AI-Readiness Checklist for Restaurant and Hotel Websites

If you want AI models like ChatGPT, Perplexity, and Google’s AI Overviews to recommend your venue rather than the place down the road your website needs to speak a language those models can read, extract, and trust.

Here’s a full breakdown of the data points, schema requirements, FAQ structures, and technical checks that determine whether you get recommended or ignored.

1. Entity & Identity Data

AI models cross-reference your business details across dozens of sources. Inconsistency creates entity confusion, the model isn’t sure your website, your Google Business Profile and your TripAdvisor listing are all the same place.

  • Business name — legal name, trading name, and any “also known as” variants
  • NAP — street address, town/city, postcode, and country, identical everywhere
  • Phone and email — in crawlable HTML, not embedded in an image
  • Cuisine type or accommodation category — stated explicitly in body copy (e.g. “fine dining Italian restaurant” or “boutique country house hotel”)
  • Opening hours — every service: lunch, dinner, bar, breakfast, check-in/out; include seasonal variations and holiday closures
  • Price range — £/££/£££ or an explicit average spend per head
  • Year established — “family-run since 1987” differentiates you from chains
  • Covers or room count — helps AI answer capacity queries from event planners
  • Parking, transport, and access notes — name the station, the car park, the bus route; critical for proximity searches

2. Structured Data (Schema.org)

Schema is the highest-impact technical action you can take. It tells AI crawlers exactly what your business is, what it offers, and where it sits.

  • Restaurant or LodgingBusiness schema on your homepage and key landing pages (use JSON-LD)
  • servesCuisine, priceRange, and currenciesAccepted populated
  • hasMenu linking to a crawlable HTML menu page — not a PDF
  • aggregateRating with reviewCount and ratingValue
  • amenityFeature array listing every key amenity (dog friendly, private dining, EV charging, accessible rooms, etc.)
  • BreadcrumbList on all interior pages
  • FAQPage schema on every FAQ block — this is the primary mechanism for injecting your answers into AI outputs
  • Event schema for recurring events (quiz nights, tasting menus, live music)
  • SpeakableSpecification on your most concise, factual paragraphs
  • geo coordinates (latitude/longitude) inside your LocalBusiness markup
  • sameAs array pointing to all authoritative profiles — Google, TripAdvisor, Instagram, Facebook

3. Menu & Offering Data

PDFs and image-based menus are effectively invisible to AI crawlers.

  • Full menus in HTML — starters, mains, desserts, drinks, all prices included
  • Dietary tags on every dish — vegan, vegetarian, GF, dairy-free, nut-free; one of the most common AI-assisted restaurant queries
  • Allergen information page — all 14 major allergens by dish (also a UK legal requirement)
  • Tasting and set menus — price and course count
  • Seasonal update cadence noted — “menu updated quarterly” tells AI your data is fresh

For hotels:

  • Every room type — bed configuration, max occupancy, key features, its own descriptive paragraph
  • Board options — breakfast/half-board/full-board with prices
  • Private dining and meeting rooms — capacity, AV facilities, deposit terms

4. FAQ Structures

FAQs are your primary injection point into AI outputs. Write them in the exact conversational language someone would use with ChatGPT or Google AI. Each answer should be 40–120 words — complete enough to be quoted, short enough to be extracted cleanly.

Use these as literal headings on your FAQ page, with FAQPage schema applied:

  • Is [venue] dog friendly? — specific details: which areas, water bowls, any restrictions
  • Does [venue] have parking? — number of spaces, charge, nearest alternatives
  • Is [venue] suitable for a birthday / anniversary / celebration? — what’s included
  • Does [venue] cater for vegans / vegetarians / coeliacs? — answer with menu examples, not just “yes”
  • What is the dress code?
  • Can I book a private dining room / exclusive hire? — include capacity, deposit, and contact
  • Is [venue] accessible / wheelchair friendly? — step-free access, accessible toilet, hearing loop, blue badge parking
  • How far is [venue] from [nearest station / town / attraction]? — exact distances and travel times (“a 4-minute walk from Bury St Edmunds station”)
  • What time does [venue] open and close? — by service, including last orders
  • Does [venue] accept walk-ins or is booking required?
  • Does [venue] have a children’s menu / highchairs?
  • Is [venue] good for a business lunch / corporate event?
  • What is the cancellation policy?
  • Does [venue] have WiFi? — hotels: state speed and whether it’s free
  • Is [venue] near [landmark]? — name every nearby point of interest; AI clusters recommendations geographically

5. Unique Signals & Differentiators

Vague copy — “great atmosphere”, “friendly staff” — is invisible to AI models. Specific, factual claims are extractable and quotable.

  • Named awards and press mentions with year — “AA Rosette holder since 2019”, “Named Best Country Pub by the Sunday Times 2023”
  • Chef or owner bio with named credentials and previous roles
  • Specific provenance — “beef from a farm 4 miles away” works; “locally sourced” doesn’t
  • Sustainability credentials — named and measurable (“solar panels covering 60% of energy use”, “certified B Corp”)
  • Heritage or architecture details — Grade II listed, converted 17th-century coaching inn; strong signal for travel queries
  • Signature dishes or cocktails — named with descriptions; AI answers “what is [venue] known for?” with this
  • Michelin recognition, rosettes, or starred status — include year awarded and current status
  • Unusual amenities — wood-fired oven, rooftop terrace, natural wine list, farm on-site; used for niche queries

6. Review & Reputation Signals

  • Google Business Profile — fully completed, verified, photos uploaded; treated by AI as a primary entity source
  • TripAdvisor listing — claimed and complete
  • Average rating and review count — visible in on-page copy or schema (“rated 4.8/5 from over 600 Google reviews”)
  • Respond to all reviews — AI infers engagement quality from response rate
  • Testimonials — named attribution (“Jane, London”) is more extractable than anonymous
  • Press and media coverage page — with links to original articles; external links are authority signals

7. Technical & Crawlability

Check your robots.txt first

A large number of hospitality sites — especially WordPress installs with security plugins like Wordfence or iThemes — silently block AI crawlers. Check yourdomain.com/robots.txt. If you see Disallow: / under any of these agents, you’re invisible regardless of how good your content is:

User-Agent: GPTBot
User-Agent: ClaudeBot
User-Agent: Google-Extended
User-Agent: PerplexityBot

A clean file looks like this — Disallow: with nothing after it means nothing is blocked:

User-Agent: *
Disallow:
Sitemap: https://yourdomain.com/sitemap_index.xml

Everything else

  • Page speed under 3 seconds on mobile (use PageSpeed Insights)
  • Canonical tags correctly set — no duplicate content
  • XML sitemap submitted to Google Search Console and kept current
  • Descriptive alt text on all images, including food and room photography
  • Open Graph and Twitter Card meta tags on all key pages
  • HTTPS site-wide, no mixed content warnings
  • No interstitials or pop-ups blocking content on load
  • Booking widget embedded on-page (not a redirect-only link to a third-party)

Priority Order

If you’re starting from scratch, work through in this order:

  1. Fix robots.txt if AI crawlers are blocked
  2. Add FAQPage schema with complete Q&A content
  3. Convert menus to HTML with dietary tags and allergen info
  4. Add Restaurant/LodgingBusiness JSON-LD with all properties
  5. Complete and verify Google Business Profile
  6. Add specificity to your copy — named suppliers, named awards, exact distances
  7. Build out the FAQ page using the conversational questions above
  8. Add review counts and ratings to on-page copy and schema

The venues AI recommends aren’t necessarily the best — they’re the ones that have given AI models the most complete, consistent, and specific data to work with.