▪ benchmark

UK hotel AI visibility benchmark

Scanned August–September 2026 · updated 3 October 2026

We scanned 30 UK hotels and guest accommodation sites — the largest sample in the corpus, and the lowest median of any vertical we measured.

Median score
55.5
Range
10.0–71.8
Businesses scanned
30
Worth per customer
£280

The lowest median of any vertical: 55.5

55.5median score, the lowest of the four verticals measured, and the only one whose range reaches into single figures.
10.0the floor. At least one property in the sample is close to invisible to an assistant — not ranked badly, but barely legible as a business at all.
Largest sampleAt n=30 this is the most reliable figure in the corpus. Treat the hotel median as the firmest number here.

Hotels compete in the single most assistant-mediated category there is — "where should I stay in…" is a question people put to an assistant constantly.

True in every vertical

Three findings held across all 82 businesses we scanned, regardless of industry:

CheckScoreWhat it means
Agentic commerce endpoints0.00Not one business of 82 exposes an ACP or AP2 surface. An assistant cannot transact with any of them directly.
llms.txt guidance file~0.15Almost nobody publishes one. It is free to add and takes minutes.
Structured data (schema.org)0.25–0.32The single biggest scoring gap in every vertical. Without it an assistant has to infer what the business even is from prose.

What this measures, in fourteen seconds

A question put to four AI assistants, with a score for each.
No business is named. The result shown is an example.

Where does your site sit?

The same audit, run on your own domain. One field, about twenty seconds, no account and no card.

Run the free check →

How this was measured

Each site was scanned by an automated audit that scores nine weighted checks: crawler access, structured data, whether content survives without JavaScript, machine-readable pricing, bot protection, terms and security, an llms.txt guidance file, sitemap discoverability, and agentic commerce endpoints. The score is out of 100.

This measures what a machine can read on the public website. It is a separate question from whether an assistant actually names the business when asked — that is measured by putting real questions to ChatGPT, Perplexity, Gemini and Claude, and the two do not always agree.

n = 30 · scanned August–September 2026 · no business named

The other verticals