When a potential traveller asks ChatGPT “What’s the best family-friendly hotel for a week in Spain?”, the brands appearing in the answer can become part of their consideration set. Which sources sit behind those answers?
Peak Ace’s LLM Industry Benchmark analysed a fixed set of 1,000 commercially relevant prompts across 10 industries in Germany during August 2026. Across Gemini, ChatGPT and Google AI Overviews, we measured which brands show up, which source types are retrieved and how brands are spoken about. Here’s what this standardised snapshot reveals for Travel & Hospitality, with a focus on the source mix and its implications for GEO and Digital PR.
Contents
- How we conducted our LLM Industry Benchmark
- AI Visibility for Travel & Hospitality: How does it compare to other industries?
- Which travel and hospitality brands are most visible in AI?
- Which Sources Do LLMs Use for Travel & Hospitality Questions?
- How do travel and hospitality brands become visible in AI?
- The Full Picture Is in the LLM Industry Benchmark
- FAQ: AI Visibility in Travel & Hospitality
How we conducted our LLM Industry Benchmark
The benchmark is built on a defined methodology:
- 1,000 standardised bottom-of-funnel prompts across 10 industries, each with 100 commercially relevant prompts.
- Prompts were split across 10 topic clusters per industry.
- Four intent types were tested: best/top/test winner, comparisons, pricing/where to buy, and criteria/guidance, with 25 prompts per intent in each industry.
- The analysis focused on the German market and German-language prompts during August 2026.
- Gemini, ChatGPT and Google AI Overviews were monitored. Each prompt ran 15 times, five per system.
- Data was sourced from Peec AI exports; 50 brands per industry were monitored, with reporting focused on the Top 20 by visibility.
- The three core brand KPIs are visibility, Share of Voice/SOV and sentiment. Visibility measures how often an entity appears in answers for the prompt set; SOV records its share of voice in the monitored dataset; sentiment measures the tone of answers mentioning an entity on a 0–100 scale. For concentration analysis, SOV shares are separately normalised to 100% within the Top 20.
The source analysis describes retrieval counts and URL types by industry and intent. All results apply to the selected prompts, monitored entities, systems and study period.
For the full methodology, definitions and cross-industry breakdowns, the complete benchmark is available for download.
AI Visibility for Travel & Hospitality: How does it compare to other industries?
In our benchmark, comparison pages lead the Travel & Hospitality source-type lists for recommendations, comparisons and purchasing questions. How-to guides lead for criteria/guidance. These are also the leading formats across all 10 industries.
Here’s how the leading source types compare:
| Intent | Travel & Hospitality: leading source type | All 10 industries: leading source type and retrieval share |
| Best/top/test winner | Comparison | Comparison, 28.31% |
| Comparisons | Comparison | Comparison, 32.65% |
| Criteria/guidance | How-To Guide | How-To Guide, 22.33% |
| Pricing/where to buy | Comparison | Comparison, 22.64% |
The percentages describe the cross-industry retrieval mix, not Travel & Hospitality shares. The industry scorecard recorded 86,235 retrievals. It publishes the order of leading source types, rather than their individual retrieval shares. [2][3]
The useful content distinction is between evaluating options and working out what to choose. Comparisons lead recommendation and purchasing questions; guides lead criteria/guidance. Category pages also rank second for recommendations, guidance and purchasing, making grouped destination and accommodation information a useful part of the content audit.
For additional context, Travel & Hospitality records average visibility of 4.45%, compared with 6.94% across all 10 industries. Its reported average SOV is 3.4%, versus 3.72%, and sentiment is 55.1, versus 54.58. The lower mention rate is not accompanied by a lower sentiment score. Sentiment measures answer tone within the dataset, not the quality of a travel experience.
Its HHI is 692, and its Top-3 Share is 34%. HHI measures concentration: higher values mean SOV is distributed less evenly. The three largest SOV contributors account for 34% of the Top-20 total, leaving 66% across the remaining entities. These concentration figures use normalised SOV shares, separate from the reported average SOV above, and are not market shares.
Which travel and hospitality brands are most visible in AI?
According to Peak Ace’s benchmark for Germany in August 2026, the top three entities by visibility in the Travel & Hospitality prompt set are:
- Booking.com: 10% visibility
- Google Maps: 8% visibility
- TUI: 8% visibility
Their shared advantage is answering different parts of a travel decision. The white paper explains their prominence through their roles in accommodation, location-based orientation and package holidays. Booking.com fits questions about finding accommodation; Google Maps fits questions about where places are and how they relate to a destination; TUI fits questions about choosing a package holiday.
These are not three interchangeable competitors. They represent different ways of helping a traveller choose, locate or book an option. That helps explain why platforms appear alongside a travel provider in the same benchmark: the commercial questions cover more than the selection of an individual hotel.
For travel brands, the practical insight is to separate the decisions. A hotel, a booking platform and a package-holiday provider need different question sets. Assess where your brand fits the traveller’s task, then review the comparisons, category pages and guides retrieved for that task. The combined industry figures are a starting point, not a substitute for analysing your own offer.
