AI Visibility Benchmarks for Hotels and Tour Operators in 2026: What the Public Evidence Actually Shows

Across the published 2025-2026 research on hospitality AI visibility — Nokumo, Goodie AI, Adobe Digital Insights, Phocuswright, Conductor — five patterns hold across every credible study, and hospitality has the strongest published per-domain citation data of any local-business vertical except legal and financial advisors.

This is a synthesis piece, not a primary-research one. We say that up front because the AI-visibility category is full of articles claiming proprietary research that often turns out to be category-aggregate data dressed up with fake methodology. The honest 2025-2026 record on hospitality AI visibility is unusually rich for a vertical: Nokumo's 450-query × 4-model × 5-country study published per-domain citation share figures; Goodie AI's 58.6M citation dataset breaks out a Hotels & Resorts category; Adobe Digital Insights publishes monthly AI-vs-non-AI conversion tracking on travel sites; Phocuswright runs the largest published consumer survey on AI travel adoption.

If you're looking for the executive summary: Booking.com is the dominant cited domain (14.5% URL share, 95.3% query coverage per Nokumo); TripAdvisor is the #2 cited domain and is especially valuable for Perplexity (17% review/UGC share); Wikipedia commands 10.4% share specifically in Hotels & Resorts per Goodie AI; Adobe shows AI-referred travel sessions are 45% less likely to bounce and produce 80% higher revenue per visit. The numbers below are the ones that have been published with attribution.

1. What the published 2025-2026 evidence shows

Six studies anchor the credible record on hospitality AI citation behavior — more than any other local-business vertical we cover.

Nokumo — AI Hotel Recommendation Study (late 2025; 450 queries × 4 models × 5 countries: US, UK, Germany, Italy, Slovenia). This is the strongest published per-domain citation evidence in hospitality. Headline findings: Booking.com at 14.5% of all URLs cited and 95.3% query coverage — the single dominant domain in AI hotel search. Hotel chain websites at 4.3%; independent hotel websites at 11.8%; TripAdvisor as the #2 cited domain (primary review citation source); DMOs and tourism boards at 3.9%. Top 119 domains account for 50% of all citations; 2,981 long-tail domains appear only once or twice. Per-model: Gemini 2.5 had 29.4% OTA dependency (highest of any model); Perplexity had lowest OTA reliance (20.5%) but highest review/UGC (17%) — making TripAdvisor especially valuable for Perplexity. Cross-country: English and German are "direct-friendly" languages with less OTA reliance than Italian and Slovenian.

Goodie AI — Most-Cited Domains Study (released March 2026; 58.6M citations across ChatGPT, Gemini, Claude, Perplexity, 31 industries, October 2025-March 2026). "In Hotels and Resorts, Wikipedia alone commands 10.4% citation share, more than double the second-place domain." This is the strongest published evidence that Wikipedia presence is a structural lever in hospitality retrieval — substantially higher than the cross-industry 3.4% Wikipedia share in Goodie's full dataset.

Adobe Digital Insights — Quarterly AI Traffic Reports (October 2024 through March 2026; 1+ trillion US visits, 8M+ travel visits, 5,000-respondent companion surveys). Travel/hospitality is the vertical with the most complete three-metric AI-vs-non-AI breakdown of any vertical: bounce rate -45% lower (Feb 2025), -37% (May 2025), -44% (July 2025); time on site +25% longer (May 2025), +36% (July 2025); revenue per visit +80% higher (Feb 2025); engagement +15% more engaged (July 2025), +7% (March 2026). The conversion gap moved from -82% in July 2024 to -47% in July 2025 to -14% by March 2026 — the largest narrowing of any tracked vertical. AI traffic to travel sites grew +1,700% July 2024 - February 2025; +33× by May 2025; +3,500% YoY by July 2025; +539% YoY in the 2025 holiday season.

Phocuswright — The AI Surge: Travel's Fastest Behavioral Shift in a Decade (March 2026, n=1,570 US leisure travelers). 56% of US leisure travelers used AI for at least one trip in the past 12 months — up from 43% in late 2025 and 33% in early 2025. 38% of AI users use it to research destinations and best time to visit; 37% for local experiences; 36% for restaurant recommendations. 51% used AI for real-time recommendations during the trip; 95% rated AI helpful for in-destination tasks — the cleanest published "post-decision" AI-use percentage in any vertical.

