Metric 1
Schema Markup
What we measure: Presence and quality of machine-readable structured data relevant to page intent.
Why it matters: Improves interpretability and signal confidence for automated extraction pipelines.
Product Narrative
Seven Core Metrics
What we measure, why it matters, and how teams use each metric to prioritize fixes.
Metric 2
On-page Trust Signals
What we measure: Visible indicators such as author, organization, and contact trust context on the page.
Why it matters: Helps systems evaluate source context without relying on hidden assumptions.
Metric 3
Semantic Structure
What we measure: Heading hierarchy, semantic organization, and layout patterns used for content chunking.
Why it matters: Reduces extraction ambiguity and improves consistency across rescans.
Metric 4
Entity Recognition
What we measure: Clarity and consistency of key entities (organizations, people, products, places).
Why it matters: Strengthens machine mapping of core concepts to your brand and subject domain.
Metric 5
Content Clarity
What we measure: Readability and directness of statements used in machine extraction contexts.
Why it matters: Supports cleaner quote extraction and lowers interpretation drift.
Metric 6
Freshness Signals
What we measure: Detectable publish/update timestamps and related recency cues.
Why it matters: Enables systems to reason about content recency instead of guessing.
Metric 7
Crawler Accessibility
What we measure: Crawler accessibility and rendering compatibility across JS and no-JS views.
Why it matters: Prevents hidden content and rendering gaps from breaking audit reliability.