Schema markup
SEO & AI searchDefinition
Schema markup is structured data, usually JSON-LD, added to a page so machines can read what the page is about: a product and its price, an FAQ, an article, a defined term. Search engines use it for rich results, and AI engines use it to extract facts with confidence.
Schema.org defines the shared vocabulary: types like Product, Offer, FAQPage, Article, BreadcrumbList, and DefinedTerm, each with named properties. You embed a JSON-LD block that states the facts plainly, independent of your visual layout.
The payoff is machine confidence. Rich results (stars, prices, FAQs) raise click-through in classic search, and unambiguous structured facts make your page a safer citation for answer engines. This page, for instance, declares its term with DefinedTerm and its Q&As with FAQPage.
How Savra puts it to work
Savra’s SEO audits check structured data on your live pages, and its site tooling emits the right types per template: Offer on pricing, FAQPage where questions live, DefinedTerm across glossaries.
People also ask
Does schema markup improve rankings?
Not directly. It improves how results display (rich snippets) and how reliably machines extract your facts, both of which lift clicks and citations.
Which schema types matter most for marketing sites?
Organization, Product and Offer, FAQPage, Article, BreadcrumbList, and DefinedTerm for glossaries. Start where you have exact matching page types.
Related terms
Where this lives in Savra
See how Savra puts schema markup to work.
Does your brand sound like itself?
Run the free 90-second Brand Genome audit and see where your marketing drifts off-voice.