Hotels & Hospitality GEO Guide

Add this JSON-LD to your hotel's website and you're immediately discoverable by AI search engines:

{
  "@context": "https://schema.org",
  "@type": "Hotel",
  "name": "Hotel Amsterdam Central",
  "url": "https://www.example-hotel.com",
  "telephone": "+31 20 123 4567",
  "email": "reservations@example-hotel.com",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "Prins Hendrikkade 33",
    "addressLocality": "Amsterdam",
    "addressRegion": "North Holland",
    "postalCode": "1012 TM",
    "addressCountry": "NL"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": 52.3787,
    "longitude": 4.9010
  },
  "description": "Luxury 4-star hotel overlooking Amsterdam Central Station with spa, rooftop bar, and canal views.",
  "priceRange": "EUR150-350",
  "starRating": {
    "@type": "Rating",
    "ratingValue": 4.5,
    "bestRating": 5
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": 4.5,
    "reviewCount": 823,
    "bestRating": 5,
    "worstRating": 1
  },
  "checkinTime": "15:00",
  "checkoutTime": "11:00",
  "amenityFeature": [
    {"@type": "Text", "name": "Free WiFi"},
    {"@type": "Text", "name": "Swimming Pool"},
    {"@type": "Text", "name": "Spa"},
    {"@type": "Text", "name": "Restaurant"},
    {"@type": "Text", "name": "Gym"},
    {"@type": "Text", "name": "Parking"}
  ],
  "petsAllowed": true,
  "offers": {
    "@type": "Offer",
    "url": "https://www.example-hotel.com/book",
    "priceCurrency": "EUR",
    "price": "200"
  }
}

Want the full version with location scores, POIs, nearby attractions, and room types? See the complete hotel schema in the examples below.

Users are asking AI engines increasingly specific questions that require both location and property data. Here are real query patterns your hotel needs to answer:

Amenity + Location Searches:

• "Best boutique hotel in Barcelona with rooftop pool and under 200 euros"
• "Family-friendly hotels near Disneyland Paris with kids club"
• "Quiet hotels in Amsterdam city center under 200 euros"
• "Pet-friendly luxury hotels in Berlin with parking"
• "Hotel with spa and wellness center in Zurich"

Logistics Searches:

• "Hotels near Charles de Gaulle Airport with airport shuttle"
• "Walking distance from Sagrada Familia, Barcelona hotels"
• "Amsterdam hotels with metro access to Schiphol"
• "Hotels within 15 minutes of Geneva train station"

Experience Searches:

• "Best rooftop bar hotel in Athens for sunset views"
• "Hotel with great city views in Prague old town"
• "Beachfront hotel in Lisbon with ocean-facing rooms"

Your data must support these queries. That means:

• Amenity details at room level (not just property level)
• Geographic coordinates for distance calculations
• Transport connectivity (metro, airport, train station)
• Nearby attractions with walking times
• Rooms with specific bed types, balcony/view data
• Review counts and sentiment for AI ranking
• Pricing flexibility

Your Hotel schema is the foundation. AI systems read this first to understand what you are, where you are, what you offer, and how good you are.

Hotel Type: LodgingBusiness vs Hotel

Use "@type": "Hotel" for traditional hotels. Use LodgingBusiness only for unusual accommodations (hostels, cabins, houseboats). Most properties are Hotels.

Required Fields

• name: Property identity (e.g., "The Pulitzer Amsterdam")
• address (full PostalAddress): Location matching, distance calculation
• geo (latitude, longitude): Precise positioning for queries like "hotels within 1km"
• description: AI uses this text to match queries, rank relevance, and cite in responses
• aggregateRating: Trust signal, AI ranks higher-rated hotels higher
• offers (price range): Filtering for budget-conscious searches
• amenityFeature: Specific capabilities AI can cite (swimming pool, spa, restaurant, WiFi)
• image: Visual confirmation for users after AI recommendation

Writing Descriptions AI Will Actually Cite

Your description field is crucial. AI systems extract details from this text to answer user queries.

Bad description (generic, vague):

"Beautiful hotel in Amsterdam. Nice rooms. Friendly staff. Great location."

Good description (specific, location-aware, amenity-rich):

"Luxury 5-star hotel occupying a restored 17th century palace on Amsterdam's Prinsengracht canal. 80 rooms with floor-to-floor windows overlooking Amsterdam's oldest waterway. Amenities include Michelin-starred restaurant, spa with sauna and steam room, rooftop terrace with canal views, 24-hour gym, and free WiFi. Located 150 meters from Westermarkt church and 300 meters from Anne Frank House. Walking distance to Jordaan neighborhood galleries and shops. Direct tram access to Central Station (5 minutes) and airport (20 minutes)."

When users ask "family-friendly hotels with spacious rooms and interconnecting doors", or "double rooms with city views under 200 euros", they need room-level data.

