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Schema markup

Also called structured data, Schema.org markup, JSON-LD

Definition

Schema markup is structured data added to a page, usually as JSON-LD, that tells search and answer engines what the page is about using the shared Schema.org vocabulary.

Updated 15 Sept 20262 sources, each checked3 min read

The idea

What it is

Schema markup describes a page as typed data a machine can read without guessing: this is an Article, written by this Person, published by this Organization, answering these questions. The vocabulary comes from Schema.org, which search engines maintain together, so the same types mean the same thing to Google, Bing and the crawlers behind AI answers.

It can be written three ways. JSON-LD puts the data in a single script block, separate from the visible HTML. Microdata and RDFa weave attributes into the HTML itself. JSON-LD is the format to use unless your platform prevents it, because a template can generate it from the same data the page renders, so the two cannot drift apart.

The evidence

Why it matters

For classic search, markup makes a page eligible for rich results such as review stars, FAQ displays and breadcrumbs, and the case studies Google publishes show those results earn noticeably more clicks. Eligibility is not a promise, though: Google states plainly that correct markup does not guarantee a rich result.

For AI search, markup removes ambiguity at the moment an engine decides who wrote a page, when, and about which company. That helps it attribute and describe you correctly. No major engine documents structured data as a ranking or citation guarantee, so treat it as making your page easier to understand, not as a switch.

The steps

How to do it

  1. 1

    Start with the types most sites need: Organization on the homepage, Article or BlogPosting with a Person author on every post, BreadcrumbList for navigation, and FAQPage only where the questions and answers are visible on the page.

  2. 2

    Add Product, SoftwareApplication or LocalBusiness only where the page genuinely describes one.

  3. 3

    Generate the JSON-LD from the data the page renders, not from a separate hand-edited file, so a changed price or author updates both.

  4. 4

    Use absolute URLs, give authors a name and a profile URL, and avoid two competing blocks of the same type on one page.

  5. 5

    Validate every template with Google’s Rich Results Test before shipping, then watch the rich result reports in Search Console for errors after launch.

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What goes wrong

Common mistakes

  • Marking up content readers cannot see, such as FAQs that exist only in the markup. Google’s guidelines prohibit it.
  • Expecting markup to create a rich result or an AI citation on its own. It makes a page eligible and easier to interpret; it does not override quality.
  • Letting markup drift from the page. A stale price or author in JSON-LD is a contradiction an engine may notice before a person does.
In practice

An example

A minimal Article block

A blog post’s JSON-LD sits in one script tag of type application/ld+json and declares an @context of https://schema.org, an @type of Article, a headline matching the visible title, and an author object of @type Person with a name and a url pointing to the author’s profile. Google’s documentation walks through the same pattern and recommends checking it in the Rich Results Test.

Google Search Central, Introduction to structured data markup, 15 Sept 2026
Nearby terms

Not to be confused with

JSON-LD
JSON-LD is one format for writing schema markup, and the one Google recommends. Schema markup is the vocabulary; JSON-LD is how it is written down.
FAQ schema
FAQPage is one schema type among many, for pages with visible questions and answers.
Checked

Sources

  1. 1Google Search Central, Introduction to structured data markup read 15 Sept 2026
  2. 2Google Search Central, General structured data guidelines read 15 Sept 2026

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