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2.10Intermediate7 min

Schema Markup Implementation: Priorities for Enterprise B2B

Lucas Blochberger··Updated 20 April 2026
Definition

Schema markup implementation for Enterprise B2B follows a clear priority order: Organization (with sameAs to Wikipedia/Wikidata), Person (for expertise), Article (with authorship chains), Service, FAQPage and BreadcrumbList. @id properties create globally unique entity identifiers, sameAs confirms references.

Key Takeaways

  • Priority 1: Organization with sameAs to Wikipedia, Wikidata, LinkedIn, Crunchbase
  • Priority 2: Person for executives and subject matter experts with knowsAbout
  • Priority 3: Article/BlogPosting with authorship chains (Person → worksFor → Organization)
  • Priority 4: Service with detailed descriptions
  • Priority 5: FAQPage — valuable for AI extraction despite Rich Result limitations
  • @id creates globally unique entity identifiers
  • Disconnected entities reduce AI trust in attribution

Proper schema implementation for B2B enterprise requires a clear priority order and clean entity linking.

Implementation Priorities

Organization with sameAs links to Wikipedia, Wikidata, LinkedIn and Crunchbase anchors the brand entity in Knowledge Graphs. Person for executives and subject matter experts with credentials, linked via worksFor to Organization. Article/BlogPosting with complete authorship chains (Person → worksFor → Organization). Service for services with detailed descriptions. FAQPage — despite rich result limitations, valuable for AI extraction. BreadcrumbList for site structure understanding. Product/Offer if relevant, with GTIN/MPN for ChatGPT Shopping.

Entity Linking

The @id property creates globally unique entity identifiers. sameAs confirms that references point to known real entities. @graph connects entity networks across pages. Disconnected entities — where Author, Publisher and Organization don't correctly reference each other — create understanding gaps that reduce AI trust.

Martha van Berkel, CEO Schema App

FAQ

Why is FAQPage Schema still useful when Rich Results are restricted?
FAQ-structured content reflects how AI systems extract answers. Although FAQ Rich Results are restricted to government and health pages, AI systems continue to use the structured question-answer pairs for information extraction and show increased citation correlation.
What are Disconnected Entities?
When Author, Publisher and Organization don't correctly reference each other, understanding gaps emerge that reduce AI trust in attribution. Example: An Article has an Author (Person), the Person has worksFor (Organization), the Organization has sameAs (Wikidata). Any break in this chain weakens the signal.