Use HotelRoom nested within your Hotel schema via containsPlace.

{
  "@type": "HotelRoom",
  "name": "Deluxe Double Room with Canal View",
  "description": "45 sqm room with king-size bed, floor-to-ceiling windows overlooking Prinsengracht canal.",
  "bed": [
    {
      "@type": "BedDetails",
      "name": "King Size",
      "numberOfBeds": 1
    }
  ],
  "occupancy": {
    "@type": "QuantitativeValue",
    "minValue": 1,
    "maxValue": 2
  },
  "amenityFeature": [
    {"@type": "Text", "name": "Private balcony"},
    {"@type": "Text", "name": "Air conditioning"},
    {"@type": "Text", "name": "Rainfall shower"},
    {"@type": "Text", "name": "Minibar"},
    {"@type": "Text", "name": "Safe"},
    {"@type": "Text", "name": "Free WiFi"}
  ],
  "floorSize": {
    "@type": "QuantitativeValue",
    "value": 45,
    "unitCode": "MTK"
  },
  "offers": {
    "@type": "Offer",
    "priceCurrency": "EUR",
    "price": "280"
  }
}

Create separate HotelRoom entries for each major room category:

• Budget/Standard Rooms: Interior rooms, queen/double beds, shared facilities if applicable
• Deluxe/Superior Rooms: Window/view rooms, premium bedding, enhanced amenities
• Suite Rooms: Separate living areas, premium locations, highest-tier amenities
• Accessible Rooms: Wheelchair accessible, accessibility features listed
• Family Rooms: Multiple beds, interconnecting doors, kids' amenities
• Suite/Penthouse: Luxury living spaces, outdoor terraces

AI systems heavily weight reviews and ratings. A 4.8-star hotel with 2,000 reviews ranks much higher in recommendations than a 5-star hotel with 3 reviews.

Always include aggregateRating at the hotel level:

{
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": 4.6,
    "reviewCount": 1847,
    "bestRating": 5,
    "worstRating": 1
  }
}

Why this matters:

• ratingValue: Raw score (out of 5). AI uses this for ranking.
• reviewCount: Number of reviews. Higher counts = more trusted by AI.
• Both together create a "confidence score" for AI rankings.

Use review array for individual reviews. Include at least your best 10-20 reviews. AI engines pull these snippets when answering "what do people say about this hotel?"

How AI uses ratings:

• Discovery: AI prioritizes high-rated properties in recommendations
• Filtering: User asks for "4-star hotel or better" and AI checks your rating
• Comparison: When showing multiple hotels, AI ranks by rating + review count
• Citation: AI cites "4.6-star hotel with 1,200 reviews" in responses to build user trust
• Sentiment Analysis: AI reads review text to understand guest satisfaction with specific amenities

This is where GEO truly powers AI recommendations. Location enrichment makes your hotel answerable to logistical queries.

Nearby Points of Interest (POIs)

Create additionalProperty entries for nearby attractions. When a user asks "hotels within walking distance of the Louvre", AI needs this data:

{
  "additionalProperty": [
    {
      "@type": "PropertyValue",
      "name": "Nearest Museum",
      "value": "Anne Frank House, 300 meters walking distance (5 minutes)"
    },
    {
      "@type": "PropertyValue",
      "name": "Nearest Public Transport",
      "value": "Westermarkt Tram Stop (lines 13, 14), 150 meters (2 minutes)"
    },
    {
      "@type": "PropertyValue",
      "name": "Nearest Airport",
      "value": "Amsterdam Airport Schiphol, 9 km (express train 20 minutes, bus 45 minutes)"
    }
  ]
}

Location Scores

Structured scores help AI understand your property's neighborhood characteristics:

{
  "additionalProperty": [
    {
      "@type": "PropertyValue",
      "name": "Walkability Score",
      "value": "92/100 - Walker's Paradise. Most errands can be accomplished on foot."
    },
    {
      "@type": "PropertyValue",
      "name": "Transit Score",
      "value": "94/100 - Excellent Public Transportation. Convenient for most trips."
    },
    {
      "@type": "PropertyValue",
      "name": "Nightlife Score",
      "value": "85/100 - Very High. Lots of nearby bars, clubs, restaurants, music venues."
    }
  ]
}

Automating Location Enrichment with GeoEnrich API

Instead of manually entering all this data, use the MapAtlas GeoEnrich API. It automatically pulls nearby attractions, transport links, and location scores based on your coordinates.

JSON-LD is essential, but your website's HTML content structure matters too. AI crawls both.

