Structured data is how you tell a machine, in its own language, exactly who you are. Instead of hoping an engine infers your business name, what you do, and who you serve from your prose, you state it in a format built to be read by software.
What it is
Structured data is a standardized way to label the meaning of a page. The vocabulary is schema.org; the recommended format is JSON-LD, a small block of JSON in a <script> tag. Google recommends JSON-LD specifically because it sits separately from your visible content and is easy to maintain.
Google’s own description of why it reads structured data is the clearest case for using it: it uses the markup “to understand the content of the page, as well as to gather information about the web and the world in general, such as information about the people, books, or companies that are included in the markup.” That last part, companies, is you.
Why AI engines care
When your identity is spelled out in structured data, an engine does not have to guess it from layout and copy, and it does not have to lean on a third-party directory that may have you wrong. You become a clearly defined entity: a name, a URL, a description, and links to the profiles that confirm it.
The two types that do the most work for most businesses are Organization (who you are) and FAQPage (the questions buyers actually ask). One note on FAQ, because Google changed the rules: it removed FAQ rich results from Search entirely in May 2026, so this markup no longer earns those expandable question boxes. The FAQPage markup is still valid schema.org, it causes no problems, and it still gives other engines and AI systems clean, structured question-and-answer pairs to extract. Add it for machine understanding, not for a Google rich result that no longer exists.
How to set it up
Drop an Organization block on your homepage. Fill in your real values:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Acme Analytics",
"url": "https://www.acme-analytics.com",
"description": "Acme Analytics provides AI visibility consulting and audits for B2B software companies.",
"logo": "https://www.acme-analytics.com/logo.png",
"sameAs": [
"https://www.linkedin.com/company/acme-analytics",
"https://www.crunchbase.com/organization/acme-analytics",
"https://www.wikidata.org/wiki/Q12345678"
]
}
</script>The sameAs links matter more than they look: they connect your page to authoritative profiles (LinkedIn, Crunchbase, Wikidata) and help engines confirm you are the entity they think you are. More on that in the schema entity coverage guide.
For the questions buyers ask, add FAQPage on the relevant page:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What does an AI visibility assessment cover?",
"acceptedAnswer": {
"@type": "Answer",
"text": "It evaluates how well your content and structured data can be understood and cited by AI search engines."
}
}
]
}
</script>Mark up only what is on the page
Your structured data should describe what is actually on the page. Marking up a FAQ that does not appear in your visible content, or an offer you do not really make, is the kind of mismatch engines learn to distrust. Keep the markup matched to the page, and validate it before you ship: paste the page into Google’s Rich Results Test or the Schema.org validator to confirm it parses cleanly.