Schema Structured Data
25 pts
Help AI systems identify entities, relationships, and page intent.
- Tier-1 coverage on key page types
- Required attributes completeness
- Nested graph structure quality
Public Scoring Methodology
How GEO Scoring calculates your AI visibility score
Our model is built to explain why a website is easy or hard for AI systems to extract, trust, and cite. The final score combines weighted dimensions, blocker penalties, and targeted bonus signals into a single 100-point framework.
Model
100 points
A weighted score built for AI search and answer-engine visibility.
Dimensions
7
Core areas spanning structure, content, authority, and readability.
Adjustments
Penalties + Bonuses
Critical blockers reduce the score, while strong AI-facing implementation can lift it.
Output
Grade + fixes
Every report pairs a final grade with prioritized remediation guidance.
Weighted dimensions
Each dimension measures a different part of AI citation readiness. Higher-impact areas receive more weight.
Total weight: 100 points
Content Citability
20 pts
Measure whether paragraphs are self-contained, quotable, and evidence-rich.
- Concrete facts and numbers
- Paragraph self-sufficiency
- Clear answer-first structure
Content Richness & Freshness
20 pts
Reward pages that are deep, current, and useful for AI answer synthesis.
- Page depth and completeness
- Freshness signals
- Supporting media and examples
Knowledge Graph Authority
15 pts
Assess brand/entity signals that make your site easier to trust and cite.
- Brand identity consistency
- Authoritative references
- Entity footprint on the open web
E-E-A-T Signals
10 pts
Check for expertise and trust markers that support high-confidence citations.
- Author and company transparency
- Trust and policy pages
- Experience and expertise cues
Open Graph & Social Metadata
5 pts
Ensure shared URLs are understandable across crawlers and downstream AI systems.
- og:title / og:description
- Image availability
- Share-ready page metadata
AI Readability
5 pts
Look for clean HTML, sensible semantic structure, and machine-readable layout.
- Semantic heading hierarchy
- Readable HTML structure
- Low-friction parsing
How the final score is produced
We do not stop at a raw weighted sum. The final grade reflects both what your site does well and whether there are hard blockers that prevent AI systems from consuming the content reliably.
1
Scan
We fetch the submitted site, inspect page structure, detect rendering mode, and collect machine-readable signals.
2
Score
Each dimension receives a weighted score based on the evidence we find on the site and in the page markup.
3
Adjust
We apply penalties for blockers and bonuses for strong AI-facing implementation patterns, then derive the final score and grade.
4
Recommend
The report surfaces the highest-impact fixes first so teams can improve citation readiness quickly.
Penalty signals
SubtractCritical crawler blocking
-15Blocking major AI crawlers or answer engines can suppress visibility regardless of content quality.
CSR-heavy rendering
-15If crawlers mainly see an empty shell, AI systems often cannot extract usable content.
Missing HTTPS
-10Trust and accessibility signals drop when the site is not served securely.
HTTP does not redirect cleanly
-3Inconsistent canonical delivery weakens consolidation and crawl confidence.
Bonus signals
AddHelpful llms.txt implementation
+3Makes high-value resources easier to discover and prioritize.
Strong content citability rate
+4Awarded when multiple pages are consistently quote-ready.
Structured ranked content
+3ItemList and similar patterns can improve synthesis for ranking-style pages.
Grade bands
Your final letter grade summarizes both weighted performance and adjustment effects.
A+
90-100
Excellent AI visibility with strong citation readiness.
A
80-89
Strong foundation with a few high-leverage gaps left.
B
70-79
Solid baseline, but important improvements remain.
C
60-69
Visible weaknesses likely reduce AI extraction quality.
D
0-59
Low AI visibility and weak machine-readable foundations.