Plain-language explainer
What is schema markup?
Schema markup is structured data added to pages, using the schema.org vocabulary, to help search engines understand content such as organisations, products, FAQs and reviews.
The work to plan together
A scope shaped around this requirement.
- Usually added as JSON-LDScope
- Must match visible contentReview
- Can enable rich resultsCheck
The useful starting point
Structured data labels information in a machine-readable form. A valid syntax test does not prove that the claims are true or that the page qualifies for every search enhancement. Choose supported types that match the page.
What to review
- Usually added as JSON-LD
- Must match visible content
- Can enable rich results
- Test with Google’s Rich Results Test
What to avoid or interpret carefully
Never mark up hidden testimonials or invented ratings. Rich-result eligibility and actual display are controlled by the search platform.
Practical detail
Make the markup agree with the visible page
An illustrative service page may describe a Service named “Appliance repair” and its actual provider. The structured data must represent facts the page visibly supports.
| Part of the work | Example output | How to review it |
|---|---|---|
| Select a type | Choose a relevant documented type for the actual content | A schema type is not automatically a supported rich-result feature. |
| Write factual properties | Name, URL, provider and other appropriate real details | Do not add invented reviews, ratings or locations. |
| Validate syntax | Review JSON-LD and the applicable testing tools | A syntax pass does not validate every business claim. |
| Check eligibility | Read the specific feature’s guidelines if seeking a rich result | Valid markup does not guarantee the enhanced appearance. |
A minimal illustrative object is {"@context":"https://schema.org","@type":"Service","name":"Appliance repair"}. Replace it with the real page’s supported facts; no special AI Overview markup is required.
Reference guidance: Google structured-data introduction; Google Search AI-feature guidance.
Make the machine-readable description match the page
Structured data describes information using a supported format. It should agree with what a person can see and the actual business facts. Passing a syntax validator does not establish eligibility for every enhanced presentation.
Choose the purpose
Use a relevant supported type for the actual content. Do not add reviews, prices or credentials that are absent or invented. More schema types do not automatically mean better visibility.
Validate the facts
Compare names, URLs, offers and FAQ answers with the published page. A template can repeat outdated data across many URLs, so sample representative outputs after changes.
Understand the boundary
A valid implementation may be eligible for a supported feature, but selection remains a platform decision. Schema should not be sold as a guarantee of rich results or AI citations.
How to interpret this guidance
Visible content is the source of truth for the description. Update both together when an offer, FAQ or business detail changes, and keep owner-dependent fields unpublished until approved.
Can we add a rating without displaying genuine reviews?
No invented rating should be published. Review the relevant platform requirements and use only genuine permitted evidence. A decorative star count is not a factual review record.
Should every service page use review-rating markup?
Only use a supported type and eligible real visible information under the relevant feature rules. Do not attach a rating merely to make a search result look stronger.
Can Tangensys help with the next step?
Yes. Share your website, goal and the issue you are investigating. We can discuss the relevant service and provide a custom quote within 2 working days.
Further reading
Consult the relevant platform documentation for current requirements: official documentation. Examples explain an approach; platform interfaces and policies can change.
Related reading and services
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