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runrun.it

runrun.it

Weak AI visibility with 25 of 48 criteria passing. Biggest gap: llms.txt file.

47/100
D
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
7/10
Content Structure
~25% weight
2/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
4/10
AI Discovery
~10% weight
5/10

Verdict

Below-average AEO readiness at 47/100 - multiple areas need attention. Key strengths include Fact & Data Density, Content Cannibalization, and First-Hand Experience Signals. Priority gaps: llms.txt File, Schema.org Structured Data, and Q&A Content Format. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

#7150of 13363
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How to Improve

Current
47/100
Projected
79/100
40Total Fixes
13Quick Wins
~81hEst. Effort
Quick Wins
Create /llms.txt fileFix HTML structure and meta tagsConfigure robots.txt for AI crawlersLink orphan pages into site navigationAdd ai.txt and content licensingFix canonical URL strategyImprove query-answer alignmentAdd visible date signalsFocus blog content on core expertisePackage evidence for AI enginesReduce extraction frictionAdd image context for AI enginesImprove server response efficiency
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Fix HTML structure and meta tags
high|low
Configure robots.txt for AI crawlers
high|trivial
Fix canonical URL strategy
critical|low
Improve server response efficiency
high|low
Create complete sitemap.xml
low|low
Reduce document weight
low|low
Add internationalization signals
medium|low

Top Opportunities10

Add more proper nouns throughout content - named sources, organizations, tools, studies, and locations. Cited text averages 20.6% proper nouns; most sites fall well below 15%.

Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.

Use HTML tables for comparison data and ordered/unordered lists for features, steps, and specifications. Structured data formats are directly extractable by AI engines for answers.

Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.

Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.

Publish original research, statistics, case studies, or proprietary data that AI engines can cite. Unique data points make your content a primary source rather than a derivative one.

Place a concise 40-80 word answer block in the first 300 words of each page. Avoid throat-clearing openers like "In this article..." and lead with the answer.

Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.

Include dateModified schema, visible last-updated dates, and time elements on content pages. Fresh content signals help AI engines prioritize your pages over stale alternatives.

Strengthen internal linking with descriptive anchor text between related pages. Add breadcrumb navigation and ensure every key page is reachable within 3 clicks from the homepage.

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Site Pages

runrun.it/en-US/how-runrun-it-worksD48
Tour | Learn about the features for work tracking and project management solution - Runrun.it
runrun.it/en-US/clientsD48
Teamwork generates productivity | Runrun.it Case Studies
runrun.it/en-GBD48
Runrun.it | Process and Projects Manager
runrun.it/pt-BRD48
Runrun.it | Gerenciador de Processos e Projetos

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