An audit of structured data validation should end with a short list of defensible changes. A vague quality score is less useful than a clearly observed defect, the reason it matters, and a check that shows whether the repair worked.
Start with the intended outcome
Structured data should describe the page's actual visible content accurately and be checked against the requirements of the intended feature.
Track validation errors, consistency with visible content, and eligibility without assuming a guaranteed search presentation.
Select a manageable sample that includes ordinary work as well as a known difficult case. Keep the current version and its relevant context. Do not assume that one unusually good or bad item represents the entire process.
Inspect five specific failure modes
1. AI-generated structured data invents ratings or reviews
Possible cause: The model fills optional fields with plausible examples.
Repair: Remove invented values and include only appropriate supported facts.
Acceptance check: Compare every claim in the markup with genuine visible page information.
2. Markup describes a different product from the page
Possible cause: A reused template retains another item's values.
Repair: Populate fields from the correct authoritative product record.
Acceptance check: Inspect the rendered markup on representative product pages.
3. Valid syntax is mistaken for guaranteed rich results
Possible cause: Technical validity is confused with display eligibility and selection.
Repair: Check applicable feature requirements and interpret validation within its limits.
Acceptance check: Do not promise a search appearance based only on a passing syntax check.
4. Structured data becomes stale after page updates
Possible cause: Visible content and markup use different data sources.
Repair: Connect both to consistent current records where practical.
Acceptance check: Compare prices, availability, and identifying details after relevant changes.
5. A page uses an irrelevant structured data type
Possible cause: The desired search appearance drives the choice instead of the content.
Repair: Select a type that accurately describes the actual page and supported use.
Acceptance check: Verify the applicable documentation before deploying the markup.
Prioritize the findings
Separate confirmed defects from suspicions. Fix issues that make the work inaccurate, unusable, or misleading before cosmetic preferences. For each selected change, record the affected item, the supporting evidence, the owner, and the acceptance check. Leave unverified ideas in a separate investigation list.
Interpret improvement carefully
Inspect the affected page in its actual site context. A change to one URL may also affect navigation, related pages, or how existing visitors reach information. Keep a record of the original state so the consequences of the change remain understandable.
Repeat the relevant checks after the change. A completed edit proves that the work was changed; it does not by itself prove a broader business effect. Keep the technical or editorial repair distinct from later performance observations, and document other changes that could influence the comparison.
Official reference for the platform or standard discussed: Google Search Central: structured data.