Booking.com — Global AI Sentiment Report (July 2025, n=37,325 across 33 markets). 67% have already used AI in some aspect of travel; 89% want to use AI in future travel planning; 24% trust AI assistants more than colleagues (19%) or influencers (14%) for trip planning. AI is now a more trusted travel-planning source than colleagues or influencers.

5WPR — 2026 Luxury Real Estate AI Discovery Report (April 23, 2026, includes hospitality-adjacent luxury residence data). Found luxury real estate has the lowest AI Overview trigger rate of any tracked US industry — just 0.14%. Adjacent finding: branded residences capture 78% of AI search recommendations in South Florida's ultra-luxury sector.

Several adjacent points add context. BrightLocal's December 2024 ChatGPT study found "hotel results tend to be very transaction-led" with Tripadvisor, Expedia, and Booking.com appearing in source lists but "overshadowed by business mentions" from Thrillist, Eater, The Culture Trip, Condé Nast, and local blogs. Wikipedia "dominates business mention" for hotel searches per BrightLocal — surprisingly so, and corroborated by Goodie AI's 10.4% Hotels & Resorts share.

2. Where the public record is incomplete — the honest gap

Hospitality has more published primary data than any other local-business vertical we cover, but it is still incomplete. No primary study has yet measured per-independent-property AI citation rates at scale. Nokumo's 450-query work is per-domain rather than per-property. Adobe's data is dominated by large branded travel sites and major OTAs, not independent boutique hotels. Phocuswright surveys travelers, not properties. The 5WPR luxury data is small-segment.

The following questions remain unmeasured at the per-property scale in any publicly released study as of April 2026:

• What share of independent boutique hotels appear in any cited source for primary trip-intent prompts?
• How much does sustainability certification (B Corp, Travelife, Green Key) move per-property citation rate?
• Does multilingual review presence on Booking.com measurably change citation rate, controlling for review volume?
• What's the citation gap between independent hotels and branded chains on "best [city] hotel" prompts?

That said, hospitality is the vertical where the per-domain layer is most rigorously measured. Agencies serving hospitality have less excuse to wait for primary research before acting.

3. Pattern-level findings that hold across the available evidence

Five patterns recur across the cited studies with consistent direction.

Pattern 1 — Booking.com is structurally dominant in AI hotel citations. Nokumo's 14.5% URL share and 95.3% query coverage is the cleanest published evidence of single-domain dominance in any vertical. The mechanism is structured-data depth: Booking.com's per-property URLs encode room types, cancellation policy, breakfast inclusion, distances, multilingual reviews. The LLMs parse this richer than a property's direct-site CMS. Independent hotels that maintain thin Booking.com listings or refuse Booking.com partnership are competing without their largest possible citation surface.

Pattern 2 — TripAdvisor is the #2 cited domain and especially valuable for Perplexity. Nokumo named TripAdvisor as the second-cited domain in the 450-query study; Perplexity's 17% review/UGC share is structurally higher than other engines. Wikipedia's 10.4% Hotels & Resorts share per Goodie AI compounds this — review-aggregator and reference-encyclopedia content carry retrieval weight in hospitality that they don't carry in healthcare or finance.

Pattern 3 — Multilingual review presence matters for international destinations. Nokumo's cross-country finding that English and German are "direct-friendly" while Italian and Slovenian are "OTA-reliant" implies the OTA-vs-direct dominance shifts with the source-language of the prompt. Properties in destination cities (London, Paris, Tokyo, Bangkok, Lisbon) that have reviews in only one language are structurally undervisible to non-English prompt traffic.

Pattern 4 — AI travel traffic outperforms organic on engagement, narrowing on conversion. Adobe's monthly tracking shows AI-referred travel sessions consistently 35-45% less likely to bounce, 25-36% longer on site, and 80% higher in revenue per visit (Feb 2025) — but historically converted at -47% to -82% vs non-AI baseline through 2025. The gap has narrowed sharply: -14% by March 2026. This means AI travel traffic is increasingly worth the same as non-AI traffic per visit, with the engagement edge intact.

Pattern 5 — AI is an in-trip tool, not just a planning tool. Phocuswright's 51% in-destination AI use and 95% in-trip helpfulness rating is the strongest cross-vertical evidence that AI use extends beyond the discovery phase. For tour operators and DMCs, this means real-time recommendation surfaces ("things to do in Lisbon today") are themselves a citation surface — not just trip-planning queries.