Your landing page should have H2 headers that match how users search:

• Luxury 5-Star Hotel in Amsterdam City Center
• Rooms with Canal Views
• Family-Friendly Amenities
• Rooftop Bar and Restaurant
• Spa and Wellness Center
• Location: Walking Distance to Anne Frank House and Jordaan
• Guest Reviews: 4.6 Stars from 1,847 Guests

FAQ Section (Critical for AI)

Create FAQ section targeting specific AI query patterns:

• "Is your hotel family-friendly?", answer with specific details
• "How far is your hotel from Amsterdam Airport?", answer with distance and travel time
• "What amenities are included with rooms?", answer with amenity list
• "Do you allow pets?", answer with policy and fees
• "What's your cancellation policy?", answer clearly
• "How can I reach the city center from your hotel?", answer with transport options

Link between your hotel, room, and location content to help AI understand relationships and improve contextual ranking.

Understanding how AI cites hotels helps you optimize your data.

When ChatGPT, Perplexity, or Claude answers "best romantic hotels in Amsterdam with canal views under 250 euros", here's what influences their recommendation:

Data Signals:

• Schema completeness (higher = more trustworthy)
• Review count and rating (higher count = more confident)
• Specific amenities mentioned in schema (luxury linens, king beds, balconies)
• Location specificity (proximity to romantic spots like Anne Frank House)
• Recent freshness (when was data last updated)
• Pricing alignment (does your price range fit the query)

AI systems cite hotels like this:

"The Pulitzer Amsterdam is an excellent choice. This 5-star luxury hotel occupies 25 interconnected 17th-century palaces on the Prinsengracht canal. Rooms feature floor-to-ceiling windows with canal views, high ceilings, and antique furnishings. The hotel has a spa, rooftop bar, and Michelin-recommended restaurant. Guests give it 4.6 stars. Rates start at EUR 280 per night."

That citation comes directly from your schema: description, reviews, amenities, offers/price.

Avoid these to ensure AI can discover and rank your hotel correctly.

1. Missing or Incorrect Coordinates

Coordinates like "52, 4" point to the ocean between Amsterdam and the UK. Use 4+ decimal places: "latitude": 52.3787, "longitude": 4.9010. Incorrect coordinates break distance calculations entirely.

2. No Room-Level Schema

AI can't answer "rooms with balconies" or "family rooms with interconnecting doors" without room-level HotelRoom schema nested via containsPlace.

3. Stock Descriptions

"Beautiful hotel in Amsterdam. Great location. Excellent service." could apply to any hotel. AI can't extract details or match user queries. Be specific: "Luxury 4-star hotel in Amsterdam's Jordaan neighborhood, 300 meters from Anne Frank House."

4. No Nearby Attraction Data

If you don't mention nearby attractions in additionalProperty or description, you miss queries like "hotels within walking distance of museums."

5. Stale Availability and Pricing

Update pricing monthly at minimum. AI thinks you're closed or untrustworthy if pricing is old.

6. No Review Markup

A high starRating without reviewCount is untrustworthy. Always use aggregateRating with both ratingValue and reviewCount.

7. Incomplete Address

Always include postalCode and addressCountry in PostalAddress. Missing fields prevent verification.

Before launching your GEO optimization, validate your schema works.

Tool 1: Google Rich Results Test

Go to search.google.com/test/rich-results, paste your page URL, and look for "Hotel" in valid tags. Check for errors or warnings and review the rich results preview.

Tool 2: AEO Checker

Go to /ai-seo-checker and enter your hotel URL. You'll receive a detailed report on schema completeness, coordinate accuracy, nearby attraction coverage, location enrichment gaps, and suggestions for improvement. Aim for 85%+ schema completeness with 20+ nearby attractions defined.

Tool 3: Test on Actual AI Systems

Ask ChatGPT, Perplexity, and Claude: "best 4-star hotels in Amsterdam with spa under 250 euros." See if your hotel appears and how it's described. If your hotel isn't appearing, you likely have a schema issue: incomplete data, incorrect coordinates, low review count, or missing amenity data that matches the query.

JSON-LD Validation

Use a JSON linter at jsonlint.com. Common errors include missing commas between properties, quotes around numbers (coordinates must be numbers, not strings), and unclosed brackets or braces.

This guide includes three complete, production-ready schema examples:

• hotel-property.json: Full LodgingBusiness/Hotel with location enrichment, room types, ratings
• hotel-room.json: HotelRoom with amenities, pricing, sizing, and reviews
• hotel-event.json: Event schema for hotel conference and event spaces

All files include real coordinate examples (Amsterdam hotels), complete additionalProperty enrichment, nearby attraction examples, location scores, multiple room types, review markup, and pricing/offers. Copy these files, update details to match your property, and deploy to your website.

• Schema.org Hotel
• Schema.org LodgingBusiness
• Schema.org HotelRoom
• Google Structured Data for Hotels
• Google Rich Results Test
• AEO Checker
• MapAtlas GeoEnrich API