Schema markup
Schema markup is structured data code (usually written in JSON-LD) that you add to a web page to label what its content means — for example, marking up a product's price, an article's author, or an FAQ's questions and answers. It gives search engines and AI answer engines machine-readable facts they can parse, trust, and cite, instead of guessing from raw text.
What schema markup actually is
Schema markup uses the shared vocabulary at Schema.org to describe entities and their properties in a format machines can read. The standard syntax is JSON-LD (JavaScript Object Notation for Linked Data) — a small script block in the page's HTML that sits separate from the visible content, so it does not change how the page looks to a human reader.
Common types include Organization, Product, Article, FAQPage, HowTo, BreadcrumbList, and DefinedTerm. Each one tells engines, in plain structured terms, things like "this is the price," "this is the author," or "this is a question and its answer" — turning prose into labeled, queryable facts.
Why it matters for SEO and GEO
In classic SEO, schema powers rich results — the star ratings, FAQ dropdowns, and breadcrumb trails you see in Google. In the AI era it matters even more. Answer engines like ChatGPT, Perplexity, and Google's AI Overviews lean on retrieval-augmented generation to find and quote sources, and pages with clean structured data are easier to parse and provide verified facts the model can reference with confidence.
- Helps AI engines pick your page as source material during retrieval
- Supplies precise, attributable facts that raise the odds of an explicit AI citation
- Reinforces entity SEO by disambiguating who you are and what you offer
- Speakable and FAQ markup feed voice and answer-engine surfaces directly
Schema is a foundation of generative engine optimization, not a magic switch. Effects take time — crawlers typically need 4 to 8 weeks to re-index and reflect changes in AI-generated answers.
Schema markup with an approval-gated AI marketing team
Writing valid JSON-LD by hand is fiddly, and a single malformed bracket can break a page's rich results. Ceres is a managed AI marketing team where an AI Growth Officer coordinates 11 specialists — including a GEO Strategist and an SEO content role — who can draft schema markup, audit what is already on your site, and flag gaps from the free GEO audit.
You stay the boss: specialists prepare the structured data and recommendations, and every outbound or publishing action is approval-gated — a human reviews and approves before anything ships to your live site.
FAQ
- What is schema markup?
- Schema markup is structured data code — typically JSON-LD — added to a web page to label what its content means, such as a product's price, an article's author, or an FAQ's questions and answers. It gives search engines and AI answer engines machine-readable, citable facts instead of leaving them to infer meaning from raw text.
- Is schema markup a Google ranking factor?
- Schema is not a direct ranking factor on its own, but it strongly influences visibility. It unlocks rich results in classic search and makes your facts easier for AI engines to parse and cite, which can improve how often your page is selected as a source and shown in AI Overviews and answer engines.
- What is the difference between schema markup and JSON-LD?
- Schema markup is the vocabulary — the Schema.org types and properties that describe your content. JSON-LD is the preferred format for writing that vocabulary into a page. In 2026 every major engine, including Google, Bing, Perplexity, and ChatGPT, favors JSON-LD because it keeps structured data in a clean script block separate from the visible HTML.
An AI growth team that runs this for you
Ceres is a managed AI marketing team — you approve what ships. 14-day free trial, from $19/month.