Structured data — CrawlNFix Guide

Structured data is machine-readable markup that helps systems understand page content.

Use this workflow to compare machine-readable statements with the page a visitor can actually read. Begin with a relevant page type and keep observed markup separate from validation and search-result eligibility.

Quick answer

Inspect JSON-LD or other supported structured markup, identify the described entity, compare its properties with visible content, correct the source generator and validate the deployed result with an appropriate schema or search-feature validator.

Why this matters

A detected Product or Offer type establishes that a declaration was present. It does not prove a valid offer, current stock, an eligible rich result or a higher ranking. Template defaults can describe the wrong entity across many URLs.

In-depth explanation

Keep three records: what markup was observed, what a validator accepted and what the target platform actually displayed. These states can differ. Rich-result appearance requires separate observation and cannot be inferred from one detected type.

For comparison research, use equivalent product pages and preserve their source dates. Regional responses and selected variants can explain differences. A category listing should describe the listing rather than claiming that the whole category is one product.

What to check

Record the entity type, identifier, URL and important properties in the delivered source.
Compare names, prices, currencies and availability against the corresponding visible page and variant.
Inspect duplicate graphs from themes, plugins or application components and identify their owner.

Manual fix steps

Choose markup that accurately describes the public page. Do not add a type only because another website has it.
Correct the CMS plugin, template or generator that owns the inaccurate statement. Avoid creating a second competing graph as a patch.
Remove invented values. If a required property is unavailable, fix the underlying product data or reconsider the feature being represented.
Deploy, clear stale HTML caches and validate the exact public URL with the validator relevant to your intended use.

Verification checklist

Confirm the corrected values in delivered source and compare with visible content again.
Run schema validation and any relevant search-feature test. Record their findings separately from CrawlNFix type detection.
Check another page using the same generator, including a variant or item with a different availability state.

Workflow resources

Common mistakes

Equating JSON parse success with feature eligibility.
Treating an observed price as a verified checkout price.
Publishing a duplicate graph with conflicting values.

Practical example

A product shows USD 49.95 but its JSON-LD still declares a previous price. The shop corrects the structured-data generator, verifies the source and visible variant price, and validates the result. It does not label a source observation as a checkout test.

Frequently asked questions

Does CrawlNFix verify every schema property?

A type observation alone does not validate every property. Follow the stated check scope and use the relevant validator.

Should I add Product markup to a category?

Describe the actual listing and its entities accurately. Do not represent a category as one purchasable product merely to match a competitor.

Related diagnostic and explanation

Open the related diagnostic tool

Website Audit Reports Explained