Why Hospitality Brands Disappear in AI Search

The number that changed how I think about digital marketing: 97%.

That’s how often hospitality brands get cited when someone types their name directly into an AI engine (ChatGPT, Perplexity, Gemini, Claude). If a traveler knows who you are and asks about you by name, the AI will tell them about you almost without fail.

Here’s the other number: 10-15%.

That’s how often those same brands surface when someone asks a trip-planning question: “Where should I stay in [destination]?” or “I’m planning a family vacation to [city] — what are the best places to book?”

We’re calling it the discovery funnel cliff.

What we tested

Earlier this year, we ran what we believe is the first AEO/GEO benchmark for hospitality operators. AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) refer to how well a brand surfaces in AI-generated answers, not just traditional search results.

We tested five vacation rental operators across four AI engines with live web search enabled: ChatGPT (GPT-5), Perplexity, Gemini, and Claude. 40 prompts per brand, 160 total responses, with full methodology published openly.

The findings don’t stay within vacation rentals. The same AI engines answer questions about hotels, resorts, and any hospitality property. The same dynamics are at play.

The funnel breakdown

Brand-name queries are a solved problem. An AI engine that can access the web will tell a user about your property if they already know to ask about you. Branded queries averaged 97% citation rates across every brand we tested.

Everything up-funnel is a different story:

• Destination discovery (“best places to book in [city]”): 30-40% average
• Direct-booking intent (“where can I book directly, not through Airbnb”): 40%
• Trip planning (“I’m planning a trip — where should we stay?”): 10-15%
• Listicle queries (“top boutique hotels in [destination]”): 10-15%

The prompts producing 10-15% citation rates are exactly where new guests make their first decision. They haven’t heard of you yet. They ask an AI where to stay. In most cases, the AI responds with Airbnb, Booking.com, Expedia, or whichever OTA has the deepest content footprint on the web.

Regional operators have a structural edge

One finding that surprised us: regional operators consistently outperformed national brands and marketplaces on destination-specific queries.

A property manager who has been the recognized name for beach rentals in a specific market for 20 years surfaces more reliably in AI answers than a national aggregator covering that same geography.

The reason is straightforward. AI engines learn which brand is the authority for a given destination from the content they’re trained on. A brand with deep, location-anchored content earns that authority signal. A national platform listing thousands of destinations earns it for none of them in particular.

For independent hotels and regional operators, this is a real advantage. The question is whether to capture it before national chains start optimizing specifically for it.

What operators should actually measure

Most hospitality operators are tracking branded performance without realizing it. Type your hotel name into Google and you’ll see your reviews, your website, your TripAdvisor listing. That’s reassuring, but it doesn’t measure your discoverability to guests who don’t know you yet.

The more useful question: if a traveler asks an AI to suggest where to stay in your destination, do you appear? Do you appear when the OTAs aren’t named? Do you appear at the top?

Getting there requires the same fundamentals that have always driven search visibility: authoritative content, structured data, external citations. The difference is the distribution layer. Most operators haven’t audited their presence on it yet.

Full study and methodology

The complete benchmark, including per-engine breakdown, prompt set, and content strategy implications, is at: craftedstays.co/vacation-rental-seo/

Gil Chan is Founder of CraftedStays, a direct booking platform for property managers. He spent 15 years in Silicon Valley e-commerce as a product director, working with platforms including Shopify, Shippo, and Narvar, and brands including Patagonia, Sephora, and Nordstrom.