Structured data

JSON-LD is how you state facts about yourself instead of hoping they're inferred.

What it is

Schema.org JSON-LD is a small block of machine-readable facts embedded in your page: who you are, what you sell, what it costs, what questions you answer.

It was built for search engines, and that is still where it does most of its work. AI tools that fetch a page mostly read the visible text instead, so treat JSON-LD as a clean statement of facts for the systems that parse it, not as a way to get quoted.

Why an agent cares

Without it, anything that does parse structured data (search engines, knowledge graphs, some agents) has to extract your facts from marketing copy, and marketing copy is exactly the genre most likely to mislead. Categories get guessed. Similar company names get merged.

Organization with sameAs ties your site to your profiles on LinkedIn, GitHub and Crunchbase, so systems that build an entity graph treat them as one company. What it does not do, on current evidence, is move AI citations much by itself: an Ahrefs study of pages that added schema found little change.

How to fix it

Start with Organization and your primary Product or Service. Add FAQPage only where the page genuinely answers those questions in visible text.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Acme",
  "url": "https://acme.com",
  "logo": "https://acme.com/logo.png",
  "description": "One sentence stating what you do and for whom.",
  "sameAs": [
    "https://www.linkedin.com/company/acme",
    "https://github.com/acme"
  ],
  "contactPoint": {
    "@type": "ContactPoint",
    "email": "hello@acme.com",
    "contactType": "sales"
  }
}
</script>

How we test it

We parse every application/ld+json block on your homepage and collect the @type values, including inside @graph. Two or more meaningful types pass.

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