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Pillar Page

Schema & Structured Data for AI Visibility

Structured data as trust and context for LLMs.

DefinedTermArticle/FAQTesting & QA

Structured Data Playbook

Machine-readable clarity

Structured data helps LLMs understand entities, relationships, and authority. This playbook prioritizes markups, QA processes, and monitoring.

Priority markups

DefinedTerm/DefinedTermSet for glossary entries and hub.

Article + Author/Organization for pillars & blog. FAQPage/HowTo where relevant.

BreadcrumbList for cluster navigation, Website/Organization for baseline signals.

Implementation & QA

Prefer JSON-LD, server-rendered. Avoid duplicate/contradicting markups.

Testing: Rich Results Test, Schema Markup Validator, automated linting in CI.

Context & consistency

Consistent naming (Organization, Author), same logos/URLs across schemas.

Link markups internally: breadcrumbs, sameAs, inDefinedTermSet, about/mentions.

Monitoring

Versioning and rollback for changes. Alerts on validation errors.

Sample logs: are schemas loaded by AI bots?

Examples

DefinedTerm JSON-LD snippet for a glossary term.

Article + FAQ combo for pillar pages.

BreadcrumbList for cluster navigation.

Next step

Test this factor in the GEO Analyzer

Test schema