Local Business

Local Business Schema Markup for WordPress

If you run a local business (a dental clinic, a law firm, a restaurant, a plumbing company) schema markup is the single clearest way to tell Google what you are, where you operate, and why you should show up when someone nearby searches for what you sell. Get it right and you become eligible for the local pack, knowledge panels, and increasingly, citations inside AI search results.

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What is LocalBusiness schema?

LocalBusiness schema is structured data (written in JSON-LD) that describes a physical, customer-facing business to search engines. In the schema.org vocabulary, LocalBusiness is a subtype of both Organization and Place, which is why it can carry both business identity and location signals in a single block.

Where a normal web page tells Google words on a page, LocalBusiness schema tells it facts about an entity: this business is called X, it's located at Y, it's open these hours, and here are the official profiles that prove it's the same business. That machine-readable clarity is the foundation of local search visibility.

Why local businesses need schema markup

The local pack and knowledge panel

Google assembles local results from a mix of your Google Business Profile, citations across the web, and the structured data on your site. Clean, consistent LocalBusiness schema reinforces the same facts Google sees elsewhere, strengthening its confidence in your business as a distinct entity.

Entity authority through sameAs

The sameAs property links your site to your Google Business Profile, Facebook, Instagram, and other authoritative profiles. This is how you connect your website to the wider Knowledge Graph and disambiguate your business from every other one with a similar name.

AI search citations

AI Overviews, ChatGPT, and Perplexity increasingly answer local, intent-driven queries ("best emergency plumber in Austin," "family dentist near me open Saturday"). A page with well-formed LocalBusiness schema is far easier for an AI system to interpret, attribute, and cite than one relying on prose alone.

Voice search

"Near me" and voice queries depend heavily on address, hours, and category data, exactly what LocalBusiness schema encodes.

A complete LocalBusiness JSON-LD example

Here's what correct, production-ready markup looks like for a dental clinic. Notice it uses the specific Dentist subtype rather than the generic LocalBusiness type:

{
  "@context": "https://schema.org",
  "@type": "Dentist",
  "@id": "https://brightsmiledental.com/#business",
  "name": "Bright Smile Dental",
  "image": "https://brightsmiledental.com/images/clinic.jpg",
  "url": "https://brightsmiledental.com",
  "telephone": "+1-512-555-0142",
  "priceRange": "$$",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "1200 South Lamar Blvd",
    "addressLocality": "Austin",
    "addressRegion": "TX",
    "postalCode": "78704",
    "addressCountry": "US"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": 30.2545,
    "longitude": -97.7688
  },
  "openingHoursSpecification": [
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
      "opens": "08:00",
      "closes": "17:00"
    }
  ],
  "areaServed": { "@type": "City", "name": "Austin" },
  "sameAs": [
    "https://www.facebook.com/brightsmiledental",
    "https://www.instagram.com/brightsmiledental"
  ]
}

A few of these fields do the heavy lifting: @id gives the business a stable, unique identifier so other schema on your site can reference the same entity. address + geo put you on the map, literally. openingHoursSpecificationpowers the "Open now / Closes at 5 PM" line searchers rely on. And sameAs is your entity glue, tying the website to the profiles Google already trusts.

Choose the right business subtype

One of the highest-impact decisions is specificity. Google recommends using the most specific applicable type, and schema.org offers 80+ LocalBusiness subtypes: Restaurant, Dentist, Plumber, AutoRepair, LegalService, and many more. See Google Search Central's structured data guidance for the current recommendation.

A dental practice should use Dentist, not LocalBusiness. If no subtype fits precisely, fall back to LocalBusiness and use sameAs to a Wikidata entry to further pin down what you do.

How to add LocalBusiness schema in WordPress

You have three options, and they aren't equal.

1. Hand-code it

Into your theme or functions.php. Full control, but brittle, every address change, new location, or theme update risks breaking the markup, and a single stray comma invalidates the whole block.

2. A general SEO plugin

Some SEO plugins offer basic LocalBusiness fields, but coverage is often shallow and locked behind assumptions about your business type.

3. Generate it automatically with AI Schema Gen

The plugin reads your page content and business details and produces a complete, subtype-specific LocalBusiness block, no code, no guesswork.

If you're weighing option 2, our AI Schema Gen vs Yoast comparison breaks down exactly what's covered and what isn't.

With AI Schema Gen, the flow looks like this:

  1. 1Install the plugin from the WordPress directory and connect your free account.
  2. 2Open the page or post for your business location.
  3. 3Generate the schema, the AI selects the correct subtype and fills in address, hours, price range, and entity signals from your content.
  4. 4Turn on auto-apply so schema regenerates whenever you update the page.
  5. 5Validate against Google's requirements right from your dashboard before it goes live.

Full setup details are in the documentation.

Common mistakes that break local schema

Even well-intentioned markup fails for predictable reasons.

Using the generic LocalBusiness type

When a specific subtype exists, this weakens classification. Always go as specific as your business allows.

Inconsistent NAP

Your Name, Address, and Phone must match exactly across your schema, your Google Business Profile, and directory citations. Mismatched NAP is one of the most common causes of local ranking trouble and entity ambiguity.

Marking up review data that isn’t visible on the page

aggregateRating and review must reflect real reviews shown to users. Inventing them is a policy violation that can trigger a manual action.

Dumping every location onto the homepage

For multi-location businesses, an array of locations on one page dilutes entity signals.

Describing information that isn’t on the page

Schema must reflect visible content, don't claim hours or services the page never mentions.

Skipping sameAs and geo

These are the fields that connect you to the Knowledge Graph and the map. Leaving them out throws away easy authority.

Multi-location businesses

If you operate more than one location, don't stack them all into a single schema block. Instead, publish a dedicated page per location and mark each one up with its own LocalBusiness block and a stable, unique @id. Keep NAP identical between each page's markup and that location's Google Business Profile. This lets each branch build entity signals and rank independently for its own area, the opposite of the diluted signal you get from a homepage location list.

LocalBusiness schema and AI search

The reason to care about all this in 2026 isn't just star ratings, it's attribution. Structured data that clearly states your business's type, location, service area, and verified profiles makes your site a cleaner, more citable source than a competitor relying on unstructured copy. Strong sameAs links and a specific business subtype are entity-authority signals that both traditional local SEO and AI-driven discovery reward. Every business vertical benefits, see how the same principle plays out for online stores and publishers.

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