Full transparency
How Detekia
calculates your score
Our scoring framework is based on the latest GEO research: Princeton/Georgia Tech (KDD 2024), ALM Corp (1.2M ChatGPT responses), AirOps State of AI Search 2026, Ahrefs Brand Radar 2026. Each criterion is weighted by its proven impact on AI citations.
The process
3 automated analysis steps
01
Content scraping
Detekia retrieves the full HTML of your page via a specialized AI scraping service. The raw HTML, text and metadata are extracted.
02
Heuristic analysis
Our analysis engine computes 7 heuristic scores by inspecting the DOM: tags, attributes, ratios, counts. These scores are reproducible and deterministic.
03
AI analysis
Our AI analysis engine evaluates the text content to assess editorial neutrality and generate contextualized recommendations. The final score incorporates this result.
3 AUDIT LEVELS
Same methodology, 3 levels of depth
The 7 criteria and scoring are identical across all 3 audits. What changes is the depth of analysis.
Score calculation
A score out of 100, 7 criteria
Each criterion is weighted based on its proven impact on AI citations (Princeton/KDD 2024, ALM Corp 2026, AirOps 2026).
25
pts
Citability
20
pts
Verifiability
15
pts
Authority E-E-A-T
10
pts
AI Accessibility
10
pts
Editorial Neutrality
10
pts
External Presence
10
pts
Freshness
Criteria details
The 7 criteria in detail
Score normalization
The score is calculated out of 100 points: 6 technical criteria (90 pts max) + AI-evaluated Editorial Neutrality (10 pts). The direct score is displayed without normalization.
Documented case studies
Each report includes real-world case studies on the 3 weakest criteria (SEO Vendor, Ahrefs, Stackmatix, etc.) to illustrate concrete impact of optimizations.
Analysis limitations
Page-level analysis
Detekia analyzes precisely the page you submit (homepage by default, or any other URL of your site), not the entire site. For most sites, the homepage concentrates the global signals (robots.txt, Organization schema, authority, social presence) and provides a representative diagnostic. To analyze multiple pages with a consolidated report, see our complete audit.
Non-measurable factors
Intrinsic content quality, offline reputation, inbound backlinks, and AI citation history cannot be measured by our technical analysis.
Algorithm evolution
AI citation criteria evolve regularly. Our methodology is updated but may lag behind the latest practices of AI models.
Dynamic websites
Websites that load their content entirely via client-side JavaScript (SPA without SSR) may receive underestimated scores because the content isn't accessible to the scraper.
SourcesโAggarwal et al., Princeton / Georgia Tech, KDD 2024ยทALM Corp, 1.2M ChatGPT citations (2026)ยทAirOps State of AI Search (2026)ยทConvertMate GEO Benchmark (2026)ยทAhrefs Brand Radar & Schema Study (2026)ยทConductor AEO/GEO Benchmarks (2026)ยทYext 17.2M AI Citations (2026)ยทBrightEdge AI Search (Mai 2026)ยทGo Fish Digital GEO Case Study (2026)
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