Schema markup operates invisibly within page source code, but it plays a decisive role in whether AI systems can reliably cite and recommend your brand. In most AI visibility audits, it’s missing. Not partially implemented. Missing entirely.

This checklist covers every relevant schema type, the required fields for each, and the JSON-LD implementation code you need. Work through it top to bottom. The first two items alone will move the needle.

Before You Start: Run a Pre-Implementation Audit

Before adding schema markup, do four things:

  1. Check your homepage source code (Ctrl+U or Cmd+U) and search for application/ld+json. If nothing appears, you have no JSON-LD schema.
  2. Run your key URLs through Google’s Rich Results Test to document what’s already there.
  3. Note any existing schema types to avoid duplication.
  4. Keep the validation tool open throughout implementation - validate each block as you go.

1. Organization Schema (Homepage - Highest Priority)

Organization schema is the single most important schema type for AI visibility. It tells AI systems and search engines exactly who your company is.

Add to: Homepage <head> section inside a <script type="application/ld+json"> tag.

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company Name",
  "legalName": "Your Legal Entity Name",
  "url": "https://yourcompany.com",
  "logo": {
    "@type": "ImageObject",
    "url": "https://yourcompany.com/logo.png",
    "width": 512,
    "height": 512
  },
  "description": "One or two sentences describing what your company does, who it serves, and what category it belongs to. Write this the way you would want an AI system to describe you.",
  "foundingDate": "YYYY",
  "numberOfEmployees": {
    "@type": "QuantitativeValue",
    "value": 50
  },
  "address": {
    "@type": "PostalAddress",
    "addressCountry": "US"
  },
  "contactPoint": {
    "@type": "ContactPoint",
    "contactType": "customer support",
    "url": "https://yourcompany.com/contact"
  },
  "sameAs": [
    "https://www.linkedin.com/company/your-company",
    "https://www.crunchbase.com/organization/your-company",
    "https://www.g2.com/products/your-product/reviews",
    "https://www.capterra.com/p/your-product",
    "https://twitter.com/yourcompany"
  ]
}

The sameAs array is where most of the AI citation value lives. Include every active third-party profile: G2, Capterra, Crunchbase, LinkedIn, Google Business Profile, Wikipedia (if applicable), and relevant industry directories.

Organization schema checklist:

  • Name matches exactly on G2, LinkedIn, and Crunchbase
  • Description is a plain, accurate statement (not marketing language)
  • Logo URL points to a publicly accessible image
  • sameAs includes all active third-party profiles
  • No blank fields or placeholder text
  • Validated in Rich Results Test without errors

2. WebSite Schema (Homepage - Implement Alongside Organization)

WebSite schema declares your canonical domain to AI crawlers and search engines, reducing entity ambiguity when your brand name is shared with other companies or common terms. It also enables sitelinks search boxes for branded queries.

Add as: A separate <script> block from your Organization schema.

{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Your Company Name",
  "url": "https://yourcompany.com",
  "description": "Brief site description matching your Organization schema description.",
  "potentialAction": {
    "@type": "SearchAction",
    "target": {
      "@type": "EntryPoint",
      "urlTemplate": "https://yourcompany.com/search?q={search_term_string}"
    },
    "query-input": "required name=search_term_string"
  }
}

Omit potentialAction if your site doesn’t have a search function.

WebSite schema checklist:

  • URL matches canonical domain exactly (consistent with canonical tags)
  • Name matches Organization name exactly
  • Implemented in a separate <script> block
  • Validated in Rich Results Test

3. FAQPage Schema (FAQ Pages and Product Pages with Q&A Sections)

FAQPage schema is the highest-impact schema type for Google AI Overviews and conversational AI citation. It marks up question-and-answer content in a format that maps directly to how buyers prompt AI systems.

Add to: Main FAQ pages, pricing pages with common questions, product pages with Q&A sections.

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What does your company do?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Plain text answer here. Do not use HTML tags inside the text field. Write the answer the way you would want an AI system to quote it."
      }
    },
    {
      "@type": "Question",
      "name": "Who is your product designed for?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Plain text answer here."
      }
    },
    {
      "@type": "Question",
      "name": "How is your product different from competitors?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Plain text answer here."
      }
    }
  ]
}

The questions in your schema must exactly match the questions visible on the page. Google will not surface FAQ rich results if the schema questions don’t correspond to actual on-page content.

FAQPage schema checklist:

  • Every question in schema appears verbatim on the page
  • Answer text is plain text with no HTML markup
  • Answers are complete and self-contained (quotable independently)
  • Questions written as buyers would ask them (not keyword strings)
  • Implemented on every page with genuine Q&A content
  • Validated in Rich Results Test

4. Article and BlogPosting Schema (Blog Posts and How-To Content)

Article and BlogPosting schema signals to AI systems that content is authored, dated, and from an identifiable source. This increases citation likelihood on retrieval-based platforms like Perplexity and Claude.

Implementation approach: Apply once to your blog template so it covers all posts automatically.

