Schema markup: how AI systems know what your business is.
Without a schema type declaration, AI systems cannot classify your business with confidence. A hotel without LodgingBusiness schema is indistinguishable from a generic webpage. A restaurant without Restaurant schema cannot surface its cuisine, menu, or reservation system in AI-generated recommendations. One technical layer. Multiple verticals. No generalism.
The audit identifies whether this service is needed for your site.
AI systems are reading your site. They just do not know what it is.
Schema markup is structured data embedded in a page HTML that explicitly tells AI systems, search engines, and knowledge graphs what a business is, what it offers, where it is located, and how to contact it. Without it, AI systems must infer this from unstructured text - and inference is less reliable, less consistent, and less likely to result in a recommendation.
The correct schema type is not generic. A hotel requires LodgingBusiness or Hotel schema - not generic LocalBusiness. A restaurant requires Restaurant schema with servesCuisine, hasMenu, and acceptsReservations. A law firm requires LegalService with areaServed and knowsAbout. Getting the type wrong is nearly as bad as having no schema at all.
In practice, small business sites usually fall into one of three buckets: no schema at all, generic plugin-generated schema, or partially completed markup that omits important nested properties. All three make AI classification less reliable than it should be.
increase in AI citations when sites implement schema markup and FAQ blocks
Category-specific schema, fully implemented.
The right @type for the specific business: LodgingBusiness, Restaurant, SpaOrBeautyParlor, Physician, LegalService, or TouristAttraction - not a generic fallback.
Universal: name, url, telephone, address (nested PostalAddress), geo (nested GeoCoordinates), image array, openingHoursSpecification. Category-specific: checkinTime/checkoutTime, servesCuisine/hasMenu, isAcceptingNewPatients, areaServed.
PostalAddress and GeoCoordinates as properly nested sub-objects - not flat text strings that fail validation.
Google Maps URL, category-relevant review platforms, and official social profiles.
Accurate ratingValue, reviewCount, and ratingCount matching live review data.
Category-specific questions that reflect actual customer queries.
Navigation path schema for improved AI understanding of site structure.
Service, Offer, OfferCatalog, FAQPage, and WebPage schema added where they match the page purpose.
{
"@context": "https://schema.org",
"@type": "LodgingBusiness",
"name": "The Grove Inn",
"url": "https://thegroveinn.com",
"telephone": "+1-828-555-0147",
"address": {
"@type": "PostalAddress",
"streetAddress": "142 River Street",
"addressLocality": "Asheville",
"addressRegion": "NC",
"postalCode": "28801",
"addressCountry": "US"
},
"geo": {
"@type": "GeoCoordinates",
"latitude": 35.5951,
"longitude": -82.5515
},
"checkinTime": "15: 00",
"checkoutTime": "11: 00",
"numberOfRooms": 18,
"priceRange": "$$",
"sameAs": [
"https://maps.google.com/?cid=...",
"https://www.tripadvisor.com/Hotel_Review-..."
],
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.8",
"reviewCount": "312"
}
}What this service does not include.
- Content writing or rewriting of any page
- Designing or updating the visual appearance of any page
- Adding new pages to the website
- Social media profile creation or updates
- Google Business Profile management
- Review solicitation or management
- Any work requiring ongoing content production
You can check this yourself.
Go to search.google.com/test/rich-results. Paste your website URL. If "No items detected" appears, you have no schema. If a schema type appears, click it to see which required properties are missing. After VERIS implements, the same test should show your business type passing with green checkmarks.
Step 1: Paste your URL. Step 2: Click Test URL. Look for your business type with green checkmarks. "No items detected" = no schema.
Common questions about schema markup.
LocalBusiness is a generic schema type. LodgingBusiness is a specific subtype that includes hotel-specific properties like checkinTime, checkoutTime, numberOfRooms, and amenityFeature. AI systems prefer specific subtypes because they signal exactly what the business is and enable rich result types that generic LocalBusiness cannot produce.
Every CMS supports schema markup - it is injected as a JSON-LD script tag in the page HTML head section. WordPress, Squarespace, Wix, Webflow, and custom-coded sites all support this. The method varies by CMS, which affects the time required, but no CMS prevents it.
Schema markup is the infrastructure that makes your business classifiable by AI systems. The implementation is what VERIS delivers. Visibility changes depend on when platforms revisit and trust the updated structure.
Incorrect schema (wrong type, missing required properties, mismatched aggregateRating) is identified in the audit and corrected in the implementation. Sometimes a bad schema implementation is worse than none - Google can flag inaccurate data and reduce trust in the entity.
Schema should be updated whenever the business changes - new hours, updated services, room additions, menu changes, staff changes. This is why the monthly maintenance retainer exists: to keep the schema current as the business evolves.
The primary business entity schema lives on the homepage. Service or product pages benefit from Service, MenuItem, or Event schema as applicable. FAQ schema should appear on any page with question-and-answer content. BreadcrumbList belongs on all non-homepage pages.
Find out if your schema is correct - or absent.
The audit checks your schema type, all required properties, and validates against Google's Rich Results Test. Free.