Mozilla.org maintains a strong global SEO position with a Global SEODiff Score of 71, reflecting solid technical and architectural foundations, though it falls short in traditional SEO execution, scoring only 44. The site earns a C-grade ACRI score (61), indicating moderate trust and credibility signals, while its AI Readiness GEO score of 82 underscores high compatibility with AI-driven search systems. Despite a robust performance profile—evidenced by a TTFB of 767ms, 80% performance score, and strong security headers (HSTS, CSP)—the site exhibits notable content integrity challenges, with a content integrity score of just 29, suggesting poor text-to-HTML ratio and potential overuse of non-semantic markup.
The site demonstrates strong AI accessibility, with gptbot, claudebot, ccbot, and Google Extended bots all allowed, and no blocking meta tags, positioning it well for AI indexing. However, it lacks structured data entirely: zero schema blocks, and missing key types like Organization, Website, Breadcrumb, and Article. This absence limits semantic enrichment and reduces visibility in AI-powered search features. Additionally, while the token bloat ratio is 4.9x and ghost ratio is 5.0%, both within acceptable ranges, the low word count (321 words) and useful text bytes (9,737) relative to total HTML (47,971 bytes) indicate excessive non-content markup, diminishing content clarity and value perception.
Architecturally, Mozilla.org shows moderate internal link distribution with 124 internal links but only 9 external links, suggesting limited external authority signaling. The absence of a declared sitemap hampers crawl efficiency and indexation coverage. While the Tranco rank of 103 confirms high global traffic and authority, the AI Trust Score of 24 reveals significant room for improvement in content authenticity and source credibility. To elevate performance, Mozilla should prioritize semantic structuring, implement comprehensive schema markup, reduce token bloat, and publish a sitemap to enhance AI and human discoverability.
🧮 Score Transparency — How is this calculated?
📊 ACRI Sub-Scores (AI Readiness Detail)
mozilla.org shows stronger AI visibility than traditional SEO ranking. Great AI foundation to build on. ACRI measures technical crawler readiness. Read the methodology →
Why mozilla.org ranks here
Fastest improvements
- Add basic Organization and WebSite JSON-LD to fix “0 schema blocks” (see Schema Coverage).
- Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
- Create an
llms.txtfile so AI crawlers can discover your content structure without heavy crawling. Generate llms.txt → - Run a full entropy audit to find which DOM regions waste the most tokens. Run Entropy Audit →
Traditional SEO
44/100 25 % of Global Score 🟢 High Confidence📝 Title Tag
Optimal range: 30–60 characters for SERP display.
📋 Meta Description
Optimal range: 120–160 characters for snippet control.
🔤 Heading Hierarchy
- ✓ Exactly 1 <h1> tag — found 1
- ✓ Has <h2> headings — found 26
- ✗ <h2> not before <h1>
🔍 Indexability
- ✗ Canonical tag present
- ✓ No noindex directive
- ✓ Meta viewport set
- ✓ HTML lang attribute →
ru - ✅ Hreflang tags
- ✓ Googlebot allowed by robots.txt
🌐 Social / OpenGraph
- ✓ og:title — Internet for people, not profit
- ✓ og:description — Mozilla is the not-for-profit behind the lightning fast Firefox browser. We put people over profit to give everyone more power online.
- ✓ og:image — preview
- ✓ twitter:card — summary
📐 How the SEO Pillar score is calculated
SEO Pillar = Title (20 pts) + Meta Desc (20 pts) + Heading Hierarchy (20 pts) + Indexability (20 pts) + Social/OG (20 pts)
Each sub-score is derived from the checks above. Canonical tag, lang attribute, og:image, and a single H1 are the highest-impact items.
AI Readiness / GEO
82/100 40 % of Global Score 🟢 High ConfidenceThis pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.
Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.
🤖 Bot Access Matrix
📊 Structure & Information Density Docs
🏷️ Schema Health Docs
Schema Coverage Map
📐 AI Efficiency Metrics Docs
Token Bloat Research
Multimodal Readiness
TDM Rights
🔥 Structural Entropy Check Research
🔬 AI-Crawler Simulation
See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
AI Answer Preview
NEWSee how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.
