AI brand monitoring for hotels: what the assistants say when nobody is watching

Your property is being recommended, or quietly skipped, in conversations you never see. Brand monitoring turns those conversations into a fixed list of questions, measured on the five AI surfaces travellers actually use, and repeated so you read a trend instead of an anecdote.

app.reporte.ai/ai
ChatGPT 3.449
Copilot 173
Perplexity 110
Gemini 78
Claude 19

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

Quick answer

AI brand monitoring for hotels measures, on a fixed list of questions repeated over time, whether an AI assistant names your property, whether it cites your website as a source, in what position and in what tone. In our own measurement pass of 3 and 4 September 2026 we ran 57 questions across 5 AI surfaces for 7 travel and hospitality domains, 285 measurements with zero errors, and the spread between surfaces was wide: 22 of the 57 questions produced a mention in Perplexity and only 10 of 57 in ChatGPT.

Named, cited, ranked and framed are four different results

Most tools report one number, visibility, and that number hides four different outcomes with four different fixes. Being named means the assistant wrote your property into the answer. Being cited means it linked your website as a source. Those two come apart: in the September pass Google AI Mode named a property on 14 of the 57 questions and cited its website on only 13 of them.

Position matters because an answer is a short list and the first item is the one a traveller acts on. When the property was named, the average position was 1.0 in Google AI Mode, 1.6 in ChatGPT, 1.9 in Gemini, 2.0 in Perplexity and 2.1 in Claude.

And the surface decides which lever you pull. In local queries, Google AI Mode cited Google entity cards rather than websites in 34 of 41 references we checked. Reading that as zero citations would send a hotel to rewrite content when the work is in its Google Business Profile.

A zero on one surface is a measurement fault until proven otherwise

The most useful thing we measured in September was our own mistake. A bug on our side returned 57 of 57 Gemini measurements as does not mention you, a clean, closed zero across an entire surface. It compiled, it wrote nothing to any log and it looked perfectly plausible as a business finding.

It was false. After the fix, the same questions on the same day returned 15 visible and 15 cited on that same surface. A monitoring product that cannot tell not measured from not mentioned will eventually tell a hotel that AI ignores it, which is the most expensive wrong answer in the category.

That is why every cell in the panel is painted three ways and not two: measured and mentioned, measured and not mentioned, and not measured with the reason attached.

How it works in reporte.ai

You keep a list of recommendation questions, the kind a traveller actually types, and the pass runs them weekly against the five surfaces. Every run is stored, so the table remembers what it measured last week instead of resetting each time you look at it. The unit cost is known and printed next to the button: 0.0040 USD per question on Google AI Mode, 0.0129 on Perplexity, 0.0415 on Gemini, 0.0456 on Claude and 0.0796 on ChatGPT.

That cost spread is a product decision, not trivia. Google AI Mode is 20 times cheaper than ChatGPT and in the September pass it found more mentions than ChatGPT did, 14 of 57 against 10 of 57, so it is the surface to measure most often. That was one pass, and a single reading proves nothing: what turns it into evidence is the cadence.

The rest of the picture lives one click away: how the assistants frame you when they do name you, who gets recommended instead of you, and how many visits any of it actually sends. For the underlying feature, see prompt analysis.

FAQ

The rest of the product

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