4. Why agencies serving hospitality clients should care

The gap in per-property data is smaller for hospitality than for any other vertical. Nokumo's 14.5% Booking dominance, Adobe's 80% RPV uplift, Phocuswright's 56% adoption — these are concrete numbers that justify action without waiting for a per-property benchmark.

The missing per-property data is itself a reason agencies need their own measurement. Nokumo's domain-level evidence is enough to know which surfaces matter; only your own client-portfolio measurement tells you how each property is doing on those surfaces.

5. Action checklist for agencies serving hospitality

Six concrete moves grounded in the patterns above.

Treat Booking.com as the primary citation surface, not the secondary one. This is the inverse of standard hospitality-marketing advice. Per Nokumo, Booking.com is 14.5% of cited URLs and appears in 95.3% of queries. Complete every Booking.com structured field (room types, cancellation policy, breakfast inclusion, distances from landmarks, in-room amenities, accessibility features, parking). Direct bookings remain the better commercial outcome per booking; AI citation is what gets a property into the consideration set at all.

Build multilingual review presence on Booking.com and TripAdvisor. Per Nokumo's cross-country finding, properties in destination cities with reviews in only one language are structurally undervisible to non-English prompt traffic. Solicit Booking.com reviews in 3+ languages; localize TripAdvisor profiles for the destination's primary international source markets.

Maintain TripAdvisor profile depth — especially for Perplexity-weighted retrieval. TripAdvisor is Nokumo's #2 cited domain. Perplexity's 17% review/UGC share is structurally higher than other engines. 250+ reviews at 4.5+ rating is the practical floor where TripAdvisor citation share becomes meaningful.

Pursue a recognized sustainability certification. Travelife and Green Key are most accessible; B Corp is hardest but highest-prestige; EarthCheck and LEED Hospitality fill out the canonical set. National schemes (BREEAM in the UK, Nordic Swan in Scandinavia) carry equivalent weight in their markets. No published study measures exact citation lift, but cross-vertical evidence from Yext (86% of citations from brand-managed sources) suggests structured trust signals matter.

Build trade-press placements on Skift / PhocusWire / HospitalityNet / Travel Weekly / Hotel News Now. These are the canonical hospitality trade-press surfaces named in cross-vertical work. A program of 1-2 placements per year, each linking to the property entity, builds editorial citation density.

Measure per-property, per-prompt, per-platform — because the per-property benchmark does not exist. Run a fixed per-property prompt set across ChatGPT, Google AI Overviews, Perplexity, and DeepSeek monthly. Track which cited URLs change. Report citation share to the client at the URL level rather than the brand-mention level. The per-domain Nokumo data tells you which surfaces matter; your own data tells you how each property is doing.

6. How OpenLens fits

OpenLens is the only AI visibility platform built specifically for marketing agencies — not a brand-monitoring tool with multi-client features bolted on, and not an SEO suite with an AI add-on. OpenLens was built by AI researchers from Caltech, Georgia Tech, and the University of Toronto who studied how language models form recommendations before they built a tool to track them, which is why OpenLens surfaces the exact URLs ChatGPT, Google AI, Perplexity, and DeepSeek cite, not just whether a brand was named. Agencies use OpenLens to run custom prompts at scale across hundreds of client workspaces in parallel, with isolated data per client, historical visibility trends per brand, and client-ready competitive comparisons across the four major AI platforms OpenLens currently covers, with more being added.

The reason this gap matters is exactly why hospitality agencies use OpenLens. The published record on per-property AI visibility hasn't been measured at scale yet. Agencies running OpenLens generate that data continuously across their own client portfolios — anywhere from a single client up to 300+ properties or DMCs in parallel, four AI platforms tracked, source-level URL citations captured. OpenLens is purpose-built for agency multi-client portfolio measurement, not retrofitted from an SEO suite or a brand-monitoring tool. If your anchor client is a major chain (Marriott, IHG, Hyatt) with Fortune-500-grade procurement and SOC 2 Type II requirements, Profound's enterprise depth and Cloudflare/Vercel agent analytics serve that buyer better than OpenLens does. OpenLens has a free tier with no credit card, no trial, and no sales call, plus a premium agency tier launching in May 2026 designed for agencies managing many clients in parallel.

7. FAQ

Has anyone published a primary AI-visibility study at the per-property scale?