The LLM Interpretation
AI-VERIFIEDSEODiff AI analyzed the extracted content of mozilla.org and produced this structured business intelligence. Fields marked SEMANTIC VOID indicate information the AI could not find — a critical gap in your site’s machine-readability.
🔧 Tech Stack
Performance & Speed
80/100 20 % of Global Score 🟢 High Confidence⏱️ Time to First Byte
Google considers <200 ms "good". AI crawlers may have even shorter timeouts.
📦 Page Weight
DOM nodes
HTML payload
🗄️ Cache & CDN
- ✓ Cache-Control header →
max-age=600 - ✗ CDN cache status
- ✗ CDN detected
🔬 Tracker Tax
tracker scripts
third-party domains
token overhead
📐 How the Performance Pillar score is calculated
Perf Pillar = TTFB (35 pts) + Page Weight (25 pts) + Cache/CDN (20 pts) + Tracker Tax (20 pts)
TTFB <200 ms = full marks. DOM >3000 or payload >300 KB incurs heavy penalties. Tracker scripts beyond 5 reduce score.
Architecture & Trust
72/100 15 % of Global Score 🟢 High Confidence🗺️ Sitemap & Robots
- ✗ Sitemap declared in robots.txt
- ✓ Googlebot allowed
- ✓ GPTBot allowed
- ✓ ClaudeBot allowed
🔗 Linking
internal links
external links
🔒 Security & Trust
- ✓ HSTS header (Strict-Transport-Security)
- ✓ Content-Security-Policy header
- ✓ HTTP status 200 OK (got 200)
♿ Accessibility Signals
- ✓ HTML lang attribute → ru
- ✓ Meta viewport for mobile
- ✓ Single H1 for screen readers
📐 How the Architecture Pillar score is calculated
Arch Pillar = Sitemap & Robots (30 pts) + Linking (25 pts) + Security (25 pts) + Accessibility (20 pts)
Having a valid sitemap, allowing AI bots, HSTS, and a good internal link count are the highest-impact items.
🏅 AI-Verified Trust Badge
Your site scores 61/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.
<a href="https://seodiff.io/radar/domains/mozilla.org" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=mozilla.org" alt="AI-Verified by SEODiff" width="280" height="52"></a>
💡 Paste in your site footer, GitHub README, or email signature. Badge updates automatically as your score changes.
� Deep Crawl Analysis 23 pages · Deep-10
Homepage scores 61, but internal pages average only 18 — a -43-point gap. Blogs, docs, and legacy content are dragging down AI readability site-wide.
Poorly formatted tables or pricing grids on 1 page will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.
| Page | Type | ACRI | Token Bloat | Words | Status |
|---|---|---|---|---|---|
| pricing | 77 | 7.6× | 1618 | 💰 Pricing | |
| legal | 77 | 9.8× | 907 | ✓ | |
| trust | 67 | 10.9× | 792 | ✓ | |
| about | 49 | 43.4× | 264 | ✓ | |
| pricing | 49 | 36.2× | 341 | ⚠️ RAG Fracture | |
| support | 49 | 37.1× | 282 | ✓ | |
| support | 49 | 34.0× | 204 | ✓ | |
| pricing | 0 | 0.0× | 0 | ✓ | |
| docs | 0 | 0.0× | 0 | ✓ | |
| blog | 0 | 0.0× | 0 | ✓ | |
| support | 0 | 0.0× | 0 | ✓ | |
| blog | 0 | 0.0× | 0 | ✓ | |
| product | 0 | 0.0× | 0 | ✓ | |
| product | 0 | 0.0× | 0 | ✓ | |
| blog | 0 | 0.0× | 0 | ✓ | |
| docs | 0 | 0.0× | 0 | ✓ | |
| conversion | 0 | 0.0× | 0 | ✓ | |
| social-proof | 0 | 0.0× | 0 | ✓ | |
| conversion | 0 | 0.0× | 0 | ✓ | |
| integrations | 0 | 0.0× | 0 | ✓ |
| Path | Pages | Avg ACRI | Ghost % | Bloat | Top Issue |
|---|---|---|---|---|---|
| /products/ | 1 | 49 | 0% | 36.2× | High JS Bloat |
| /contact/ | 1 | 49 | 0% | 34.0× | High JS Bloat |
| /support/ | 1 | 49 | 0% | 37.1× | High JS Bloat |
| /api/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /terms/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /case-studies/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /help/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /demo/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /careers/ | 1 | 77 | 0% | 7.6× | High JS Bloat |
| /privacy/ | 1 | 77 | 0% | 9.8× | High JS Bloat |
| /about/ | 1 | 49 | 0% | 43.4× | High JS Bloat |
| /get-started/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /solutions/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /trust/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /blog/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
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🔌 API Access
Pull this data programmatically. All sub-page metrics are available via our public API.
