Noma Lens

Scoring Methodology

The Readiness Score is /100, built from four evidence-weighted pillars. Every check below links to the published research behind its weight — and this page is generated from the same registry the auditor runs, so it can never drift from what we actually measure.

The four pillars

Raw check points inside each pillar are normalized to the pillar's weight, so adding or re-weighting checks never changes the meaning of the headline score. Business-type multipliers (SaaS, e-commerce, media, SMB) adjust individual checks before normalization. Tiers: 80+ AI-Ready, 60–79 AI-Aware, 40–59 AI-Exposed, below 40 AI-Blind.

Access & Retrievability 30 of 100

CheckWeightEvidence
AI retrieval bots can fetch pages (CDN/WAF level)
8 ptsCloudflare pay-per-crawl announcement
Content visible in raw HTML (no JavaScript required)
6 ptsVercel/MERJ AI-crawler rendering study
No restrictive snippet/preview controls
4 ptsShepard 54-study meta-analysis
XML sitemap present and valid
3 ptshygiene / supporting
Primary CTA accessible without CAPTCHA
Weighted by business type: smb ×0.6, ecommerce ×1, saas ×1, media ×0.7
3 ptshygiene / supporting
robots.txt present and valid
2 ptshygiene / supporting
Canonical tags present
2 ptshygiene / supporting
Contact/booking form accessible without hard bot block
Weighted by business type: smb ×1, ecommerce ×1, saas ×0.8, media ×0.6
2 ptshygiene / supporting
OpenAI bot stance documented in robots.txt
1 ptsBuzzStream training-vs-retrieval blocking study
Anthropic bot stance documented in robots.txt
1 ptshygiene / supporting

Content & Extractability 35 of 100

CheckWeightEvidence
Answer-first structure (content leads the page)
6 ptsShepard 54-study meta-analysis
Statistics and quotations density
6 ptsPrinceton GEO paper (KDD 2024)
Content chunked into heading-led sections
4 ptsShepard 54-study meta-analysis
Answer-dense content patterns present
4 ptsShepard 54-study meta-analysis
Content freshness (visible, recent dates)
4 ptsShepard 54-study meta-analysis
Specific verifiable claims present
3 ptsPrinceton GEO paper (KDD 2024)
Named author attribution present
3 ptshygiene / supporting
Sufficient unique content (low duplication risk)
3 ptshygiene / supporting
Schema.org structured data present
2 ptsAhrefs schema causal study
FAQPage or HowTo schema present
2 ptshygiene / supporting
OpenGraph tags complete (title, description, image)
2 ptshygiene / supporting

Authority & Off-site 25 of 100

CheckWeightEvidence
Brand mention footprint on the web
6 ptsAhrefs 75k-brand correlation study
LinkedIn Company page linked
4 ptsAhrefs 75k-brand correlation study
Brand listed on Crunchbase or Wikidata
4 ptsAhrefs 75k-brand correlation study
Wikipedia / Wikidata presence
4 ptsAhrefs 75k-brand correlation study
Review-platform presence
Weighted by business type: smb ×1, ecommerce ×1, saas ×1, media ×0.5
4 ptsProfound 680M-citation analysis
External citations / links to primary sources
3 ptsPrinceton GEO paper (KDD 2024)

Attribution & Measurement 10 of 100

CheckWeightEvidence
Analytics platform installed and active
4 ptshygiene / supporting
Noma Intel Smart Tag installed
4 ptshygiene / supporting
UTM parameters present on key links
3 ptshygiene / supporting

Reported, deliberately not scored

These observations appear in every report as “AI Posture & Compliance”, but carry zero score weight — because the evidence says they don't move AI visibility. llms.txt: no major engine reads it (97% of published files receive zero bot requests). Training-bot opt-outs: blocking GPTBot or Google-Extended does not remove you from AI answers — it's a data-governance choice, not a visibility factor, and rewarding it in a visibility score would be contradictory. Emerging agent standards (agent.json, MCP): promising, unmeasured — we'll re-weight when evidence lands. Privacy posture: a compliance matter, reported for completeness.

Show all 19 informational checks
/llms.txt present
Ahrefs llms.txt study
/llms-full.txt present
Ahrefs llms.txt study
Google-Extended stance documented
hygiene / supporting
CCBot (Common Crawl) stance documented
hygiene / supporting
Bytespider, PerplexityBot, YouBot covered in robots.txt
hygiene / supporting
GPTBot blocked (OpenAI training opt-out)
BuzzStream training-vs-retrieval blocking study
Google-Extended blocked (Gemini training opt-out)
BuzzStream training-vs-retrieval blocking study
CCBot blocked (Common Crawl training opt-out)
hygiene / supporting
Terms of Service references AI / automated scraping
hygiene / supporting
Privacy Policy references AI data processing
hygiene / supporting
/.well-known/agent.json manifest present
Weighted by business type: smb ×0.4, ecommerce ×0.6, saas ×1, media ×0.5
hygiene / supporting
MCP (Model Context Protocol) server published
Weighted by business type: smb ×0.3, ecommerce ×0.5, saas ×1, media ×0.4
hygiene / supporting
OpenAPI / Swagger spec published
Weighted by business type: smb ×0.2, ecommerce ×0.6, saas ×1, media ×0.3
hygiene / supporting
On-site AI features disclosed
hygiene / supporting
Privacy Policy references AI / automated processing
hygiene / supporting
Third-party AI service data sharing disclosed
hygiene / supporting
Data retention period stated in Privacy Policy
hygiene / supporting
Contact email listed for data/privacy queries
hygiene / supporting

What this score is not

The Readiness Score measures what you control on and around your site — it is not a measurement of how often AI engines actually mention you. Engine answers are volatile (the same query returns ~9% overlapping results across runs in some engines), so a defensible visibility number needs repeated sampling with confidence ranges. That measured Visibility Score is coming as a separate number beside this one — we won't blend them, because hiding the cause-and-effect between the two is how tools mislead.

Weights are reviewed quarterly against new research. When the evidence changes, the score changes, and this page changes with it — automatically.