SchemaFree

JSON-LD Presence

Counts JSON-LD structured data blocks on your page. More schema types means AI engines have richer context about your content.

Why It Matters for AI Visibility

JSON-LD is the primary way to communicate structured information to AI engines. ChatGPT, Perplexity, and Google AI Overviews use structured data to understand what your page is -- an article, a product, a FAQ -- who wrote it, and when it was published. Without any JSON-LD, AI engines must guess your content type from HTML patterns alone, which is unreliable and often wrong. With structured data, you explicitly declare: "This is a BlogPosting by [author] published on [date] about [topic]." That machine-readable context helps AI engines categorize your content, verify its authority, and decide whether to cite it in a response. Multiple schema types create a richer picture. An Article schema tells AI the content type. Add Organization schema and the AI knows the publisher. Add BreadcrumbList and it understands your site hierarchy. Add FAQPage and it gets extractable Q&A pairs. Each additional schema block gives AI engines another dimension of structured, unambiguous data about your page. Pages with comprehensive structured data are easier for AI to parse, trust, and cite than pages that force AI to infer everything from unstructured HTML.

How We Score It

The scoring is based on how many JSON-LD blocks exist on the page. Zero schemas is a fail with a score of 0 -- this is the single most impactful gap to fix since you get no structured data credit at all. One schema earns a partial score of 5 -- a good start, but AI engines need more context for full understanding. Two to three schemas earns an 8, representing solid coverage across content type and entity data. Four or more schemas earns a perfect 10, indicating comprehensive structured data that gives AI engines everything they need. The analyzer reports which @type values it found (Article, Organization, FAQPage, BreadcrumbList, etc.) so you can see exactly what context AI engines are receiving. A score of 7 or higher passes, 4-5 is partial, and 0 is a fail.

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How to Improve

1
Start with an Article or WebPage schema
If you have zero JSON-LD, add a basic Article schema with headline, author, and datePublished. This single addition moves your score from 0 to 5 and tells AI engines the fundamental nature of your content. Use the BlogPosting type for blog content or Article for general articles.
2
Add Organization schema site-wide
Include your company name, logo URL, website URL, and sameAs links to social profiles. Add this to every page via your site template or layout component. It establishes your brand entity across the entire site and is an easy win since you write it once and deploy everywhere.
3
Layer on BreadcrumbList for site hierarchy
BreadcrumbList schema tells AI engines where a page sits within your site structure -- for example, Home > Blog > Category > Post Title. This is especially valuable for content-heavy sites with deep hierarchies. Combined with Article schema, it gives you two blocks and a score of 8.
4
Add FAQPage schema to pages with FAQ content
If your page includes a frequently asked questions section, add FAQPage schema with the Q&A pairs as structured data. AI engines like Google AI Overviews can extract these directly into their responses. Combined with Article and Organization, this gives you three schemas and a score of 8.
5
Use separate script blocks for each schema type
The analyzer counts individual `<script type="application/ld+json">` blocks. Placing multiple types inside a single block using @graph may count as one block. For the maximum score, use separate script tags for each schema type -- one for Article, one for Organization, one for BreadcrumbList.

Before & After

Before

<!-- No JSON-LD on the page -->
<!-- Score: 0 (fail) -->

After

<script type="application/ld+json">
{ "@context": "https://schema.org", "@type": "Article",
  "headline": "Guide to API Authentication", "author": {"@type": "Person", "name": "Jane Smith"},
  "datePublished": "2025-01-15" }
</script>
<script type="application/ld+json">
{ "@context": "https://schema.org", "@type": "Organization",
  "name": "Acme Dev", "url": "https://acmedev.com", "logo": "https://acmedev.com/logo.png" }
</script>
<script type="application/ld+json">
{ "@context": "https://schema.org", "@type": "BreadcrumbList",
  "itemListElement": [
    {"@type": "ListItem", "position": 1, "name": "Home", "item": "https://acmedev.com"},
    {"@type": "ListItem", "position": 2, "name": "Blog", "item": "https://acmedev.com/blog"},
    {"@type": "ListItem", "position": 3, "name": "API Authentication"}
  ]}
</script>
<!-- Score: 8 (pass) — 3 JSON-LD blocks detected -->

Code Examples

Minimal Article schema

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Your Article Title",
  "author": {
    "@type": "Person",
    "name": "Author Name"
  },
  "datePublished": "2025-01-15"
}

Organization schema

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://example.com",
  "logo": "https://example.com/logo.png",
  "sameAs": [
    "https://twitter.com/yourcompany",
    "https://linkedin.com/company/yourcompany"
  ]
}

Frequently Asked Questions

Does it matter which schema types I use, or just the count?

This factor only counts the number of JSON-LD blocks. However, other GEO factors check for specific types and their completeness (Article schema, FAQ schema, Organization schema each have their own dedicated factors). For this factor, start with the types most relevant to your content and aim for at least two blocks.

Can I put all schemas in a single JSON-LD block using @graph?

The analyzer counts individual `<script type="application/ld+json">` blocks. Using @graph with multiple types inside one block may count as a single block. For the maximum score, use separate script tags for each schema type. This also makes it easier to manage and debug each schema independently.

Is JSON-LD better than Microdata or RDFa for AI engines?

Yes. JSON-LD is Google's recommended format and the easiest for AI engines to parse. It lives in a separate script tag, completely decoupled from your HTML markup. This means you can add, modify, or remove structured data without touching your page content. Most modern schema implementations use JSON-LD.

Related Factors

Schema

Article / BlogPosting Schema

Schema

Organization Schema

Schema

Schema Validation

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