lonza.shoes 58 D
🛡️ SEO 46 🤖 GEO 65 ⚡ Perf 39 🏗️ Arch 83

lonza.shoes — Global SEODiff Score 58/100

lonza.shoes
📊

At 73/100, the ACRI for lonza.shoes indicates strong fundamentals in AI extractability, surpassing the majority of indexed sites. Compared to other ecommerce sites (avg score: 57), lonza.shoes performs above the benchmark, suggesting strong competitive positioning in AI search. A ghost ratio of 30% indicates a mixed rendering strategy where core content loads server-side but interactive sections rely on JavaScript. The bloated 19.6× token ratio highlights an urgent need to clean up non-content markup, scripts, and navigation clutter. Only 1 schema block is present — adding Organization, WebSite, and Breadcrumb schemas would significantly improve structured data coverage. Robots.txt grants unrestricted access to the key AI user-agents, which is the strongest starting position for AI visibility.

58
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Performance (39) needs urgent attention.
🎯 Top Fix: Fix title tag length → +3 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 26, 2026 · 📋 API
Does your site score higher than lonza.shoes?
Run the same 40-signal audit on your own domain — free, instant results.
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)46 × 0.25 = 11.5
🤖 AI Readiness / GEO (40% weight)65 × 0.40 = 26.0
⚡ Performance (20% weight)39 × 0.20 = 7.8
🏗️ Architecture & Trust (15% weight)83 × 0.15 = 12.4
Weighted sum = 11.5 + 26.0 + 7.8 + 12.4
Global SEODiff Score = 58 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
84
Rendering
avg 93
51
Structure
avg 35
42
Schema
avg 10
55
Tech Stack
avg 64
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 40%
Rank #396828
-15 pts
Gap
AI (ACRI)
Top 24%
Score 73/100

lonza.shoes is more visible to Google than to AI models. There's room to improve AI discoverability to match your search reputation. ACRI measures technical crawler readiness. Read the methodology →

Why lonza.shoes ranks here

Tech stackExpress
Industryecommerce
RenderingHybrid
Schema coverage1 blocks
Token bloat19.6×

Fastest improvements

  • Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
  • Create an llms.txt file 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 →
🧪

JavaScript Rendering Check

We check what AI crawlers miss when they skip JavaScript execution.

Running headless browser to simulate AI extraction…
🛡️

Traditional SEO

46/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

74 chars
Too long

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

308 chars
Too long

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 5
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://lonza.shoes/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → uk
  • ✓ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — Взуття жіноче шкіряне від виробника ➡️ Lonza Shoes
  • ✓ og:description — Взуття жіноче купити ⭐ Lonza Shoes ⭐ Зимове, демісезонне, літнє шкіряне взуття для жінок від виробника ⇒ Мережа магазинів - Київ, Харків, Дніпро, Одеса ⇒ Працюємо 10 років в Україні!
  • ✓ og:image — preview
  • ✓ twitter:card — summary_large_image
📐 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

65/100 40 % of Global Score 🟢 High Confidence

This pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.

🔗

Citation Alternatives

Research
💡
Insight: In the ecommerce sector, stylekorean.com (ACRI: 88) currently has stronger AI extractability. AI models tend to prefer sources with higher semantic structure and schema coverage. Domains with ACRI < 40 see 3.5× more hallucinations. Read the research →
lonza.shoes
53
Your ACRI Score
88
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. stylekorean.com has schema coverage of 4 blocks and uses Custom / Proprietary. Improve your score by implementing the remediation patches below.
📊 Side-by-Side Comparison →
🚨

Hallucination Risk

Research

Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.

👻
Shadow Content Detected: 30% of your page token budget is trapped in non-rendered regions (JavaScript-dependent content invisible to AI crawlers). Combined with 19.6x token bloat, AI models are using most of their context window on noise instead of your real content. This dramatically increases hallucination probability — models fill the gap with made-up facts.
Analyzing hallucination risk…

🤖 Bot Access Matrix

GPTBot (OpenAI)
Allowed
ClaudeBot (Anthropic)
Allowed
CCBot (Common Crawl)
Allowed
Google-Extended
Allowed
Googlebot
Allowed

👻 Rendering (Ghost Ratio) Docs

Ghost Ratio 30%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type Hybrid

📊 Structure & Information Density Docs

Structure Grade 51/100 — Fair
Structured Elements 113 elements (113 lists, 0 rows, 0 headers)
Total Words1444
Raw Density7.8%

🏷️ Schema Health Docs

Organization Schema ✅ Present
Product / Service Schema ⚠️ Not Found
Total Schema Blocks1 block(s) — Basic (low value for AI)

Schema Coverage Map

1/7 schema types detected
✅ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Product / Service schema missing. AI models don't know this is a SaaS product. Add Product or SoftwareApplication schema so AI understands what you offer and can surface pricing/features.
💡BreadcrumbList schema missing. AI cannot understand your site hierarchy or how pages relate to each other.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.
💡WebSite schema missing. Add WebSite + SearchAction so Google can generate a Sitelinks Search Box for your brand in AI results.

