Technical · 16 pages
Structured data for AI citation
Which schema types matter for answer engines, how to implement them without bloat, and how to verify they are being read.
Key findings
- 01
Organization, Product or Service, FAQPage, and Article cover most B2B needs. Add more only when a page genuinely fits the type.
- 02
Schema must match visible content. Markup that describes things the page does not show is ignored or penalized.
- 03
Connect entities with stable @id references so every page reinforces the same organization record.
Preview
Structured data does not make a page citable on its own, but it removes guesswork. It tells retrieval systems what an entity is, how it relates to others, and which facts are authoritative.
The short list
- Organization on every page, referenced by @id.
- Service or Product on offer pages, with Offer pricing where public.
- FAQPage where questions and answers are visible on the page.
- Article on editorial content, with a real author and dates.
Implementation rules
Generate JSON-LD from the same source as the visible content so the two cannot drift. Keep one graph per page, reuse @id values across the site, and validate on every deploy.
Verification
Use the Rich Results Test and Schema Markup Validator for syntax, then confirm in Search Console that the types are detected. For answer engines, check whether facts from your markup appear correctly in responses about your brand.