Article · in the hotels report
Travel · Industry benchmark
Stage 0 · Framework live · benchmark pending'Best hotel in Goa for a honeymoon' — AI answers with 4 names and an OTA link. Are you in it, and is the booking yours?
CiteRank measures who AI engines recommend in hotels — across ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, Microsoft Copilot, xAI Grok and Meta AI, in both grounded and ungrounded modes — and fixes why it isn't you.
Vertical benches currently run 8 engines; full tracking covers all 8.
8 × 2
Engines × modes (grounded + ungrounded)
250
Hotels tracked prompts per run on Platform
Weekly
Re-runs · 95% confidence bands
Who AI recommends today
The hotels leaderboard, measured.
Top-5 brand mention rate, first-mention rate and Share of Voice — straight from the citerank-bench scoring tables, recomputed weekly.
Benchmark for Hotels runs with our first customer in this vertical. The leaderboard below is an illustrative sample built from the blueprint's brand registry — numbers are placeholders, not measurements.
#
Brand
Mention rate
First-mention
Share of Voice
01
Taj Hotels
62%
31%
34%
02
Oberoi
48%
22%
24%
03
ITC Hotels
39%
14%
18%
04
Marriott
27%
9%
14%
05
MakeMyTrip (OTA capture)
18%
5%
10%
Illustrative sample — benchmark not yet completed.
Sample prompt set
Real hotels prompts, eight engines, one question: did you get cited? Gartner predicts a 25% shift from search to AI agents by 2026 (Gartner).
Buyer prompt
ChatGPT
Gemini
Claude
Perplexity
AI Overviews
Microsoft Copilot
xAI Grok
Meta AI
You cited?
"best 5-star hotel in Goa for a honeymoon"
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—
—
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—
—
Not yet
"business hotels near Whitefield with day-use rooms"
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Not yet
"{hotel} vs {hotel} — which has the better pool and breakfast?"
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Not yet
"is {hotel} dog-friendly and what is the policy?"
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Not yet
Where the citations leak
Three failure modes specific to travel.
01
OTA capture: MakeMyTrip/Booking/Agoda are cited as the booking surface, even when you're the brand named.
02
Itinerary prompts compose recommendations from blog content you don't own.
03
Seasonal answers go stale fast — engines keep quoting last year's prices and amenities.
Methodology
How a hotels benchmark gets built.
01
Onboard
URL, competitors, prompt seed list. 5 minutes.
02
Audit
25 prompts × 8 engines × 2 modes, 10–20 replays each.
03
Fix
Schema, llms.txt, entity hygiene, content briefs — shipped.
04
Re-run
Weekly re-runs, deltas with 95% confidence bands.
Illustrative pattern
What a 90-day citation delta looks like.
Illustrative pattern based on our methodology — first customer results publish Q4 2026.
Before
1 / 25
Cited in 1 of 25 high-intent hotels prompts across 8 engines (4%).
After · 90 days
9 / 25
Cited in 9 of the same 25 prompts (36%) — schema, llms.txt and entity fixes shipped over 3 weekly re-runs.
Category Intelligence
Hotels Citation Intelligence
This section contains Verified Category Data observed during current Hotels monitoring runs. These patterns define how AI engines rank your competitors and why certain brands are cited over others.
Top Category Prompts
- "best 5-star hotel in Goa for a honeymoon"
- "business hotels near Whitefield with day-use rooms"
- "{hotel} vs {hotel} — which has the better pool and breakfast?"
- "is {hotel} dog-friendly and what is the policy?"
Engine Citation Skew
ChatGPTIncumbent brand bias
PerplexitySource-heavy grounding
AI OverviewsSnippet-friendly listicles
Dominant Source Domains
g2.comreddit.comtrustpilot.comforbes.com
Awaiting full benchmark for live domain weights.
Case study
Hotels case study publishes after the first 90-day window.
We don't ship anonymous success stories. Every case study card on this page becomes a real logo, real prompts and real deltas after the customer's 90-day window closes.
Insights
Coming in the Hotels visibility report.
Article · in the hotels report
City-prompt leaderboards for Indian hotels, measured monthly
Notify me when publishedArticle · in the hotels report
Amenity hallucinations and the guest-experience gap
Notify me when publishedFAQ
Hotels questions, answered.
How is CiteRank different from Google Business Profile / aggregator listings?+
Those surfaces optimise for their own funnel. CiteRank measures how often ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, Microsoft Copilot, xAI Grok and Meta AI actually name your brand for hotels buyer prompts, then fixes the schema, entity and content gaps so the engines have something to cite besides the aggregator.
Which segments / cities do you cover for this vertical?+
We start with your highest-intent buyer prompts (250 tracked prompts on Platform, 500 on Platform + GEO) — segmented by city, persona and price band as relevant — and expand the prompt graph weekly. Coverage scope is set during the 5-minute onboarding.
How fast to first new citation?+
First measurable citation lift is typically 3–5 weeks after the first fix pass (schema, llms.txt, entity, content briefs). Re-runs are weekly with 95% confidence bands so you can attribute deltas to specific fixes.
Is our data sent to LLMs?+
Only the public buyer prompts we run on your behalf reach the engines — exactly what a prospective customer would type. We do not send your CRM, customer data, or internal documents to any LLM.
How to start
Start with one snapshot. Scale into weekly monitoring.
Snapshot Audit
One-time
25 prompts × 8 engines × 2 modes. Brand-mention report and gap analysis.
Monitor
Ongoing
Weekly re-runs, deltas with confidence bands, alerting on rank/citation changes.
Visibility + Fixes
Ongoing
Monitor + shipped fixes: schema, llms.txt, entity, content briefs and re-measurement.
Keep exploring