The Seven Schema Types Every Local Business Is Missing in 2026

When I audit a local business site, I check Schema.org markup within the first five minutes. Not because it's the most important thing — but because it's the fastest signal of whether the site was built with AI retrieval in mind or not. Roughly 85% of Brooklyn small business sites I audit have either no schema markup at all, or only the minimal LocalBusiness block that a Squarespace or Wix template auto-generates with the business name and address and nothing else.

That minimal implementation is better than nothing. But it misses most of the fields that actually matter for AI citation, and it skips six other schema types entirely that have direct influence on whether and how AI engines include your business in their answers.

This post walks through the seven. For each one, I'll explain what it does, what most sites get wrong, and show the fields that matter most.

01. LocalBusiness — The Foundation Most Sites Underspecify

Every local business site should have a LocalBusiness block (or a more specific subtype — Optician, MartialArtsSchool, Dentist, etc.). Most do. The problem is which fields they include.

The fields most sites have: name, address, telephone, url. That's enough to pass a schema validator. It is not enough to make you AI-retrievable.

The fields most sites are missing:

geo — explicit latitude/longitude coordinates. AI engines use this to resolve location ambiguity. If your address contains a street that exists in multiple neighborhoods or cities, geo coordinates are the authoritative signal.
openingHoursSpecification — machine-readable hours. Not a text string like "Mon-Fri 9-6." A proper openingHoursSpecification array with dayOfWeek, opens, and closes values.
priceRange — a simple string like "$$" or "$75–$150 per session". This is a low-effort field that AI engines use to qualify businesses for price-sensitive queries ("affordable optometrist Crown Heights").
aggregateRating — if you have reviews anywhere online, this field should exist. See schema type 5 below for the full picture.
sameAs — an array of URLs that confirm your identity across other platforms: your Yelp URL, your Google Business Profile URL, your Facebook page. This is how AI engines verify entity consistency.

{
  "@context": "https://schema.org",
  "@type": "Optician",
  "name": "Nostrand Optical",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "1234 Nostrand Ave",
    "addressLocality": "Brooklyn",
    "addressRegion": "NY",
    "postalCode": "11225"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": 40.6602,
    "longitude": -73.9496
  },
  "telephone": "+1-718-555-0100",
  "url": "https://nostrandoptical.com",
  "priceRange": "$$",
  "sameAs": [
    "https://www.yelp.com/biz/nostrand-optical",
    "https://maps.google.com/?cid=XXXXXXX"
  ]
}

02. FAQPage — The Most Direct Path to AI Citation

FAQPage schema is the single highest-leverage schema type for AI citation, and almost no local business sites use it. Here's why it matters so much: AI engines are answering questions. FAQPage schema tells them, in machine-readable format, exactly what questions you answer and exactly what you say in response. It is pre-formatted content for AI extraction.

Google has used FAQPage markup for rich results in organic search for years. In the AI search context, the same markup makes your Q&A content directly extractable by Perplexity, ChatGPT, and Google AI Overviews when a user asks a matching question.

What to write FAQ schema for: every question your customers ask before booking. "Do you accept insurance?" "How long is a new patient exam?" "Do I need an appointment?" "What's parking like?" "Is this good for beginners?" Write the questions the way people actually ask them, in natural language, and write thorough declarative answers.

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "Do you accept VSP and EyeMed insurance?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Yes, Nostrand Optical accepts VSP, EyeMed, and most major vision insurance plans. We verify benefits before your exam at no charge."
      }
    },
    {
      "@type": "Question",
      "name": "How long does a comprehensive eye exam take?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "A full eye exam at Nostrand Optical takes approximately 45 to 60 minutes for new patients, including the refraction, health screening, and frame consultation if needed."
      }
    }
  ]
}

03. Service — Telling AI Exactly What You Offer

LocalBusiness schema tells AI engines that you exist and where you are. Service schema tells them what you actually do. These are different facts, and AI engines treat them separately when assembling answers to service-specific queries.

When someone asks "who offers private adult BJJ lessons in Park Slope," an AI engine needs a machine-readable claim that connects a specific service (private adult BJJ instruction) to a specific provider (Brooklyn BJJ Lessons) in a specific location (Park Slope, Brooklyn). Service schema provides that connection explicitly.

Key fields for Service schema: name (the service name), description (a clear declarative description), provider (linked to your LocalBusiness entity), areaServed (the geographic area), and audience (who it's for). Use a separate Service block for each distinct service you offer.

{
  "@context": "https://schema.org",
  "@type": "Service",
  "name": "Private Adult BJJ Lessons",
  "description": "One-on-one Brazilian Jiu-Jitsu instruction for adult beginners and intermediates in Park Slope, Brooklyn. Sessions are 60 minutes and designed around the student's pace and goals.",
  "provider": {
    "@type": "LocalBusiness",
    "name": "Brooklyn BJJ Lessons",
    "url": "https://brooklynbjjlessons.com"
  },
  "areaServed": {
    "@type": "City",
    "name": "Brooklyn"
  },
  "audience": {
    "@type": "Audience",
    "audienceType": "Adults, beginners welcome"
  }
}

04. BreadcrumbList — Helping AI Cite the Right Page

This is the schema type that feels least important to most people and is actually quietly influential. BreadcrumbList markup tells AI engines how your site is structured — which page is the homepage, which is the services page, which is a specific service page — and gives them a navigational context for the content they're retrieving.

