Make Lemonade · Luxury Hospitality
AI Visibility for Luxury Hotels
When guests ask AI to recommend a luxury hotel, most properties are not in the answer.
Here is why, and what to do about it.
The problem
The consideration set is forming before your website is visited.
Before a guest contacts your property, before they visit your website, before they speak to a travel agent, many are now asking AI. They ask open questions: “Where should I stay for a honeymoon in Sardinia?” or “What are the best small luxury hotels in Japan?”
AI does not send these guests to a search results page. It gives them an answer. If your property is not in that answer, the guest may never know you exist. The shortlist is formed. The research begins. And you were never in it.
Paid search does not solve this. PR alone does not solve this. AI visibility requires a specific approach to how your brand is structured, cited, and described across the web.
Three specific problems
Luxury hospitality has a specific AI visibility problem.
Generic digital marketing advice does not address it. It has three parts.
01
OTA dominance in AI answers
When AI systems are asked to recommend hotels, they draw heavily on OTA sources: Booking.com, Expedia, TripAdvisor, Hotels.com. For many luxury properties, the OTA listing is what AI cites, not the hotel’s own website. The brand story, the positioning, and the distinctive voice you have spent years building is bypassed entirely.
02
Brand versus property confusion
AI systems often struggle to distinguish between a hotel brand and its individual properties. A group with six properties may find that AI recommends the brand confidently but fails to surface specific properties for location-based queries, or cites individual properties with no connection to the wider brand.
03
Publication authority gaps
Not all press coverage carries equal weight with AI systems. Some prestigious consumer titles have minimal AI citation footprint. Meanwhile, certain travel publications are cited repeatedly by ChatGPT, Claude, Perplexity, and Gemini. Most luxury hotels are being placed in the wrong publications for AI visibility, not because the PR is poor, but because no one has mapped which titles AI actually trusts.
What we work on
Five areas that determine AI visibility for hotels.
Improving AI visibility for a luxury hotel or travel brand requires work across five areas. Each addresses a different reason why properties are excluded from AI-generated recommendations.
Website content structure
AI systems extract specific, structured facts from websites: room counts, amenity lists, location details, award history. Properties with narrative-heavy websites and minimal structured content are frequently passed over. Restructuring key pages to lead with extractable facts, while preserving brand voice, is the foundation of any AI visibility programme.
Schema markup
Schema markup is structured data that tells AI systems exactly what a property is, where it is, what it offers, and how it is categorised. Hotel schema, restaurant schema, room schema, and award schema all contribute to AI parsability. Most luxury hotel websites have incomplete or missing schema. This is one of the most directly addressable causes of AI exclusion.
Publication and citation strategy
For luxury travel, knowing which specific publications are cited by AI for relevant queries is the difference between PR that builds AI visibility and PR that does not. This requires testing, not assumptions. Our work maps exactly which titles carry AI citation weight for your category and location, so coverage is targeted at the sources that move the needle.
OTA and third-party listing accuracy
Since AI frequently cites OTA listings, the accuracy and completeness of those listings matters directly to AI visibility. Incomplete descriptions, outdated amenity lists, and inconsistent property names across platforms all reduce AI confidence in recommending a property. Auditing and correcting third-party listings is a core part of any hospitality AI visibility programme.
Visibility testing and measurement
AI visibility cannot be inferred from Google rankings. It requires direct testing: running the queries your target guests would use across ChatGPT, Claude, Perplexity, and Gemini, and tracking whether your property appears, how it is described, and how it compares to competitors. An AI Visibility Snapshot is where that process starts.
Common questions
Frequently asked questions
Getting a hotel to appear in AI recommendations requires structured website content, complete schema markup, accurate third-party listings, and coverage in publications that AI systems trust and cite. AI visibility is built across several months through consistent optimisation of these signals. An AI Visibility Snapshot gives you a clear picture of where your property currently stands and where the gaps are.
The most common reasons are: your competitors have better-structured website content that AI can extract and cite, they are featured in publications that carry more AI citation weight for your category, their third-party listings are more complete and consistent, or they have accumulated more third-party mentions over time. Each of these is addressable with the right strategy.
Yes, but only if the PR targets the right publications. AI systems do not weight publications equally. Some titles that are prestigious in traditional PR terms have minimal AI citation footprint. Effective AI visibility strategy maps which publications carry genuine weight for your sector and location, so PR investment is directed at the sources that actually influence AI recommendations.
Traditional SEO optimises a hotel website to rank in Google search results for specific keywords. AI visibility optimises how AI systems understand, describe, and recommend a property in conversational responses. The signals are different: AI systems weight third-party citations, entity clarity, and structured data more heavily than keyword density or backlink volume. A strong SEO foundation supports AI visibility but does not guarantee it.
Technical fixes such as schema markup and content restructuring can improve AI parsability within weeks. Building the third-party citation profile that AI systems use to determine credibility takes longer, typically three to six months of consistent activity. Meaningful improvement in AI recommendation frequency is usually visible within a quarter for properties starting from a low baseline.
Ready to start?
Find out where your property stands with AI.
The AI Visibility Snapshot gives you a clear, plain-language picture of how AI systems currently see, describe, and recommend your property, and where the gaps are. No jargon. No obligation to go further.