Structured data
Also known as: Schema markup · JSON-LD
Machine-readable metadata embedded in a web page (usually as Schema.org JSON-LD) that tells AI agents and search engines exactly what the page is about — product, article, FAQ, breadcrumb, review, etc.
Structured data is the layer of metadata that makes web content machine-legible. Schema.org is the shared vocabulary; JSON-LD is the preferred embedding format. Every major AI surface parses structured data preferentially over prose content because it's unambiguous.
Key schema types for agentic commerce: Product (name, price, availability, brand, offers), Offer (delivery, returns, shipping), FAQPage (Q&A pairs), Review + AggregateRating (first-party reviews), BreadcrumbList (site hierarchy), Article (blog posts and case studies), Organization (company details), DefinedTerm (glossary entries), Person (author bios).
Structured data is the highest-leverage single technical tactic in AI Search Visibility. Adding rich Product + FAQ + Review schema to a top SKU can move that SKU's rank measurably in 2-4 weeks — faster than most content-depth work.
See also
Structured data
Machine-readable metadata embedded in a web page (usually as Schema.org JSON-LD) that tells AI agents and search engines exactly what the page is about — product, article, FAQ, breadcrumb, review, etc.
Canonicalization
The process by which an AI agent decides which brand's version of a product is the 'canonical' one to recommend when multiple brands sell similar SKUs. Built over time via content depth + review + external authority.