Why this matters for AI citation: when an AI engine retrieves content from your site to answer a query, it needs to know whether to cite the root domain, a category page, or a specific page. BreadcrumbList gives it that hierarchy explicitly. Without it, the engine has to infer structure from URL patterns and internal link context, which is less reliable and may result in citing a less relevant page.

Every page on your site should have a BreadcrumbList block reflecting its position in the site hierarchy. It's a small addition with meaningful impact on which URL gets surfaced in AI answers.

05. Review / AggregateRating — The Social Proof Signal AI Uses for Confidence

AI engines aren't just finding businesses — they're recommending them. Recommendations require confidence. AggregateRating schema is a direct machine-readable signal that other people have evaluated and affirmed your business.

Most local business sites with reviews don't expose those reviews in Schema markup at all. They exist on Yelp, on Google, on Healthgrades — but not in structured data on the business's own site. That gap means the AI engine can't attribute review data to your site's entity without fetching it from third-party sources, which is less reliable and less often done.

The fix is straightforward: pull your aggregate review data (total count, average rating) into an AggregateRating block on your homepage and link it to the source. If you have individual reviews you want to highlight, use Review schema with reviewer attribution. Keep the data current — an AggregateRating block showing 4.9 stars from 47 reviews is a concrete confidence signal for AI citation in competitive queries.

{
  "@context": "https://schema.org",
  "@type": "Optician",
  "name": "Nostrand Optical",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.9",
    "reviewCount": "84",
    "bestRating": "5",
    "worstRating": "1"
  }
}

06. Person — Connecting the Founder to the Business Entity

This schema type is almost universally absent from solo practitioner and small business sites, and it's particularly important in the AI search era. Here's why: when someone asks "who is the best private BJJ instructor in Brooklyn" or "who runs the optometry practice on Nostrand," AI engines are looking for a person entity, not just a business entity. Person schema connects the two.

Person schema establishes a machine-readable identity for the practitioner behind the business. It includes their name, role, credentials, and relationship to the business entity. For any business where the founder's expertise, credentials, or personality is part of the value proposition — a solo instructor, a solo practitioner, a consultant — this schema type is load-bearing for AI visibility.

It also feeds directly into Google's E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness). A Person entity with documented expertise in a field, connected to a LocalBusiness entity providing services in that field, is a strong combined signal for AI confidence in citing your business for expert-service queries.

{
  "@context": "https://schema.org",
  "@type": "Person",
  "name": "Marcus Webb",
  "jobTitle": "Brazilian Jiu-Jitsu Instructor",
  "description": "Marcus Webb is a Brazilian Jiu-Jitsu black belt and private instructor based in Park Slope, Brooklyn, with 14 years of training and 7 years of teaching experience.",
  "worksFor": {
    "@type": "LocalBusiness",
    "name": "Brooklyn BJJ Lessons",
    "url": "https://brooklynbjjlessons.com"
  },
  "url": "https://brooklynbjjlessons.com/about"
}

07. WebSite with SearchAction — Signaling a Retrievable Web Presence

The last schema type on this list is the one that signals to AI engines that your site is a structured, retrievable web presence — not just a collection of HTML pages. WebSite schema with a SearchAction property tells crawlers that your site has searchable, organized content worth indexing as a coherent entity rather than a loose set of documents.

The SearchAction component, specifically, is a machine-readable statement that your site supports queries — useful for AI systems that are trying to understand whether a web presence is a structured information source. Combined with the other schema types on this list, it completes a picture of a site that is explicitly designed to be retrieved and cited.

{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Nostrand Optical",
  "url": "https://nostrandoptical.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": {
      "@type": "EntryPoint",
      "urlTemplate": "https://nostrandoptical.com/?s={search_term_string}"
    },
    "query-input": "required name=search_term_string"
  }
}

How to check your current schema

Paste your site URL into Google's Rich Results Test (search.google.com/test/rich-results) or Schema.org's validator (validator.schema.org). You'll see every schema block present on your page, any validation errors, and which rich result types you're eligible for. Most local business sites I audit fail on at least 4 of the 7 types listed here. The fix is an afternoon of work, not a month-long project.

Schema markup is a conversation you're having with AI in a language it understands natively. Most local businesses are staying silent.

None of these seven schema types require a developer. They're JSON-LD blocks that live in the <head> of your HTML pages or in your CMS's custom code sections. Every schema type on this list has been present on the Signal client sites that rank best in AI search. None of the sites that I've inherited with weak AI visibility have had all seven.

The relationship between schema completeness and AI citation consistency isn't a hypothesis at this point. It's a pattern I've seen repeatedly across the Brooklyn portfolio. Start with LocalBusiness and FAQPage if you're adding schema from scratch. Then layer in Service, Person, and AggregateRating. BreadcrumbList and WebSite are quick additions that complete the picture. You're looking at a few hours of implementation work against a meaningful improvement in how confidently AI engines retrieve and cite your business.