Structured Data for AI Recommendations: Examples by Industry

When someone asks an AI assistant for a recommendation, it looks for businesses whose facts clearly match the request: the right location, price range, features or speciality. Structured data helps make those facts unambiguous. Which data matters most depends on your industry, so it pays to prioritise the facts buyers in your sector actually ask about.

Restaurants and cafés

Typical prompts: “vegan-friendly brunch in Lisbon”, “quiet restaurant for a business dinner near Gare de Lyon”.

• Restaurant markup with address, hours, price range and cuisine.
• A menu page in plain text, not only a PDF or photo.
• Consistent details on Google Business Profile, TripAdvisor and local guides, which assistants often draw on.

Clinics and healthcare practices

Typical prompts: “dentist in Denver open Saturdays”, “physio who treats running injuries in Manchester”.

• A specific type such as Dentist or Physician, with hours and location per clinic.
• Practitioner pages with qualifications, written clearly on the page.
• Accurate listings on the health directories used in your country.

Online shops

Typical prompts: “waterproof hiking boots under €150 with wide fit”, “organic baby clothes that ship to Belgium”.

• Product markup with price, availability, brand, size and material.
• Shipping and returns information on the page and in your merchant feed.
• Reviews shown on product pages, from real customers. Our guide for e-commerce brands covers shopping assistants.

Software and SaaS

Typical prompts: “CRM for a 10-person agency”, “invoicing tool that integrates with Stripe”.

• SoftwareApplication markup with category, operating system and pricing where public.
• Clear feature and integration pages in plain HTML.
• Up-to-date profiles on G2, Capterra and similar review sites, which AI tools frequently reference.

Professional services

Typical prompts: “family lawyer in Lyon who speaks English”, “accountant for crypto tax in Berlin”.

• LegalService, AccountingService or ProfessionalService markup, with areas served.
• Person markup for partners or advisers with their specialities.
• Languages spoken and specialities stated clearly in text, not only in a logo or badge.

Home and trade services

Typical prompts: “emergency plumber in Leeds”, “solar installer near Toulouse with good reviews”.

• A specific LocalBusiness type with service area.
• Separate pages for each main service.
• Consistent listings on trade directories and review platforms.

The common thread

In every industry, the facts that drive recommendations are location, speciality, price and trust signals. Structured data labels the first three. Trust comes from reviews and mentions you earn elsewhere. For a full audit of your markup, use our schema audit checklist.

Hotels and travel

Typical prompts: “pet-friendly hotel near the beach in Nice”, “family guesthouse in the Alps with parking”.

• Hotel or LodgingBusiness markup with address, amenities and check-in times.
• Clear amenity lists in text: parking, pets, accessibility, breakfast.
• Consistent details on booking platforms and travel review sites, which assistants often draw on for this kind of question.

Education and training

Typical prompts: “weekend coding bootcamp in Berlin”, “online French course for business beginners”.

• Course markup with provider, description and delivery mode.
• Clear pages stating level, duration, language and price.
• Listings on the course directories and comparison sites students actually use.

Whatever your sector, start with the three or four facts buyers mention most often in their questions, and make sure those facts are stated in plain text on your site and marked up correctly.

How Keboost helps

Keboost tracks the recommendation prompts buyers in your industry ask across AI assistants, shows which competitors appear, and creates focused content to improve your chances of being included. Run a free AI visibility check to see the prompts that matter in your sector.