LSD
▌ GlossaryGlossary / Schema markup

Schema markup

Also: Structured data · JSON-LD · Schema.org markup

Schema markup (also called structured data or JSON-LD) is a set of standardized tags that label your page's content so search engines and large language models can parse it as structured data — business hours, ratings, prices, FAQs, articles — instead of inferring from raw HTML.

Technical SEO · 4 min read

Try it · free

Fill in your business details. The JSON-LD on the right updates live and is ready to paste into the `<head>` of your page.

LocalBusiness JSON-LD

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "Joe's Pizza Brooklyn",
  "url": "https://joespizza.com",
  "telephone": "+1-718-555-0142",
  "priceRange": "$$",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "124 Fulton St",
    "addressLocality": "Brooklyn",
    "addressRegion": "NY",
    "postalCode": "11201",
    "addressCountry": "US"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.8",
    "reviewCount": "542"
  }
}
</script>

Validate after pasting. Use Google's Rich Results Test to confirm the markup is valid before deploying.

Open Rich Results Test

What schema markup is

Schema.org is the open vocabulary, maintained jointly by Google, Bing, Yahoo, and Yandex, that defines hundreds of entity types — LocalBusiness, Restaurant, Product, FAQPage, Article, Event, and so on. JSON-LD is the recommended format for delivering schema markup: a single <script type="application/ld+json"> block in the page <head> that names the entity and its properties.

When Google's crawler hits a page with valid JSON-LD, it pulls the data into its Knowledge Graph and uses it for rich results, AI Overviews, Local Pack snippets, and any other surface that displays structured business information.

Why schema markup matters more in 2026

In the 10-blue-link era, schema markup was a *nice-to-have* — it powered rich snippets and FAQ accordions, but you could rank without it. In the AI-search era, schema markup has become a *load-bearing* signal. AI Overviews, AI Mode, and LLM citations all preferentially draw from sources that publish clean structured data, because LLMs can parse it without ambiguity.

A page with well-structured schema is roughly twice as likely to be cited in an AI answer as the same page without it, according to multiple 2025 studies. The work is the same; the surfaces it influences have multiplied.

LocalBusiness schema — the essential type

For any local business, the LocalBusiness type (or a more specific subtype like Restaurant, Dentist, Plumber) is the foundational schema. Required properties for full rich-result eligibility:

  • name, url, telephone
  • address (with PostalAddress sub-type: street, city, region, postal code, country)
  • geo (latitude + longitude)
  • openingHoursSpecification (day + open/close times)
  • priceRange
  • aggregateRating (rating value + review count)

Google's Rich Results Test validates the markup. Use the JSON-LD generator above to produce a baseline, then extend with the optional properties Google's docs reference.

JSON-LD vs Microdata vs RDFa

Three formats exist for delivering schema. JSON-LD is the format Google recommends and the one virtually all modern sites use — clean separation from HTML, straightforward to update, supported by every crawler.

Microdata embeds the data inline as HTML attributes (itemprop, itemscope). It works but pollutes the HTML and is harder to update programmatically. RDFa is similar to Microdata but uses different attributes. Both are legacy formats.

For any new implementation, use JSON-LD in the <head>. Don't mix formats — Google will parse them all but consistency matters for debugging.

Schema markup in the agent era

An agent generating content for a multi-location business needs schema markup at every published URL. Modern workflows automate this: the agent fetches the business profile via the Google Business Profile API, pulls reviews via the Google Reviews API, generates LocalBusiness + AggregateRating + Review markup, and ships it as part of the page's static metadata.

The markup itself is mostly mechanical. The judgment calls — which subtype, which properties to include, whether to add Service or Product schema in addition — are where the agent earns its keep.

Related terms

Glossary

Knowledge Graph

Google's structured database that consumes schema markup.

Glossary

Rich results

Schema-powered visual enhancements in the SERP.

Glossary

AI Overview

AI surface that preferentially cites well-structured pages.

Glossary

Topical authority

Earned over time; schema accelerates how it's recognized.

Related APIs

API

Google Business Profile API

Pull the data you'll feed into LocalBusiness schema.

API

Google Reviews API

Pull aggregate-rating + individual reviews to mark up programmatically.

FAQ

Does schema markup directly improve rankings?+
Indirectly. Schema doesn't add ranking weight on its own, but it unlocks rich results, increases CTR, makes pages eligible for AI Overview citations, and clarifies your content for LLMs — all of which feed measurable ranking and visibility outcomes.
Which schema types should every local business have?+
At minimum: LocalBusiness (or a subtype like Restaurant, Dentist), PostalAddress, GeoCoordinates, OpeningHoursSpecification, and AggregateRating. Add FAQPage if the page has Q&A content, Service if it lists services, and Product for e-commerce.
How do I know if my schema is working?+
Validate with Google's Rich Results Test for syntactic correctness, then check Google Search Console's *Enhancements* section to confirm rich-result eligibility 1-2 weeks after deployment.
Can agents generate schema markup automatically?+
Yes — this is one of the highest-leverage agent workflows. An agent connected to the Google Business Profile API can pull all needed data, generate complete LocalBusiness JSON-LD, and update it any time the underlying data changes.
Does AI search read schema markup?+
Yes — and weights it. LLMs prefer structured data because it eliminates parsing ambiguity. Pages with valid schema markup are cited more frequently in AI Overviews, ChatGPT responses, and Perplexity answers than equivalent unstructured pages.

Want this at API scale?

Pull NAP, hours, categories, and aggregate-rating data — the inputs your LocalBusiness schema needs.

See Google Business Profile API