📐 AI Efficiency Metrics Docs

52
AI Extractability
High
Crawl Cost
None
Blocklist Risk
Extractability52/100 — AI models can partially extract answers from this page
Crawl CostHigh (75/100) — expensive for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

5%
🗑️ 95%
Useful Content (17.6 KB)Bloat (326.7 KB)
Token Bloat Ratio19.6× — Heavy

Multimodal Readiness

Visual Context99% Optimized for Vision
Image Alt Coverage88 / 89 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 94.9% · SNR: 0.05 · Signal: 4502 / Noise: 83636 tokens

🔬 AI-Crawler Simulation

See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.

🌐
This is what humans see — styled, branded, visual.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
🤖

AI Answer Preview

NEW

See how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.

Simulating AI extraction…

🔧 Tech Stack

FrameworkExpress
AI-Readiness Score55/100
Servernginx
CDN
HTTP Status200
Load Time1142 ms
Raw HTML Size344.3 KB
Visible Text Size17.6 KB

Performance & Speed

39/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1142 ms
Slow — bots may time out or deprioritise

Google considers <200 ms "good". AI crawlers may have even shorter timeouts.

📦 Page Weight

2003
DOM nodes
344 KB
HTML payload
Heavy page — consider reducing DOM complexity

🗄️ Cache & CDN

  • ✗ Cache-Control header
  • ✗ CDN cache status
  • ✗ CDN detected

🔬 Tracker Tax

0
tracker scripts
0
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
📐 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

83/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://lonza.shoes/sitemap.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

204
internal links
2
external links
Good internal linking — helps crawlers discover content

🔒 Security & Trust

  • ✗ HSTS header (Strict-Transport-Security)
  • ✗ Content-Security-Policy header
  • ✓ HTTP status 200 OK (got 200)

♿ Accessibility Signals

  • ✓ HTML lang attribute → uk
  • ✓ 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 53/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for lonza.shoes
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/lonza.shoes" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=lonza.shoes" 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 1 pages · Deep-10

Homepage ACRI
53
Single-page score
-12
Moderate hidden bloat
Δ delta
Site-Wide ACRI
41
Avg across 1 pages · Range 41–41
🔍
Hidden Bloat Detected

Homepage scores 53, but internal pages average only 41 — a -12-point gap. Blogs, docs, and legacy content are dragging down AI readability site-wide.

Total Words
126
Avg Bloat
325.0×
Ext. Citations
2
Page Type ACRI Token Bloat Words Status
https://lonza.shoes/blog
Блоги та новини Lonza Shoes
pricing 41 325.0× 126 💰 Pricing
🔗
Outbound External Citations
2 unique external domains cited across 1 pages
instagram.com ×1
facebook.com ×1
🔄 Re-Crawl & Update 📡 Track this Domain

Scores update automatically each month. Create a free account for on-demand re-crawls (3/month free).

🔌 API Access

Pull this data programmatically. All sub-page metrics are available via our public API.

curl https://seodiff.io/api/v1/deep10/domain/lonza.shoes

Get your free API key — 100 requests/month included.

🔗 Similar ecommerce Sites

Domains with a similar tech stack, industry, and AI readiness profile to lonza.shoes. Compare side-by-side.

Domain ACRI AI Score Tech Stack Token Bloat Schema
lonza.shoes (this site) 53 73 Express 19.6× 1
tritonshowers.co.uk 53 76 Express 19.1× 1 Compare →
kandk.co.nz 52 77 Express 20.3× 1 Compare →
citarella.com 51 74 Express 19.2× 1 Compare →
suning.com 54 76 Express 19.8× 0 Compare →
skribis.be 52 72 Express 17.5× 1 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to lonza.shoes. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

Add WebSite + SearchAction JSON-LD
High Impact ⏱ 5 min
Enables the Sitelinks Search Box in Google and allows AI to understand your site structure.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Shoes",
  "url": "https://lonza.shoes",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://lonza.shoes/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Reduce Token Bloat
Medium Impact ⏱ 1–2 hrs
Only 5% of your HTML is useful content. AI crawlers waste context window tokens on bloat.
html
<!-- Move inline CSS to external stylesheets -->
<link rel="stylesheet" href="/css/main.css">

<!-- Move inline scripts to external files with defer -->
<script src="/js/app.js" defer></script>

<!-- Remove duplicate navigation blocks -->
<!-- Keep only ONE <nav> in the <header> -->

<!-- Ensure <main> wraps your primary content -->
<main>
  <!-- Your content here — this is what AI sees first -->
</main>
Add FAQ Schema
Medium Impact ⏱ 10 min
FAQ schema lets AI models directly extract Q&A pairs. This is the easiest way to get featured in AI responses.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Shoes?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Shoes does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Shoes work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Shoes."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for lonza.shoes:

Current Score
73
Projected Score
85
Improvement
+12 pts
Add WebSite schema +4 pts
Reduce token bloat +5 pts
Add FAQ schema +3 pts

*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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🧭 Self-Diffing (Private Layer)

For owned domains, combine this world snapshot with private drift + regression history.
Template Drift
Track in My Site
Drift → Traffic Impact
In development coming soon
Regression Incidents
Track in My Site
Internal Linking
Deep Audit graph
Semantic Structure
GEO view in Deep Audit
Content Quality
Thin/duplicate tracking

🕒 History

Score over timeAvailable in My Site history
Drift eventsTemplate timeline + incidents
Drift → Revenue AttributionComing soon
Schema/rendering/extractability changesTracked per scan in project history