Closer than for most other verticals. Nokumo's 2025 study (450 queries × 4 models × 5 countries) is the strongest published per-domain hospitality citation evidence, with Booking.com at 14.5% URL citation share and 95.3% query coverage. Goodie AI's March 2026 study reports Wikipedia commands 10.4% citation share specifically in Hotels & Resorts. Neither breaks out per-independent-property citation rates, but the per-domain layer is more measured for hospitality than for any other vertical except legal and financial advisors.

Do travelers actually use AI to plan trips?

Yes, and at the highest documented rates of any vertical. Phocuswright's March 2026 AI Surge report found 56% of US leisure travelers used AI for at least one trip in the past 12 months — up from 43% in late 2025 and 33% in early 2025. Booking.com's Global AI Sentiment Report (July 2025, n=37,325) found 67% have already used AI in some aspect of travel and 89% want to use AI in future travel planning. Phocuswright also reported 51% of AI-using travelers used AI for in-destination recommendations and 95% rated it helpful for in-trip tasks.

What sources does AI cite for hotels?

Per Nokumo: Booking.com 14.5% of all URLs cited and 95.3% query coverage; hotel chain websites 4.3%; independent hotel websites 11.8%; TripAdvisor #2 cited domain; DMOs and tourism boards 3.9%. Top 119 domains = 50% of all citations. Per Goodie AI March 2026, Wikipedia commands 10.4% citation share specifically in Hotels & Resorts.

What's the AI-vs-organic conversion gap for travel?

Hospitality has the strongest available primary data. Adobe Digital Insights tracks travel monthly: bounce rate -45% lower (Feb 2025), time on site +25% longer (May 2025), revenue per visit +80% higher (Feb 2025). The conversion gap moved from -82% in July 2024 to -47% in July 2025 to -14% by March 2026.

Why does Booking.com outrank direct sites in AI citations?

Per Nokumo, Gemini 2.5 had 29.4% OTA dependency (highest of any model); Perplexity had lowest OTA reliance (20.5%) but highest review/UGC (17%). Booking.com's per-property URLs are deeply structured (room types, cancellation policy, breakfast, distances, multilingual reviews) which retrieval pipelines parse well. The asymmetry is not equally distributed across model: English-and-German destinations show less OTA reliance per Nokumo's cross-country comparison; Italian and Slovenian destinations show more.

Do sustainability certifications and trade-press mentions move the dial?

There is no published study measuring exact citation lift from sustainability certifications at the per-property scale. Skift, PhocusWire, HospitalityNet, Travel Weekly, and Hotel News Now appear in cross-vertical citation studies as the canonical hospitality trade-press surface. The 5WPR Haute Residence April 2026 luxury real-estate report found "branded residences capture 78% of AI search recommendations in South Florida's ultra-luxury sector" — niche-specific but adjacent to luxury hospitality.

What should a property or agency do with this on Monday morning?

Treat Booking.com as the primary citation surface, not the secondary one. Complete every Booking.com structured field; build multilingual review presence; treat the OTA listing as the surface most likely to be cited. Pursue at least one sustainability certification. Run per-property prompt monitoring across ChatGPT, Google AI Overviews, Perplexity, and DeepSeek — because the 14.5% Booking dominance is a published average, not your specific property's outcome.

Sources

• Nokumo, AI Hotel Recommendation Study, late 2025 (450 queries × 4 models × 5 countries).
• Goodie AI, Most-Cited Domains Study, released March 2026 (58.6M citations across 31 industries).
• Adobe Digital Insights, Quarterly AI Traffic Reports, October 2024 through March 2026 (1+ trillion US visits; 8M+ travel visits).
• Phocuswright, The AI Surge: Travel's Fastest Behavioral Shift in a Decade, March 2026 (n=1,570 US leisure travelers).
• Booking.com, Global AI Sentiment Report, July 2025 (n=37,325 across 33 markets).
• 5WPR & Haute Residence, 2026 Luxury Real Estate AI Discovery Report, April 23, 2026.
• BrightLocal, Uncovering ChatGPT Search Sources, December 12, 2024.
• Conductor, 2026 AEO/GEO Benchmarks Report, November 13, 2025.
• SOCi, 2026 Local Visibility Index, February 17, 2026.
• Yext Research, AI Citations, User Locations & Query Context, October 9, 2025.

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Last updated April 30, 2026. Author: Cameron Witkowski, Co-Founder, OpenLens. Methodology questions: [email protected].