curl https://seodiff.io/api/v1/deep10/domain/mozilla.orgGet your free API key — 100 requests/month included.
🔗 Similar infrastructure Sites
Domains with a similar tech stack, industry, and AI readiness profile to mozilla.org. Compare side-by-side.
| Domain | ACRI | AI Score | Tech Stack | Token Bloat | Schema | |
|---|---|---|---|---|---|---|
| mozilla.org (this site) | 61 | 80 | Custom / Proprietary | 4.9× | 0 | — |
| insuranceyet.com | 86 | 87 | Custom / Proprietary | 4.9× | 4 | Compare → |
| pubsandclubs.com.au | 86 | 87 | Custom / Proprietary | 4.9× | 4 | Compare → |
| melbourneschool.com | 86 | 87 | Custom / Proprietary | 5.0× | 4 | Compare → |
| educationdirectory.com.au | 86 | 87 | Custom / Proprietary | 5.1× | 4 | Compare → |
| kondela.hu | 86 | 93 | Custom / Proprietary | 3.1× | 4 | Compare → |
📊 Semantic Share of Voice
How often would an AI cite mozilla.org when users ask about topics in this domain's niche? We run entity queries through our 188k-page search index and measure citation probability.
Analyzing citation landscape…
Bait & Switch Delta
A 5 PAGESCompares your homepage rendering quality with inner pages. A high drift score means AI crawlers see a polished homepage but degraded inner content — the "bait & switch" that erodes trust.
Worst Inner Pages
E-E-A-T Trust Signals
C 40/100Trust indicators extracted from surface pages. These signals help AI systems verify your site's Experience, Expertise, Authoritativeness, and Trustworthiness.
Citation Profile
37 DOMAINSOutbound citation patterns across surface-crawled pages. Sites that cite diverse, authoritative sources signal higher E-E-A-T to AI systems.
AI trust scores for the domains mozilla.org links to. Citing high-trust sources lifts your own credibility signal.
Remediation Patches
COPY-PASTEAuto-generated code fixes tailored to mozilla.org. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Mozilla",
"url": "https://mozilla.org",
"logo": "https://www.mozilla.org/media/img/favicons/mozilla/apple-touch-icon.05aa000f6748.png",
"sameAs": []
}
</script>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "WebSite",
"name": "Mozilla",
"url": "https://mozilla.org",
"potentialAction": {
"@type": "SearchAction",
"target": "https://mozilla.org/search?q={search_term_string}",
"query-input": "required name=search_term_string"
}
}
</script>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is Mozilla?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Add your answer here — describe what Mozilla does in 1-2 sentences."
}
},
{
"@type": "Question",
"name": "How does Mozilla work?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Explain the key features and how users interact with Mozilla."
}
}
]
}
</script>
Projected Impact
ROI EST.If you apply the patches above, here's the estimated improvement for mozilla.org:
*Estimates based on SEODiff's scoring model. Actual results depend on implementation quality.
📋 Data Export
Download scores and metadata for audits, client reports, or CI/CD pipelines. Exports contain computed metrics only (no copyrighted content).
All data is generated automatically and updated with each crawl. JSON exports contain scores and metadata only (no copyrighted content).
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