micobotnia.fi 79 B
🛡️ SEO 74 🤖 GEO 80 ⚡ Perf 74 🏗️ Arch 88

micobotnia.fi — Global SEODiff Score 79/100

micobotnia.fi
📊

With a solid 80/100 ACRI, micobotnia.fi is well-positioned for AI search — better than 94% of sites in the Radar. Content is delivered server-side, meaning bots and AI agents can parse the full page without executing JavaScript. The 8.2× token bloat ratio falls within the normal range, though there is room to trim navigation, footer, and script overhead. Minimal structured data (1 block) limits the site's ability to communicate entity relationships to AI systems. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

79
B — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (74) is your bottleneck.
🎯 Top Fix: Monitor weekly to catch regressions early
🔬 Automated SEODiff Assessment · Snapshot: Mar 20, 2026 · 📋 API
📈 ACRI Trend 3 snapshots
Mar 7 Mar 20
🔔 Recent AI Indexing Activity
No recent changes detected by adaptive crawler.
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)74 × 0.25 = 18.5
🤖 AI Readiness / GEO (40% weight)80 × 0.40 = 32.0
⚡ Performance (20% weight)74 × 0.20 = 14.8
🏗️ Architecture & Trust (15% weight)88 × 0.15 = 13.2
Weighted sum = 18.5 + 32.0 + 14.8 + 13.2
Global SEODiff Score = 79 (B)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
100
Rendering
avg 93
53
Structure
avg 35
42
Schema
avg 9
85
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 50%+
Rank #693113
-63 pts
Gap
AI (ACRI)
Top 6%
Score 80/100

micobotnia.fi ranks much higher on Google (Tranco Top 50%+) than in AI search (Top 6%). This is the 'Visibility Gap' pattern — implementing the recommendations above can help close the AI gap. ACRI measures technical crawler readiness. Read the methodology →

Why micobotnia.fi ranks here

Tech stackWordPress
Industry
RenderingSSR
Schema coverage1 blocks
Token bloat8.2×

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

74/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

21 chars
Too short

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

165 chars
Too long

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 7
  • ✓ <h2> not before <h1>

🔍 Indexability

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

🌐 Social / OpenGraph

  • ✓ og:title — Etusivu - Mico Botnia
  • ✓ og:description — Olemme kasvava ja kehittyvä palveluyhtiö, jonka 110 asiantuntijaa varmistavat asiakkaillemme sujuvat talous- ja palkkapalvelut sekä tulkki- ja käännöspalvelut.
  • ✗ og:image
  • ✓ 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

80/100 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.

🚨

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 53/100 — Fair
Structured Elements 34 elements (34 lists, 0 rows, 0 headers)
Total Words404
Raw Density8.4%

🏷️ Schema Health Docs

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

Schema Coverage Map

3/7 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.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.

📐 AI Efficiency Metrics Docs

64
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability64/100 — AI models can partially extract answers from this page
Crawl CostLow (30/100) — efficient for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

12%
🗑️ 88%
Useful Content (8.1 KB)Bloat (58.5 KB)
Token Bloat Ratio8.2× — Normal

Multimodal Readiness

Visual Context30% Optimized for Vision
Image Alt Coverage3 / 10 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Only 30% 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: 87.9% · SNR: 0.14 · Signal: 2069 / Noise: 14987 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…
🧠

The LLM Interpretation

AI-VERIFIED

SEODiff AI analyzed the extracted content of micobotnia.fi 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.

Core Offering
This service provides financial and payroll solutions with translation services.
Target Audience
Financial professionals, businesses requiring payroll services, translation agencies
Pricing Model
⚠ SEMANTIC VOID
🛡️ Compliance Standards
GDPR
🏆 Competitive Moat
Data-driven insights for improved user experience and website performance.
📊 Content Depth
2/10
⚡ Key Pain Points
• Lack of clear pricing information
• Complex cookie consent management
Analyzed by SEODiff AI · 2026-04-01

🔧 Tech Stack

FrameworkWordPress
AI-Readiness Score85/100
Servernginx
CDN
HTTP Status200
Load Time818 ms
Raw HTML Size66.6 KB
Visible Text Size8.1 KB

Performance & Speed

74/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

818 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

432
DOM nodes
67 KB
HTML payload
Lean page — fast for bots and users

🗄️ 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

88/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

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

🔗 Linking

55
internal links
1
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 → fi
  • ✓ 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 57/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

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

Homepage ACRI
57
Single-page score
-53
Severe hidden bloat
Δ delta
Site-Wide ACRI
4
Avg across 10 pages · Range 0–44
🔍
Hidden Bloat Detected

Homepage scores 57, but internal pages average only 4 — a -53-point gap. Blogs, docs, and legacy content are dragging down AI readability site-wide.

Total Words
194
Avg Bloat
4.5×
Page Type ACRI Token Bloat Words Status
https://micobotnia.fi/contact
Contact details - Mico Botnia
support 44 45.3× 194
https://micobotnia.fi/pricing pricing 0 0.0× 0
https://micobotnia.fi/about about 0 0.0× 0
https://micobotnia.fi/features product 0 0.0× 0
https://micobotnia.fi/products product 0 0.0× 0
https://micobotnia.fi/docs docs 0 0.0× 0
https://micobotnia.fi/blog blog 0 0.0× 0
https://micobotnia.fi/case-studies social-proof 0 0.0× 0
https://micobotnia.fi/integrations integrations 0 0.0× 0
https://micobotnia.fi/faq support 0 0.0× 0
📂
Health by Sub-Directory
Average ACRI and top issues aggregated by URL path prefix
Path Pages Avg ACRI Ghost % Bloat Top Issue
/docs/ 1 0 0% 0.0× Low AI Readiness
/blog/ 1 0 0% 0.0× Low AI Readiness
/case-studies/ 1 0 0% 0.0× Low AI Readiness
/about/ 1 0 0% 0.0× Low AI Readiness
/integrations/ 1 0 0% 0.0× Low AI Readiness
/pricing/ 1 0 0% 0.0× Low AI Readiness
/contact/ 1 44 0% 45.3× High JS Bloat
/faq/ 1 0 0% 0.0× Low AI Readiness
/products/ 1 0 0% 0.0× Low AI Readiness
/features/ 1 0 0% 0.0× Low AI Readiness
🔗
Outbound External Citations
0 unique external domains cited across 10 pages
wordpress.org ×1
🔄 Re-Crawl & Update 📡 Track this Domain

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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/micobotnia.fi

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

🔗 Similar Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
micobotnia.fi (this site) 57 80 WordPress 8.2× 1
csucc.edu.ph 67 77 WordPress 8.4× 1 Compare →
resellerme.com 67 83 WordPress 9.6× 1 Compare →
personifycloud.com 67 82 WordPress 6.6× 1 Compare →
sgr777foods.com 67 85 WordPress 5.0× 1 Compare →
mondu.ai 67 80 WordPress 10.4× 2 Compare →
Compare All 5 Similar Sites →

📊 Semantic Share of Voice

How often would an AI cite micobotnia.fi 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…

🩹

Remediation Patches

COPY-PASTE

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

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 Micobotnia?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Micobotnia does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Micobotnia work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Micobotnia."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for micobotnia.fi:

Current Score
80
Projected Score
86
Improvement
+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
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