What OpenAI has actually published about browsing and citing
OpenAI documents three crawlers by name: GPTBot, used to train and improve its models; OAI-SearchBot, which powers search-style browsing in ChatGPT; and ChatGPT-User, which fetches a page a user has actively asked the assistant to look at. All three are documented to respect robots.txt rules the same way traditional search crawlers do. That's the extent of what's publicly confirmed about access — which bots exist, roughly what each is for, and that they honor a site's crawl permissions.
What OpenAI has not published is the ranking logic — the internal process that decides, out of everything ChatGPT can access, which specific hotels get named in a given answer and in what order. There's no public documentation of exact ranking weights or a disclosed scoring formula. Any claim about the precise algorithm beyond this is a guess, because OpenAI hasn't said.
Observed behavior in travel-planning answers
Commonly observed behavior — not a confirmed algorithm — is that ChatGPT's travel answers tend to draw on a mix of sources: OTAs like Booking.com and Expedia, review aggregators like TripAdvisor, and, less consistently, hotels' own websites. When ChatGPT names a specific property, it often does so alongside a description that reads as if assembled from a listing page rather than the hotel's own marketing copy.
This pattern shows up repeatedly enough to be worth noting, but it isn't something OpenAI has confirmed as a rule. It's reasonable to assume that easier-to-parse, well-structured sources get pulled from more often — but that's an inference from observed behavior, not a documented mechanism.
What this means for a hotel's site
Given what is confirmed (crawler behavior) and what is reasonably inferred (a preference for clear, structured content), there are concrete things a hotel can control. The first is crawlability: robots.txt needs to allow GPTBot and OAI-SearchBot. This is a hard technical gate rather than a matter of degree — get it wrong and the rest doesn't matter.
The second is structured data — schema.org Hotel and FAQPage markup stating room counts, amenities, address, and common questions in machine-readable form. The third is freshness: pages updated and re-crawled regularly appear, based on observed behavior, to be treated as more current, though OpenAI hasn't published a specific freshness weighting.
Where OTAs and review sites fit in vs. a hotel's own domain
OTAs and review sites appear to have a practical advantage in many ChatGPT travel answers — plausibly driven by heavier investment in structured data, higher site authority, and broader page coverage — though this is an inference from observed patterns, not a confirmed weighting OpenAI has published. A hotel's own domain is often the best source of accurate, first-party facts — but only if it's actually crawlable and structured well enough to be used. When a hotel's own site isn't crawlable or clearly structured, an AI answer appears to fall back on whichever secondary source it can parse most confidently — though the exact fallback logic isn't documented.
Test it yourself, and where to go from here
Ask ChatGPT a guest-style question naming your city and hotel segment, without naming your hotel — for example, "what's a good boutique hotel in Porto for a long weekend." Note whether your hotel is named and what kind of source appears cited or implied. None of this tells you why a hotel was or wasn't named — only OpenAI has that answer, and it hasn't published it. A one-time check tells you where you stand today; only a check repeated on a schedule tells you whether a change actually moved the needle.