Hotel AEO: how a property gets written into the answer

Answer engine optimization for hotels is not schema markup with a new name. It is the work of being readable, trustworthy and quotable, and the first surprise is that the highest leverage asset is often not your website.

app.reporte.ai/ai
ChatGPT 3.446
Copilot 173
Perplexity 110
Gemini 78
Claude 19

AI sessions measured across the sites we track, last 30 days.

Quick answer

Hotel AEO is the work of making a property extractable, trustworthy and citable by answer engines, and of proving it with measurements rather than opinion. In our pass of 3 and 4 September 2026 we ran 57 questions across ChatGPT, Claude, Gemini, Perplexity and Google AI Mode over 7 domains, 285 measurements with 0 errors: 3 of those 7 domains appeared in at least one surface and 4 appeared in none. Invisibility is the normal starting state, and it is measurable before it is fixable.

The four layers, and the order is not negotiable

Access comes first. If a crawler gets a 403 at the edge, every hour spent on structured data is decoration on a locked door, and edge level blocking is far more common than teams expect because it is a zone setting nobody remembers switching on. Check it with a real request, not by reading your own robots.txt, and use the robots.txt checker for the rules themselves.

Representation is second: what a model actually receives once it gets in. Facts locked inside images, prices that only exist in a booking widget and amenities described in three adjectives are all invisible to a reader that cannot click.

Structure is third: whether the answer to the question is at the top of the page or buried under sales copy. Fourth is verifiability, which is what turns a property from a plausible option into a source worth quoting. The AI readiness grader scores all four on a fixed 100 point scale and generates an llms.txt from real pages.

On local questions the lever is the business profile, not the page

This is the finding that changes budgets. In a test on local hotel questions during the 3 and 4 September 2026 pass, Google AI Mode built its answer from 41 references and 34 of them were Google entity panels rather than websites. Five out of six citations went to a business profile.

The practical consequence is uncomfortable for anyone selling a website rebuild. On that surface, the highest return per hour of work is a complete business profile with correct categories, hours, amenities, photos and reviews, and only after that the pages that support it. It is also cheap to keep measuring: Google AI Mode cost 0.0040 USD per question in that pass, the lowest of the five surfaces by a factor of almost 20 against ChatGPT at 0.0796 USD, and it still surfaced the measured site in 14 of the 57 questions against 10 for ChatGPT, across 7 domains of our own travel network rather than one hotel.

Being named and being cited are two different jobs

In that same pass the best performing domain appeared in all five surfaces, but its name is written into the body of the answer in only two of them, ChatGPT and Google AI Mode. On Claude, Gemini and Perplexity it appears only in the source list under the answer, which means a reader has to look down and click to ever learn it exists.

Those are two different pieces of work and confusing them wastes a quarter. Getting into the source list is an access and authority problem. Getting your name into the sentence is a content problem: the model has to find a specific, attributable claim worth repeating. A small property we measure on the Costa Tropical in Granada, a camping, entered the September pass with one question and zero appearances across the five surfaces, and the honest first deliverable there was not a promise, it was the baseline. The distinction is tracked per question in prompt analysis, and the writing side is AI content strategy.

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