Travellers are asking AI where to stay. Your hotel is not in the answer.

Why are travellers asking AI where to stay instead of using booking sites?

The way people plan trips has fundamentally changed. Instead of scrolling through pages of listings on Booking.com or Expedia, travellers now ask AI a single question and expect a curated shortlist. AI platforms pull their recommendations from structured data, not from OTA listings or advertising spend. Hotels without schema markup are excluded from these conversations entirely.

Think about how you would plan a weekend away right now. Five years ago, you might have opened a booking platform, set your dates and filters, and scrolled through 200 results sorted by price. Today, more and more people simply ask: "Where should I stay near Manchester city centre for a weekend break?" They want a trusted recommendation, not a catalogue.

ChatGPT, Perplexity and Google AI Overviews are answering these questions millions of times a day. The hotels they recommend are not chosen by advertising budget or commission rate. They are chosen because AI can read their structured data and confirm they match the query. Location, amenities, room types, ratings, check-in times - all verified through schema markup.

For independent hotels especially, this is a seismic shift. The playing field between a 20-room boutique property and a global chain comes down to who has better structured data on their own website. And right now, most independents have none at all.

What accommodation queries are people asking AI platforms?

The queries travellers put to AI are conversational and specific. They go far beyond "hotels in Manchester". Here are the categories driving real bookings right now:

• "Where should I stay for a weekend break in Manchester?" - The classic leisure query. AI recommends hotels with rich amenity data, good ratings and a central location. Without LodgingBusiness schema, your hotel is not part of the answer.
• "Find a hotel near the AO Arena for a concert this Saturday" - Event-driven searches are surging. AI needs your areaServed and proximity data in structured format to match you to venue-based queries.
• "Business hotel in Salford with conference facilities and free WiFi" - Corporate travellers ask very specific questions. Each amenity they mention needs to exist as a distinct amenityFeature in your schema for AI to confirm you offer it.
• "Family-friendly hotel with pool and parking near Manchester" - Family travel queries stack multiple requirements. AI checks each one against your structured data. Miss one amenity from your schema and you are out of the running.
• "Dog-friendly boutique hotel in Greater Manchester" - Niche queries are where independent hotels win. But only if the niche features are in your schema. "Pets allowed" as an amenityFeature is what makes this work.

Every one of these queries represents a traveller ready to book. They are not browsing. They want a recommendation they can trust and act on immediately. The hotels that appear in these AI responses capture bookings that never reach a traditional search results page or OTA platform.

Which schema types does a hotel need?

Most hotel websites were built with visual appeal in mind - beautiful photography, smooth booking widgets, and perhaps some basic SEO. That is not enough for AI search in 2026. AI platforms need machine-readable structured data that describes every aspect of your property in detail.

How do amenities and room types translate into AI search visibility?

Every amenity and room type on your website that exists only as text or an icon on a visual page is invisible to AI. Structured data turns those features into machine-readable facts that AI platforms can match directly against traveller queries. A swimming pool mentioned in a paragraph does nothing. A swimming pool listed as an amenityFeature in your schema answers the query "hotel with pool near Manchester" automatically.

This is where hotels have a massive advantage over most local businesses. A plumber has a handful of services. A hotel has dozens of individual amenities, room configurations, dining options, and facilities - each one a potential match for a specific traveller query.

Consider the specificity of real accommodation searches:

• Room types: Standard double, king suite, family room, accessible room - each should be a separate structured entity with bed configuration, occupancy limits, square footage and features.
• Dining: On-site restaurant, bar, room service, breakfast included - each as a distinct Service with its own hours and description.
• Facilities: Pool, gym, spa, sauna, business centre, meeting rooms - each as an amenityFeature. AI checks these one by one against the traveller's requirements.
• Practical amenities: Free WiFi, parking, EV charging, luggage storage, airport shuttle - the details that close a booking decision. If they are not in your schema, AI cannot confirm you offer them.

The more granular your structured data, the more specific queries your hotel can match. A competitor with generic LodgingBusiness schema might match "hotel in Manchester". But a property with full amenityFeature markup matches "dog-friendly hotel with EV charging and pool near Manchester city centre" - a far more qualified, ready-to-book traveller.

Can independent hotels compete with chains and OTAs in AI search?

Yes - and this is the single biggest opportunity AI search has created for independent hotels in a decade. When a traveller asks AI where to stay, the AI does not default to Marriott or Booking.com. It looks for the most complete, structured data source that matches the query. If your own website has richer schema than the OTA listing for your property, AI can cite your direct site instead.

For years, independent hotels have been trapped in a cycle. You pay OTAs 15 to 20 percent commission on every booking because they own the search visibility. Your direct website exists, but travellers find you through Booking.com first and book there because it ranks higher.

AI search breaks that pattern. When someone asks Perplexity for a boutique hotel recommendation, it does not show an OTA page. It recommends a specific hotel, often linking to the hotel's own website if that site has the best structured data. No commission. No intermediary. A direct booking driven entirely by the quality of your schema markup.

The direct booking opportunity

The numbers are straightforward. If your hotel averages 100 per night and an OTA takes 18 percent commission, every OTA booking costs you 18 pounds. Ten AI-driven direct bookings per month saves you 180 pounds - and that number grows as AI search adoption accelerates.

Chain hotels have dedicated digital teams implementing schema across hundreds of properties. But they are working with templated, generic data. An independent hotel can have richer, more detailed structured data about its specific character, unique amenities and local knowledge than any chain template can match. That specificity is exactly what AI rewards.

What does schema markup cost for a hotel?

We start with a free AI Visibility Snapshot. You receive a scored report showing exactly where your hotel stands in AI search, which schema you are missing, what your local competitors have implemented, and how OTA listings for your property compare to your own website's structured data.

From there, a full site audit costs £49. Schema implementation starts from £295, covering your homepage, room pages, amenities, restaurant, conference facilities and contact page. Monthly monitoring to catch schema errors before they cost you bookings starts from £79 per month, with no lock-in contracts.

For context: the commission saved on a single direct booking that bypasses an OTA can cover the cost of a full schema implementation. The question is not whether you can afford it. It is how many direct bookings you are losing every week because AI cannot read your website.