In this lesson you’ll cover:
- Why structured data is a signal automated systems use to classify and reconcile entities — and why consistency beats volume
- The canonical-name problem: how name variants across your site fragment an entity into separate nodes
- The three retrieval contexts (search-mediated, direct page access, structured endpoint) and what’s visible in each
- Why JavaScript-injected schema is invisible to direct-access agents, and the case for server-side-rendered JSON-LD in the head
- What schema does and doesn’t do across contexts: disambiguation, rich results, Knowledge Graph, LLM citation, ranking
- The three fields that do the interpretive work: @id, sameAs, and a classifying description
- The five common implementation errors and their fixes: wrong type, homepage-only schema, broken sameAs, blank-node person, aspirational schema
- Why passing validation is a floor, not a target — and a 30-minute organization-schema audit