.8% | |
| 17 | Peninsula | 13 | 6 | · 0% | |
| 18 | Oberoi | 12 | 4 | · 0% | |
| 19 | 1 Hotels | 10 | 5 | ↑ 150.0% | |
| 20 | Wyndham | 7 | 5 | · 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.