{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "The Exact Post Title",
  "description": "The post meta description or first paragraph.",
  "url": "https://yourcompany.com/blog/post-slug",
  "datePublished": "2026-04-03",
  "dateModified": "2026-04-03",
  "author": {
    "@type": "Person",
    "name": "Author Name",
    "url": "https://yourcompany.com/author/author-name"
  },
  "publisher": {
    "@type": "Organization",
    "name": "Your Company Name",
    "logo": {
      "@type": "ImageObject",
      "url": "https://yourcompany.com/logo.png"
    }
  },
  "image": {
    "@type": "ImageObject",
    "url": "https://yourcompany.com/blog/post-featured-image.jpg",
    "width": 1200,
    "height": 630
  },
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "https://yourcompany.com/blog/post-slug"
  }
}

For company-published content rather than individual author bylines, replace the Person type in author with an Organization type matching your Organization schema.

Article/BlogPosting schema checklist:

  • Headline matches the H1 exactly
  • datePublished reflects actual publish date
  • dateModified updates when content changes
  • Image URL points to featured image (1200x630px recommended)
  • Templated across all blog posts, not just new ones
  • Validated on at least three posts to confirm the template works

5. Product Schema (Product and Service Pages)

Product schema communicates what your product or service does, who it’s for, and how it compares - in a structured format that AI systems draw on when generating vendor comparison responses. It’s particularly valuable for queries like “best tools for X.”

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Your Product Name",
  "description": "Clear, specific description of what the product does and who it is for. Avoid marketing language. Write it as a factual statement.",
  "url": "https://yourcompany.com/product",
  "brand": {
    "@type": "Brand",
    "name": "Your Company Name"
  },
  "manufacturer": {
    "@type": "Organization",
    "name": "Your Company Name",
    "url": "https://yourcompany.com"
  },
  "category": "Your Product Category",
  "offers": {
    "@type": "Offer",
    "priceCurrency": "USD",
    "priceSpecification": {
      "@type": "UnitPriceSpecification",
      "priceType": "https://schema.org/InvoicePrice",
      "name": "Starting price or pricing model description"
    },
    "url": "https://yourcompany.com/pricing"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.7",
    "reviewCount": "142",
    "bestRating": "5"
  }
}

Only include aggregateRating if you have verified public reviews to back it up. The rating value and review count should match what appears on G2, Capterra, or another public review platform.

Product schema checklist:

  • Description is factual and specific (not marketing copy)
  • Category matches G2 and Capterra categorization
  • aggregateRating only included if verifiable public reviews exist
  • Rating values match the most prominent public review source
  • Implemented on every product or service page
  • Validated in Rich Results Test

6. BreadcrumbList Schema (All Multi-Level Pages)

BreadcrumbList schema helps AI systems and search engines understand your site architecture, which improves the indexability of deeper content pages. It also generates breadcrumb trails in Google search results.

{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "https://yourcompany.com"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "Blog",
      "item": "https://yourcompany.com/blog"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "Post Title",
      "item": "https://yourcompany.com/blog/post-slug"
    }
  ]
}

Adjust the itemListElement array to reflect the actual page hierarchy - product pages would have Home, Products, and the specific product name.

BreadcrumbList schema checklist:

  • Implemented on all pages beyond the homepage
  • Position numbers sequential with no gaps
  • Each item URL is canonical for that hierarchy level
  • Matches visual breadcrumb navigation if present

The Full Implementation Checklist

Homepage:

  • Organization JSON-LD with complete sameAs array
  • WebSite JSON-LD
  • No placeholder text in any field
  • Validated in Rich Results Test (zero errors)

FAQ and Q&A Pages:

  • FAQPage JSON-LD on every page with genuine Q&A
  • Questions match page content verbatim
  • Answers are plain text, self-contained, quotable

Blog and Content Pages:

  • BlogPosting or Article JSON-LD templated across all posts
  • dateModified updates automatically on content changes
  • BreadcrumbList present on all posts

Product and Service Pages:

  • Product JSON-LD on each product or service page
  • aggregateRating only if backed by public reviews
  • BreadcrumbList present

Validation:

  • Every schema type tested in Rich Results Test
  • No errors (warnings acceptable, errors are not)
  • Re-validated after any content or schema update

What Happens After Implementation

Implementing this checklist changes what AI systems can do with your website. Before: inference from unstructured text, which introduces uncertainty and suppresses citation. After: confirmed, structured facts that AI crawlers can read and use directly.

Timeline expectations:

  • Google AI Overviews: Often reflect new FAQPage schema within two to four weeks.
  • Perplexity: Responds quickly to schema changes on newly indexed pages.
  • ChatGPT and Claude: Rely more on training data and take longer to update, but still benefit from schema during live browsing.

What this checklist doesn’t replace is the entity signals work: your third-party profiles, your press coverage, your review volume. Schema tells AI systems what your company is. Entity signals tell AI systems that independent sources agree. Both are required.