The AI-Readiness profile for datacycle.cloud is strong: an ACRI of 69/100 places it ahead of 66% of domains in the index. Within the saas vertical, this places datacycle.cloud above the industry average of 57 —, suggesting strong competitive positioning in AI search. Server-side rendering keeps the ghost ratio near zero, giving AI systems direct access to all visible content. The 11.2× token bloat ratio falls within the normal range, though there is room to trim navigation, footer, and script overhead. Zero schema blocks puts this site at a disadvantage in knowledge graph and AI-answer pipelines that rely on explicit structured data. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.
🧮 Score Transparency — How is this calculated?
📊 ACRI Sub-Scores (AI Readiness Detail)
datacycle.cloud ranks much higher on Google (Tranco Top 50%+) than in AI search (Top 34%). This is the 'Invisible Giant' pattern — implement the patches above to close the AI gap. ACRI measures technical crawler readiness. Read the methodology →
Why datacycle.cloud 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
39/100 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 2
- ✓ Has <h2> headings — found 5
- ✓ <h2> not before <h1>
🔍 Indexability
- ✓ Canonical tag present →
https://open.datacycle.cloud/ - ✓ No noindex directive
- ✓ Meta viewport set
- ✓ HTML lang attribute →
de - ✗ Hreflang tags
- ✓ Googlebot allowed by robots.txt
🌐 Social / OpenGraph
- ✓ og:title — open.datacycle.cloud
- ✓ og:description — opendataCycle.Cloud opendataCycle .Cloud Neu, einzigartig, effizient: Open Data beschreibt Daten, die frei zur Verfügung gestellt, weiterverbreitet und genutzt werden können. Damit wird die Zusammenarbeit erleichtert und Synergien werden geschaffen. Wer seinen Content als Open Data zur Verfügung stellt, kann die Zusammenarbeit mit Partnern und Dienstleistern beschleunigen, vereinfachen und am Ende: mehr Reichweite und Sichtbarkeit schaffen. Funktionen & Ziele open!dataCycle.Cloud ist ein Projekt des auf Tourismus spezialisierten österreichischen Datenmanagementsystems dataCycle: Ein zentraler Daten-Hub für alle Arten von touristischen Datenmaterialien im DACH-Raum. Das Ziel: Destinationen und touristische Anbieter stellen ihre freien Daten (Copyrightfrei und entsprechend gekennzeichnet) wie z.B. Veranstaltungen, Point of Interest, von Restaurants etc. über diese Datenbank, entsprechend definierten Standards, für andere touristische Anbieter sowie Dienstleister und Plattformen zur Verfügung. Diese können dann auf das Datenmaterial, das bisher mühsam recherchiert und zusammengetragen werden musste, einfach und kostenlos zugreifen. Notwendig ist nur eine Registrierung. Einfacher Zugriff & individuelle Filterung Der Zugriff auf die Daten wird dabei so simpel wie möglich gestaltet: Über HTML-Widgets, über welche die Daten direkt angezeigt und verwaltet werden können. Sowie über eine von Developer einfach zu verwendende Datenschnittstelle. Das bedeutet in der Praxis: Ein Hotel kann beispielsweise, wenn seine Region die Daten auf der Plattform zur Verfügung gestellt hat, die Veranstaltungen seiner Region ganz einfach auf seiner Website für User abbilden. Mehr Nutzen & entscheidende Wettbewerbsvorteile Durch diese Verbesserung der gesamten zur Verfügung gestellten Datenbasis ergibt sich für Nutzer der open!dataCycle.cloud ein entscheidender Mehrwert: Die Zusammenführung von eigentlich unabhängigen Datenpools zu einer einzigen, konsistenten Datenbasis. Entscheidend für User, wenn sie zum Beispiel neben einer Veranstaltung auch gleich die notwendigen Wetterdaten mitgeliefert bekommen. Oder Seetemperaturen. Oder die Schneehöhe. Oder. Oder. Oder. Mehrwert schaffen: Die bereitgestellten Daten werden von unterschiedlichen, bereits vorhandenen Quellen für offene Daten übernommen und über den online Knowledge Graphen aufbereitet bzw. aufgewertet. Diese Aufwertung umfasst…
- ✗ og:image
- ✗ twitter:card
📐 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
64/100 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.
🔧 Tech Stack
Performance & Speed
49/100 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=10 - ✗ 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
50/100 15 % of Global Score 🟡 Medium 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 → 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 41/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.
<a href="https://seodiff.io/radar/domains/datacycle.cloud" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=datacycle.cloud" 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 saas Sites
Domains with a similar tech stack, industry, and AI readiness profile to datacycle.cloud. Compare side-by-side.
| Domain | ACRI | AI Score | Tech Stack | Token Bloat | Schema | |
|---|---|---|---|---|---|---|
| datacycle.cloud (this site) | 41 | 69 | WordPress | 11.2× | 0 | — |
| browsehappy.com | 39 | 71 | WordPress | 11.2× | 0 | Compare → |
| smilesoftware.com.mx | 41 | 68 | WordPress | 8.5× | 0 | Compare → |
| applykrdoo.com | 39 | 15 | WordPress | 11.1× | 1 | Compare → |
| sabadapp.com | 42 | 69 | WordPress | 11.8× | 1 | Compare → |
| cloudvip.net | 43 | 71 | WordPress | 11.6× | 1 | Compare → |
Remediation Patches
COPY-PASTEAuto-generated code fixes tailored to datacycle.cloud. 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": "Cloud",
"url": "https://datacycle.cloud",
"logo": "https://open.datacycle.cloud/wp-content/uploads/2023/07/Favicon-32x32.png",
"sameAs": []
}
</script>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "WebSite",
"name": "Cloud",
"url": "https://datacycle.cloud",
"potentialAction": {
"@type": "SearchAction",
"target": "https://datacycle.cloud/search?q={search_term_string}",
"query-input": "required name=search_term_string"
}
}
</script>
<!-- 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>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is Cloud?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Add your answer here — describe what Cloud does in 1-2 sentences."
}
},
{
"@type": "Question",
"name": "How does Cloud work?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Explain the key features and how users interact with Cloud."
}
}
]
}
</script>
Projected Impact
ROI EST.If you apply the patches above, here's the estimated improvement for datacycle.cloud:
*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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