Evidence benchmark
Rose-Brook shows whether ChatGPT, Gemini and Claude can find, compare and recommend your hotel when guests ask where to stay.
Sample benchmark read
Verdict, model agreement, evidence gaps and the next action.
Guest asks AI
"Best family hotel with parking near the pier?"
Rank
#2 of 4
Gap
22 pts
Why you lost
The leading competitor gives AI clearer parking, room-type and family-arrival proof to repeat.
Fix first
Add explicit parking, family-room and weekend-arrival proof across the website and listings.
AI recommends
1. North Pier Hotel
Clear parking, family-room and pier access proof.
74/100
Recommended first2. Your hotel
Visible, but arrival and family-stay evidence is weaker.
52/100
Second choice3. Harbour House
Useful local restaurant evidence, weaker guest-fit proof.
41/100
MentionedModel agreement
ChatGPT
Competitor first
Gemini
Competitor first
Claude
Your hotel close
Included in the benchmark
Exact prompts and answers saved
Competitor proof separated from hotel proof
Fix-first brief for web and listing updates
What you get
The benchmark is designed for owners, GMs and commercial teams who need a fast read before they inspect the supporting prompts.
A plain read of whether assistants appear ready to choose your hotel for guest-style stay questions.
A competitor view showing which nearby hotels are being named, preferred, or easier for AI to defend.
One practical evidence action for the website, listings, amenities, location proof, or guest-fit copy.
How it works
Rose-Brook gives hotel teams a repeatable way to see the current AI recommendation story, then decide which public evidence to make clearer.
Confirm the hotel and the real competitors guests might book instead.
Run repeatable guest-intent prompts across the benchmark.
Read the verdict first, then open the evidence only when you need to audit it.
Common questions
The product stays evidence-led, but the default view is built for a 60-second commercial decision.
Hotel AI visibility is whether an AI assistant can find, compare and recommend a hotel when a guest asks where to stay.
Rose-Brook benchmarks what assistants say, which competitors appear, and what evidence gaps may make a hotel easier or harder to recommend.
The default read shows whether AI would recommend the hotel, who AI recommends first, the main reason, and the first evidence fix to make before the next benchmark.
The product keeps prompt evidence, scoring notes and model agreement available behind evidence views. The public long-form guide explains the category in more detail.