deutschakademie.de 69 C
🛡️ SEO 64 🤖 GEO 87 ⚡ Perf 27 🏗️ Arch 86

deutschakademie.de — Global SEODiff Score 69/100

deutschakademie.de
📊

The AI-Readiness profile for deutschakademie.de is strong: an ACRI of 80/100 places it ahead of 94% of domains in the index. Within the developer vertical, this places deutschakademie.de above the industry average of 57 —, suggesting strong competitive positioning in AI search. The low ghost ratio (0%) confirms that what crawlers see matches what users see — a hallmark of strong SSR implementation. The token bloat ratio sits at a lean 4.1×, meaning the ratio of code to visible content is efficient — crawlers spend their token budget on actual information. 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.

69
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Performance (27) is your bottleneck.
🎯 Top Fix: Monitor weekly to catch regressions early
🔬 Automated SEODiff Assessment · Snapshot: Feb 26, 2026 · 📋 API
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)64 × 0.25 = 16.0
🤖 AI Readiness / GEO (40% weight)87 × 0.40 = 34.8
⚡ Performance (20% weight)27 × 0.20 = 5.4
🏗️ Architecture & Trust (15% weight)86 × 0.15 = 12.9
Weighted sum = 16.0 + 34.8 + 5.4 + 12.9
Global SEODiff Score = 69 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
100
Rendering
avg 93
79
Structure
avg 35
2
Schema
avg 10
85
Tech Stack
avg 64
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 25%
Rank #247641
-18 pts
Gap
AI (ACRI)
Top 6%
Score 80/100

deutschakademie.de ranks much higher on Google (Tranco Top 25%) than in AI search (Top 6%). This is the 'Invisible Giant' pattern — implement the patches above to close the AI gap. ACRI measures technical crawler readiness. Read the methodology →

Why deutschakademie.de ranks here

Tech stackWordPress
Industrydeveloper
RenderingSSR
Schema coverage1 blocks
Token bloat4.1×

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

64/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

58 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

135 chars
Good length

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✗ Exactly 1 <h1> tag — found 2
  • ✓ Has <h2> headings — found 14
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.deutschakademie.de/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → de-DE
  • ✗ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — Deutschkurs vor Ort oder online – jeden Monat neue Kurse
  • ✓ og:description — Deutschkurse für alle Level: A1-C2. Intensiv oder semi-intensiv, kostenpflichtig oder kostenlos – für Alltag, Beruf und Prüfungen.
  • ✓ 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

87/100 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 developer sector, hikkoshizamurai.jp (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 →
deutschakademie.de
73
Your ACRI Score
88
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. hikkoshizamurai.jp has schema coverage of 5 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.

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

📊 Structure & Information Density Docs

Structure Grade 79/100 — Good
Structured Elements 326 elements (326 lists, 0 rows, 0 headers)
Total Words1752
Raw Density18.6%

🏷️ Schema Health Docs

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

Schema Coverage Map

2/7 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.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.

📐 AI Efficiency Metrics Docs

69
AI Extractability
Medium
Crawl Cost
None
Blocklist Risk
Extractability69/100 — AI models can partially extract answers from this page
Crawl CostMedium (60/100) — moderate for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

24%
🗑️ 76%
Useful Content (81.4 KB)Bloat (256.1 KB)
Token Bloat Ratio4.1× — Lean

Multimodal Readiness

Visual Context57% Optimized for Vision
Image Alt Coverage31 / 54 images have alt text

TDM Rights

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

🔥 Structural Entropy Check Research

23 Entropy
Poor Token Bloat: High
Noise Ratio: 75.9% · SNR: 0.32 · Signal: 20848 / Noise: 65556 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

FrameworkWordPress
AI-Readiness Score85/100
ServerApache
CDN
HTTP Status200
Load Time4145 ms
Raw HTML Size337.5 KB
Visible Text Size81.4 KB

Performance & Speed

27/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

4145 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

2319
DOM nodes
338 KB
HTML payload
Heavy page — consider reducing DOM complexity

🗄️ Cache & CDN

  • ✓ Cache-Control header → no-store, no-cache, must-revalidate
  • ✗ 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

86/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://www.deutschakademie.de/sitemap_index.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

342
internal links
18
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 → de-DE
  • ✓ 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 73/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

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

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
deutschakademie.de (this site) 73 80 WordPress 4.1× 1
wavevms.com 74 85 WordPress 4.1× 1 Compare →
onestopplus.com 74 87 WordPress 4.2× 1 Compare →
globalplatform.org 73 84 WordPress 3.3× 1 Compare →
lesen.net 73 84 WordPress 5.0× 1 Compare →
iscparis.com 72 79 WordPress 4.5× 1 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to deutschakademie.de. 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": "Deutschakademie",
  "url": "https://deutschakademie.de",
  "logo": "https://www.deutschakademie.de/wp-content/themes/deagweb/assets/favicon/apple-icon-57x57.png",
  "sameAs": []
}
</script>
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 Deutschakademie?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Deutschakademie does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Deutschakademie work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Deutschakademie."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for deutschakademie.de:

Current Score
80
Projected Score
92
Improvement
+12 pts
Add Organization schema +6 pts
Reduce token bloat +3 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