AngryturtleWhat Is Local Schema Markup?
Local schema markup is structured data, written in Schema.org vocabulary, added to a business's website to explicitly tell search engines — and increasingly, AI systems — what the business is, where it is, what it does, and a set of other structured attributes. It's usually written as JSON-LD and placed in the <head> or <body> of the relevant page.
The core schema type for local businesses is LocalBusiness, along with its more specific subtypes: MedicalOrganization, Restaurant, LodgingBusiness, LegalService, and dozens more depending on category. Full field-level detail on this type lives in LocalBusiness schema →.
What local schema includes
Business name, address, phone (NAP)
Opening hours (by day, including special hours)
Geographic coordinates (latitude/longitude)
Business type/category
Price range
Aggregate rating (from reviews)
Website URL
Logo image URL
Social media profile links
Every one of these fields needs to match what's actually on the GBP and elsewhere on the web. A schema block declaring hours that don't match the GBP doesn't just fail to help — it actively contradicts a source Google already trusts, which is worse than having no schema at all.
Why local schema matters
Schema markup makes business data machine-readable rather than something a crawler has to infer from prose. Google extracts this structured data to populate Knowledge Graph → entries, local search results, and increasingly, AI Overview citations. A business with complete, accurate LocalBusiness schema tends to get cited more consistently and more correctly by AI systems than one that leaves the same facts sitting only in paragraph text, because the model doesn't have to guess where the address ends and the next sentence begins.
Schema for multi-location businesses
Each location page needs its own LocalBusiness schema block, with location-specific NAP matching the GBP for that location exactly. This is a rule businesses at scale get wrong more often than businesses with one location — a chain will build one central /locations/ page with an aggregate schema block covering all branches, then treat that as sufficient. It isn't. Google and AI systems need the schema at the page level where a user or crawler would actually land looking for that specific branch; a central aggregate page doesn't substitute for it. See multi-location SEO → for the operational side of managing this across dozens of branches.
Validation
Schema implementation should be checked with Google's Rich Results Test tool before assuming it's working. Syntax errors — a missing comma, a malformed nested object — can silently prevent extraction even when the markup is technically present on the page, which means a business can believe it has working schema for months while Google reads none of it.
Common mistakes
The most frequent mistake, beyond the multi-location aggregate-page problem above, is copying a schema template from a generic tutorial and never updating the placeholder fields for the specific business — a LocalBusiness block that still says "priceRange": "$$" when the currency and format should be in rupees, or hours left at the tutorial's default. The second is adding schema once at launch and never touching it again as hours, categories, or ratings change, so the structured data drifts out of sync with reality on the page it's supposedly describing.
Adjacent concepts
Local schema is one specific application of the broader structured data → concept, written in JSON-LD → using Schema.org → vocabulary. Review schema → covers the review and rating portion in more depth, and FAQPage schema → is worth adding alongside LocalBusiness schema on pages that answer common customer questions.
Local schema in India: Most Indian business websites have no LocalBusiness schema at all. This is a straightforward technical implementation — a developer can usually add it to a template in an afternoon — that provides a meaningful competitive advantage in local search and AI citation for the businesses that bother.
Related terms: LocalBusiness Schema → · Structured Data → · Schema.org → · JSON-LD → · Multi-Location SEO → · Knowledge Graph →
Example: A Jaipur boutique hotel chain adds LocalBusiness schema to each of its three property pages, declaring the correct address, GPS coordinates, amenities, and aggregate rating for that specific property. Within a few weeks, an AI Overview answering "boutique hotels near Hawa Mahal" correctly names the closest of the three properties by name and distance — something it hadn't done reliably before the schema was in place.
Related glossary terms
A score you can argue with, not a black box
Rank OS gives every profile a 0–100 score built from five weighted dimensions — Relevance, Review Health, Freshness, Entity Authority and AIO Readiness — and the weights are tunable. Underneath it sits a ranked list of the fixes that move the number, each with the point lift it unlocks.
Ready to have this run for you?
Book a free audit — we'll show you where you stand in 48 hours.