Direct answer
Structured data is markup that explains information on a page to machines through predefined fields and relationships. It can make an entity's type, name, links and properties clearer, but it cannot turn a false claim into truth or guarantee that every AI system will use the data.
In plain language
Writing 'fragile glass tumblers, quantity 12' on a box says more than writing only 'items'. The label does not change the box; it describes its contents in a more orderly way.
Why this matters
Explicit fields can reduce entity confusion and ambiguous relationships. Markup that says something different from the visible page, however, creates a new trust problem.
Do not confuse
- JSON is a data format; JSON-LD is a use of JSON that adds linked-data meaning.
- Schema.org is a vocabulary; it does not mean every provider uses every field.
- Structured data does not replace visible content.
What should you do?
- Correct the fact in the visible text first.
- Choose the correct entity type and a stable identifier.
- Mark up only properties that are visible on the page and supported.
- Align relationships, names and URLs with the other canonical records.
- Test syntax and factual accuracy separately.
How do you audit it?
- Is the markup syntactically valid?
- Is the entity type correct?
- Does the marked-up information also appear on the visible page?
- Do the canonical URL and identity links conflict?
- Was an unsupported award, rating or ownership claim added?
Limit
Valid markup does not guarantee a rich result, indexing, citation, recommendation or accurate AI output.
Remember in one sentence
Structured data describes reality more clearly; it does not create reality.
Sources for this record
- S05Google Search Central, *Introduction to Structured Data*Provider documentation
- S06Google Search Central, *General Structured Data Guidelines*Provider documentation
- S07W3C, *JSON-LD 1.1*Standard
- S08Schema.org, *Data Model*Standard and community vocabulary