Overview
Schema Optimisation is the disciplined selection, implementation and validation of structured data that matches each page's real content. Correct schema can clarify entities and enable supported search features, but it is not a ranking trick and no individual schema type should be sold as a guaranteed AI-citation lever.
Business problem
Pages can be harder for machines to interpret when structured data is absent, wrong or invalid. At the same time, adding markup for retired features or claiming direct AI-citation effects wastes engineering and overstates what schema proves.
Decision supported
Which schema types to add to which pages, and how to fix invalid or conflicting markup.
Inputs & outputs
Inputs
- Page type and content purpose inventory
- Existing structured data and validation errors
- Eligible rich-result and schema types per page
- Entity and organisation data for markup
Outputs
- Per-page-type schema recommendation set
- Validated, deployable structured-data markup
Decisions this helps answer
KPIs
- Rich-result eligibility rate across key pages
- Structured-data error and warning count
SearchScore insight
Product feature mapping
How this capability maps to SearchScore product features, today and on the roadmap.
Recommends the highest-value schema type for each page.
Checks structured data for errors and eligibility.
Links organisation and entity markup into a coherent graph.
Future improvements
- Auto-generated schema tuned to emerging AI-answer requirements
- Continuous validation with regression alerts on markup changes
- Site-wide entity graph consistency scoring
Starter prompt
Based on the purpose and content of this page, recommend the most valuable schema types, generate valid markup, and flag any existing structured-data errors to fix.Recommended next steps
Where this fits - and what's next
The SearchScore path from a problem you feel to visibility you can measure.