GEO for Travel & Hospitality: How Brands Can Appear in AI Recommendations
This guide was produced by AI, TELL ME!, a Berlin-based AEO and GEO agency with its own AI search monitoring platform.
Summary
A traveller now asks an LLM where to stay before opening a single booking site, and generative engine optimisation is what decides whether a hotel or destination brand gets named in that answer at all. This piece looks at why travel queries behave differently from a product search, since one trip involves inspiration, destination choice and local recommendations, each pulled from a different mix of sources. It covers where brands lose visibility once online travel agents and outdated pages fill the gap a hotel's own website should occupy, and closes with the fixes that turn a brand from being paraphrased into being cited directly.
Travel used to start with a search bar and ten blue links. Increasingly it starts with a single open-ended question typed into an LLM (large language model), and generative engine optimisation is what decides which hotels and destinations that question surfaces: where should we stay in Lisbon with two kids under ten, which boutique hotels in the Douro Valley are open in November. The answer is a short, synthesised recommendation with two or three named options, and a brand left out does not get a second chance further down the page, because there is no page.
Why Travel Planning Now Runs Through AI Before It Reaches a Booking Page
Adoption is still early but the direction is clear. McKinsey's research on AI-assisted travel planning found that fewer than a third of travellers have used generative AI for trip-related tasks so far, yet 84% of those who did said it improved their experience, and traffic those tools sent to travel sites showed a bounce rate 45% lower than other channels (McKinsey & Company). General research led at 54% of use cases, followed by inspiration and local food recommendations at 43% each.
The operator side is moving faster. A separate McKinsey survey found that 90% of travel executives already use generative AI somewhere in the business, and over 90% of consumers reported some confidence in AI-given travel information, even though only 2% would let AI change a booking without human oversight (McKinsey & Company). That gap between trust in the information and trust in the transaction is where GEO sits: the recommendation stage is already largely automated, and the booking stage still runs through the brand's own site, an OTA or a call centre.
What Generative Engine Optimisation Means for Travel and Hospitality
Generative engine optimisation is the work of making sure LLMs can find, verify and correctly repeat what is true about a property or destination, rather than defaulting to whichever third-party listing is easiest to paraphrase. It differs from search engine optimisation, because ranking on Google for "boutique hotels Porto" does not guarantee an LLM names that hotel in a conversational answer. For travel, the pool of sources an LLM draws from is unusually crowded, spanning brand websites, OTAs, review platforms, tourism boards and travel media, each describing the same property in slightly different terms.
That crowding makes GEO for travel harder than for most sectors. A hotel cannot edit a three-year-old review describing a room type it no longer offers, nor control the OTA listing an LLM might cite instead of its own site. The table below shows how travel queries typically get answered and which sources carry the most weight.
Query type | What it tests | Typical source AI leans on |
Destination inspiration | Broad appeal, seasonality, fit | Travel media, tourism boards |
Property shortlist | Category fit, amenities, price tier | OTAs, review aggregators |
Policy or amenity fact-check | Accuracy of a specific claim | Brand website, booking engine |
Local recommendations | Proximity, relevance, freshness | Review platforms, local guides |
Price positioning | Where a brand sits against rivals | OTAs, comparison sites |
Where Travel and Hospitality Brands Lose Visibility
Four patterns show up repeatedly once a brand checks how it appears in AI answers rather than assuming it does.
OTA intermediation: a property with a thin direct website gets described through its Booking.com or Expedia listing, so the brand has no say over which amenities or policies get repeated back.
Stale renovation data: a wing closed for refurbishment eighteen months ago still gets recommended because the source the model pulled from was never updated.
Fragmented review sentiment: the same property reads as excellent on one platform and mediocre on another, and an LLM synthesising both can land on a flattened impression that undersells guests' actual experience.
Generic destination framing: smaller destinations often suit a traveller's brief just as well as major hubs, yet there is far less citable content describing who they are for, so an LLM defaults to whatever is already well documented.
Each is fixable, but only once a brand knows which is happening in its own case, which is where monitoring comes in rather than guessing.
Building a Monitoring Practice for Travel and Hospitality Prompts
A single spot-check query cannot tell a brand whether it is visible, because travel prompts vary by season, traveller type and stage of the journey in a way a software comparison does not. A monitoring practice for this sector needs prompts across four dimensions: destination-level, property-level, use-case such as family travel or accessibility, and seasonal, tied to specific months. Running the same prompts on a recurring basis, rather than once, shows whether visibility is stable or drifting, in the way described in AI, TELL ME!'s guide to checking whether ChatGPT recommends a brand. AEO Monitoring gives a brand that baseline before anything gets changed.
Turning Visibility Gaps Into Fixes
Once the gaps are visible, the fix runs on two tracks at once. The first is owned content: property and policy pages need to state facts in a form that is easy to extract and quote rather than buried in marketing copy, the discipline covered in how to get a website cited by ChatGPT and other AI search engines. The second is the external layer a hotel does not fully control: keeping OTA listings, tourism board pages and travel media aligned with what is true today, since an LLM has no way to know a listing is outdated unless a more trustworthy source contradicts it. A flawless website with no third-party coverage still risks being described entirely through an OTA listing.
FAQ
Does generative engine optimisation replace SEO for a hotel or travel brand?
No. SEO still governs Google rankings. GEO governs a separate, growing channel: whether an LLM names the property when a traveller asks a conversational question.
Why does a well-reviewed hotel still get left out of AI recommendations?
Reviews alone do not guarantee visibility. If the strongest reviews sit on a platform the model rarely draws from, the property can be passed over for a less impressive but better-documented competitor.
How often should a travel brand check its AI visibility?
Monthly is a reasonable baseline, with more frequent checks around seasonal peaks or after a renovation, since those are the moments outdated data is most likely to cause harm.
Can a small independent hotel compete with large chains in AI answers?
Yes, because LLMs do not rank by brand size the way a paid search auction does. A smaller operator with clear, well-distributed information about a niche can outperform a larger brand with inconsistent signals.
What is the difference between GEO Monitoring and GEO Readiness?
GEO Monitoring tracks how a brand currently appears across LLM answers, covering mentions, citations and sentiment. GEO Readiness looks at why, examining the brand's own site and the external sources an AI system draws from.
A can find out exactly how it appears in AI answers today. AI, TELL ME! runs AEO Monitoring for travel and hospitality brands and turns the results into a GEO Readiness plan.
If you want to see how AI currently describes your property or destination brand and where run a free AEO Monitoring check at aipleasetellme.com.
