vlerick.com 60 C
🛡️ SEO 50 🤖 GEO 60 ⚡ Perf 56 🏗️ Arch 83

vlerick.com — Global SEODiff Score 60/100

vlerick.com
📊

At 77/100, the ACRI for vlerick.com indicates strong fundamentals in AI extractability, surpassing the majority of indexed sites. In the education sector, vlerick.com outperforms the average (57), suggesting strong competitive positioning in AI search. Content is delivered server-side, meaning bots and AI agents can parse the full page without executing JavaScript. Heavy markup overhead (50.0× bloat) forces AI systems to wade through excess code before finding useful information. The complete absence of JSON-LD schema is a missed opportunity: even basic Organization markup would improve how AI crawlers understand this domain. Robots.txt grants unrestricted access to the key AI user-agents, which is the strongest starting position for AI visibility.

60
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (50) is your bottleneck.
🎯 Top Fix: Reduce token bloat (118×) → +5–10 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 26, 2026 · 📋 API
Does your site score higher than vlerick.com?
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)50 × 0.25 = 12.5
🤖 AI Readiness / GEO (40% weight)60 × 0.40 = 24.0
⚡ Performance (20% weight)56 × 0.20 = 11.2
🏗️ Architecture & Trust (15% weight)83 × 0.15 = 12.4
Weighted sum = 12.5 + 24.0 + 11.2 + 12.4
Global SEODiff Score = 60 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
77
Structure
avg 35
0
Schema
avg 10
70
Tech Stack
avg 64
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 23%
Rank #225412
-8 pts
Gap
AI (ACRI)
Top 14%
Score 77/100

vlerick.com 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 vlerick.com ranks here

Tech stackNext.js
Industryeducation
RenderingSSR
Schema coverage0 blocks
Token bloat50×+

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.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

50/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

49 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

84 chars
Too short

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 8
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.vlerick.com/en/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en
  • ✓ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — Homepage
  • ✓ og:description — A place where entrepreneurial dreams are born and game-changing ideas become reality
  • ✓ 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

60/100 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 education sector, rndirectors.com (ACRI: 85) 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 →
vlerick.com
47
Your ACRI Score
85
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. rndirectors.com has schema coverage of 4 blocks and uses WordPress. 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.

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 5%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 77/100 — Good
Structured Elements 70 elements (70 lists, 0 rows, 0 headers)
Total Words394
Raw Density17.8%

🏷️ Schema Health Docs

Organization Schema ❌ Missing
Product / Service Schema ⚠️ Not Found
Total Schema Blocks0 — No JSON-LD detected

Schema Coverage Map

0/7 schema types detected
❌ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Organization schema missing. AI models cannot identify your brand entity. Without it, your brand won't appear in Knowledge Panels or be associated with your content.
💡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

49
AI Extractability
High
Crawl Cost
None
Blocklist Risk
Extractability49/100 — AI models can partially extract answers from this page
Crawl CostHigh (80/100) — expensive for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

1%
🗑️ 99%
Useful Content (2.7 KB)Bloat (314.2 KB)
Token Bloat Ratio50×+ — Bloated

Multimodal Readiness

Visual Context38% Optimized for Vision
Image Alt Coverage10 / 26 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Your HTML is 316.9 KB, but only 2.7 KB is text. 1% useful / 99% bloat. AI crawlers have limited context windows (e.g. 128k tokens). This level of bloat (50×+) risks context-window truncation by ChatGPT, Claude, and Gemini. Reduce inline scripts, CSS, hydration payloads, and tracking code.
💡Only 38% of images have alt text. Add descriptive alt attributes so multimodal AI (ChatGPT Vision) can understand your images.

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 99.2% · SNR: 0.01 · Signal: 686 / Noise: 80442 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

FrameworkNext.js
AI-Readiness Score70/100
ServerVercel
CDNvercel
HTTP Status200
Load Time1549 ms
Raw HTML Size316.9 KB
Visible Text Size2.7 KB

Performance & Speed

56/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1549 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

507
DOM nodes
317 KB
HTML payload
Heavy page — consider reducing DOM complexity

🗄️ Cache & CDN

  • ✓ Cache-Control header → public, max-age=0, must-revalidate
  • ✗ CDN cache status
  • ✓ CDN detected → vercel

🔬 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://www.vlerick.com/sitemap.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

66
internal links
10
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 → en
  • ✓ 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 47/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for vlerick.com
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/vlerick.com" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=vlerick.com" 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.

🔗 Similar education Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
vlerick.com (this site) 47 77 Next.js 118.3× 0
foxitsoftware.com 48 70 Next.js 117.9× 0 Compare →
foxit.com 48 70 Next.js 117.9× 0 Compare →
worldtesolacademy.com 47 68 Next.js 119.9× 1 Compare →
unw.ac.id 45 77 Next.js 122.1× 0 Compare →
unitestudents.com 42 71 Next.js 117.6× 1 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

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

Add Organization JSON-LD
High Impact ⏱ 5 min
AI models cannot identify your brand entity without Organization schema. This is the #1 fix for AI visibility.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Vlerick",
  "url": "https://vlerick.com",
  "logo": "https://vlerick.com/favicon.ico",
  "sameAs": []
}
</script>
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": "Vlerick",
  "url": "https://vlerick.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://vlerick.com/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Reduce Token Bloat
Medium Impact ⏱ 1–2 hrs
Only 0% 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 Vlerick?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Vlerick does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Vlerick work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Vlerick."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for vlerick.com:

Current Score
77
Projected Score
95
Improvement
+18 pts
Add Organization schema +6 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