Structured Data
Structured data (schema markup) is machine-readable code embedded in a webpage — typically JSON-LD — that explicitly tells search engines and AI crawlers what a business, service, or piece of content is. Revvye checks whether required structured data exists and whether its required properties are complete.
Structured data uses the schema.org vocabulary to describe entities on a page — a LocalBusiness, a Service, a Product, an Organization, an FAQPage — in a format machines can parse directly, rather than inferring meaning from unstructured text. Revvye's scanner parses a site's JSON-LD and checks it against required properties for the relevant schema type; a common finding is a LocalBusiness block that exists but is missing its telephone or address property, which Revvye's public rule taxonomy names explicitly as structured-data.localbusiness.incomplete.
Structured data matters for two audiences at once. For traditional search engines, complete schema markup is what enables rich results — star ratings, business hours, FAQ accordions — directly in search listings. For AI crawlers and answer engines, structured data is often the fastest, most reliable way for a model to confirm facts about a business (its name, services, location, credentials) without having to parse and interpret free-form page text, which makes it directly relevant to whether an AI answer engine can describe a business correctly.
Structured data is one of Revvye's eight measured dimensions and interacts closely with trust signals and NAP consistency: provider, organization, and service schema is what lets a machine connect a team page, a service page, and a set of credentials into one coherent, verifiable story instead of three disconnected fragments.
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