Entities
Salience, disambiguation, canonical names, and linked references.
Methodology
How the AI Mention Scorecard works.
Our GEO/AEO rubric reverse-engineers how answer engines crawl, parse, and cite content. It is not a keyword checklist--it is a technical evaluation of how ingestible and verifiable your page is for modern LLMs.
Research-driven process
Six stages keep the rubric honest.
- Intent discovery: Map the high-value AI prompts your buyers ask.
- Crawl & capture: Fetch HTML, schema, feeds, and evidence exactly like AI agents do.
- Rubric scoring: Apply the 9-point GEO/AEO framework with weighted signals per engine.
- Entity & schema modeling: Align taxonomy, IDs, `sameAs`, and references.
- Answerability & evidence: Structure cite-able copy, proof, and ingestion cues.
- Implementation & governance: Provide tickets, JSON-LD, and monitoring hooks.
Rubric pillars
Every category ladders up to "Can AI engines cite you?"
Schema
JSON-LD validity, ID coverage, graph completeness, and context alignment.
Answerability
Prompt coverage, clarity, scannable headings, and structured responses.
Verifiability
Citations, evidence density, external corroboration, and trust cues.
Ingestion
Feeds, sitemaps, internal links, render fidelity, and language alternates.
Authority
Reputation signals, author entities, and cross-domain mentions.
Optimization KPIs
We measure outcomes, not vanity metrics.
- AI Intent Coverage (AIC)
- Share of tracked prompts where your brand appears in answers or source panels.
- Citation Rate (CR)
- Percentage of observed answers that explicitly cite or mention your brand/domain.
- Time-to-First-Mention (TTFM)
- Median time from publish/update to first observed AI mention.
- Entity Health Score (EHS)
- Validity + completeness of priority entities, relationships, and schema nodes.
Want the deep dive?
We publish experiments, release notes, and templates.
The Lab section (coming soon) will house KPI experiments, prompts, and entity templates so your team can keep pace with model updates.