Which Sources Do LLMs Use for Travel & Hospitality Questions?
The benchmark analysed which types of content the selected AI systems retrieved when processing Travel & Hospitality prompts.
Note: retrieval records source access, not necessarily a citation or brand mention in the final answer. The published scorecard does not identify leading travel domains or link particular sources to individual brands. The patterns below inform content audits; they do not establish the effect of a specific format or placement.
The source mix varies by intent:
| Intent | Leading benchmark source types, in descending order |
| Best/top/test winner | Comparison, Category Page, Listicle, How-To Guide |
| Comparisons | Comparison, Article, Product Page, Listicle |
| Criteria/guidance | How-To Guide, Category Page, Article, Listicle |
| Pricing/where to buy | Comparison, Category Page, How-To Guide, Listicle |
A few things stand out:
- Comparison pages lead three lists, including recommendations and purchasing questions. Their role extends beyond explicit comparisons between two travel options.
- Category pages rank second in three lists: recommendations, guidance and purchasing. Grouped information features alongside comparisons and practical advice.
- How-to guides lead criteria/guidance and appear in recommendation and purchasing lists. Planning advice complements the evaluation of options.
- Listicles appear in all four lists, but do not lead any of them. Round-ups are part of the mix, not a reason to make every page a “best hotels” list.
- Articles rank second for comparisons, while product pages appear third. Explanatory and offer-specific information both feature when options are evaluated.
What does the source mix suggest?
- Make suitability explicit in comparisons. For a family-holiday question, useful selection content should explain which options fit the traveller’s requirements, not merely present a list of names. Review location, accommodation features and relevant booking conditions.
- Give category pages a clear selection purpose. Category pages rank ahead of listicles for recommendations. Audit destination and accommodation-group pages for useful distinctions between options, rather than treating them only as a route to individual listings.
- Connect planning advice with bookable options. Guides lead guidance questions and also feature in purchasing prompts. Help travellers understand the criteria for their trip, then connect that advice to relevant accommodation or holiday offers.
How do travel and hospitality brands become visible in AI?
The data raises several questions that travel and hospitality marketers should consider:
- Are you visible on the comparison and listicle pages retrieved for relevant questions? Review the actual pages and domains in your own monitoring. Check whether they explain the suitability of your accommodation or travel offer, rather than merely naming it.
- Does your content strategy cover all four intent types? Travel research extends beyond “best hotel” or “best destination” questions. Cover comparisons, pricing and practical guidance alongside recommendations.
- Is your brand represented consistently across the sources that inform answers? Check accommodation details, locations, facilities, inclusions and booking conditions across your website and relevant third-party listings or coverage. Prioritise conflicting or outdated information.
- Are you connecting SEO, content and Digital PR? Use your monitoring to identify relevant comparison and editorial sources for a particular destination, traveller profile or holiday type. Track brand mentions and retrieved sources separately, using a consistent prompt set and reviewing results by intent and system.
The Full Picture Is in the LLM Industry Benchmark
This blog post covers the Travel & Hospitality highlights. The full LLM Industry Benchmark goes further:
- How the source mix differs across all 10 industries.
- How source types shift between recommendations, comparisons, pricing and guidance.
- Visibility, SOV and sentiment for the reported brands.
- How concentrated SOV is within each industry’s Top 20.
- The industry scorecards and complete methodology.
Download the full LLM Industry Benchmark here.
Had a look at our benchmark and looking to improve your travel brand’s presence in AI answers? Get in touch with our team.
FAQ: AI Visibility in Travel & Hospitality
How visible are travel and hospitality brands in ChatGPT and other AI assistants?
Average visibility was 4.45% in the German-market snapshot for August 2026, aggregated across Gemini, ChatGPT and Google AI Overviews. This is not a ChatGPT-only figure.
Which travel and hospitality brands are most visible in AI search?
Booking.com recorded 10% visibility, Google Maps 8% and TUI 8%. They represent accommodation, location-based orientation and package holidays within the commercial prompt set.
What types of content do LLMs use to answer travel questions?
In our benchmark, comparisons led recommendations, comparisons and purchasing questions. How-to guides led criteria/guidance. Listicles appeared among the leading formats for all four intents.
Does AI visibility matter for travel and hospitality brands?
It measures presence in answers to commercial travel questions. Use it alongside traffic, enquiries and bookings to assess how potential travellers encounter and engage with your offers.
What is a GEO strategy for travel brands?
Generative Engine Optimisation combines SEO, content, Digital PR and monitoring to work on presence in AI answers. For travel brands, priorities should follow the traveller’s decision and retrieved sources.
How can travel and hospitality brands improve their AI visibility?
Start with one destination, traveller profile or holiday type. Review retrieved comparisons, category pages and guides against audience questions, correct information gaps, and monitor changes with the same prompt set.
