Nicolas Sitter
Still in beta. Spot something off or have ideas? Send me your feedback — DM on LinkedIn or email. Bugs forward 🙏
Live · refreshed weeklyUpdated September 7, 2026

AI Hotel Landscape

How leading AI assistants recommend hotels — 616 prompts across 56 destinations, refreshed every Monday.

Data is directional. Some prompts retry due to upstream variance, so absolute counts can shift ±5% week to week.
PROMPTS

The 11 prompts we ask ChatGPT about Hong Kong

Same 11 question patterns asked about every destination — persona (couples, families, solo, business), budget (luxury, mid, budget), and zoom (city-wide, neighborhood, landmark).

family friendly hotels in Hong Kong
persona: familieszoom: wide
best hotels in Hong Kong for couples
persona: coupleszoom: wide
luxury hotels in Hong Kong
budget: luxuryzoom: wide
affordable hotels in Hong Kong under $200
budget: budgetzoom: wide
best hotels in Hong Kong for solo travelers
persona: solo_leisurezoom: wide
best hotels in Hong Kong
zoom: widecontrol
boutique hotels in Central, Hong Kong
zoom: near
best hotels in Central, Hong Kong
zoom: near
hotels in Hong Kong with rooftop pool
zoom: wide
hotels near Victoria Peak, Hong Kong
zoom: near
best hotels in Hong Kong for business travelers
persona: solo_businesszoom: wide
HIGHLIGHTS

Named hotels in Hong Kong — ChatGPT

ChatGPT's top picks specifically in Hong Kong, HK. Pick a different destination above, or clear to see worldwide.

Hotel of the Week
9 mentions

Most-mentioned hotel by ChatGPT this week.

Top 20 hotels by ChatGPT mentions — week of September 7, 2026
#HotelCityChainMentionsW/W
1Four Seasons Resort Maldives at Kuda HuraaFour Seasons9 9
59Upper House Hong KongAdmiralty5 5
75Four Seasons Hotel Hong KongCentralFour Seasons4 4
134The Peninsula Hong KongTsim Sha TsuiPeninsula4 4
101Mandarin Oriental, Hong KongCentralMandarin Oriental4 4
270The Ritz-Carlton, Hong KongKowloonMarriott3 3
279The St. Regis Maldives Vommuli ResortMarriott3 3
166Conrad Maldives Rangali IslandHilton3 3
239Rosewood Hong KongTsim Sha TsuiRosewood3 3
237Regent Hong KongTsim Sha TsuiIHG3 3
307Anantara Kihavah Maldives VillasMinor2 2
383Gili Lankanfushi Maldives2 2
ADS

Sponsored placements in Hong Kong

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.

No sponsored placements detected for Hong Kong this week. Ad geo coverage is limited to US / AU / NZ / CA.
SOURCES

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.

Review Site
16.4% (9)
Editorial
16.4% (9)
Chain
14.5% (8)
OTA & Aggregator
14.5% (8)
Other
12.7% (7)
Hotel Directory
9.1% (5)
Independent Hotel
9.1% (5)
Meta-search
3.6% (2)
Community
3.6% (2)
Top categories
Review Site
tripadvisor.com 50% · en.tripadvisor.com.hk 38% · oyster.com 13%
16.4%9
Editorial
timeout.com 43% · cntraveller.com 29% · tatlerasia.com 29%
16.4%9
Chain
marriott.com 40% · peninsula.com 40% · fourseasons.com 20%
14.5%8
OTA & Aggregator
booking.com 75% · expedia.com 13% · hk.trip.com 13%
14.5%8
Other
babagoeschina.com 33% · budgetdecoded.com 33% · lajollamom.com 33%
12.7%7
Hotel Directory
hotelsforkings.com 100%
9.1%5
Independent Hotel
upperhouse.com 50% · 99bonham.com 25% · mondrianhotels.com 25%
9.1%5
Meta-search
hotelscombined.com 50% · momondo.com 50%
3.6%2
Community
budgetyourtrip.com 50% · hotelierschoice.com 50%
3.6%2
Has that changed over time?
20 weeks · 2026-04-272026-09-07

Share of citations by source type, week by week, for Hong Kong. Search engine is its own bucket rather than part of metasearch, and covers Google (every regional domain), Bing and the rest. Google AI Mode routes its cited sources through google.com/searchviewer instead of linking the publisher, and those citations were landing under “meta-search” alongside trivago and kayak — which made the mix read as competitive pressure from metasearch when actual metasearch is under 1%. The dashed rule marks the week that started.

OtherReview siteEditorialChainOTAIndependent hotelCommunitySmaller categories
0%20%40%60%searchviewer04-2705-1806-0806-2907-2008-1008-3109-07

Which categories get a line is decided once over the whole window by total citations, not week by week — otherwise a category dropping out of the top N would look like it collapsed to zero. Everything below the cut is summed into “smaller categories” rather than dropped, so the lines always account for the full week. Citations per week: 04-27 108 · 05-04 336 · 05-11 7 · 05-18 36 · 05-25 191 · 06-01 441 · 06-08 362 · 06-15 149 · 06-22 157 · 06-29 242 · 07-06 265 · 07-13 124 · 07-20 138 · 07-27 127 · 08-03 109 · 08-10 104 · 08-17 117 · 08-24 55 · 08-31 102 · 09-07 55.

BRANDS

Top hotel parent groups in Hong Kong — ChatGPT

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.

#BrandMentionsHotelsW/W
1Marriott53 66.7%
2Four Seasons41 33.3%
3Mandarin Oriental42 20.0%
4Peninsula31 50.0%
5IHG31 40.0%
6Rosewood31 200.0%
7Hyatt32 200.0%
8Wyndham11
9Hilton11 50.0%
10Shangri-La11 50.0%
Chain vs Independent

Of the hotels named this week: how many resolved to a chain (Marriott / Accor / …), an independent property, a vacation rental, or stayed unmatched.

Chain59.6% 3.7%
Independent40.4% 51.3%
Vacation rental0.0%
Unresolved0.0% 100.0%
DEFINITIONS

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.
Want a deeper read? See the in-depth annual report