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runlocal.ai
SUMMER 2024

runlocal.ai

Weak AI visibility with 26 of 48 criteria passing. Biggest gap: llms.txt file.

Developer Tools & InfrastructureDeveloper Platforms
49/100
2 since v1
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
5/10
Content Structure
~25% weight
6/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
4/10

Verdict

Below-average AEO readiness at 49/100 - multiple areas need attention. Key strengths include Schema.org Structured Data, Canonical URL Strategy, and Query-Answer Alignment. Priority gaps: llms.txt File, RSS/Atom Feed, and Table & List Extractability. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

How to Improve

Current
49/100
Projected
80/100
40Total Fixes
13Quick Wins
~88hEst. Effort
Quick Wins
Create /llms.txt fileStrengthen entity authority (NAP)Configure robots.txt for AI crawlersBuild FAQ sections with schemaAdd direct answer paragraphsAdd ai.txt and content licensingAdd visible date signalsFocus blog content on core expertiseAdd first-hand experience signalsMake content creators clearly visibleExplain how content was tested or reviewedAdd answer-first content placementPackage evidence for AI engines
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Configure robots.txt for AI crawlers
high|trivial
Create complete sitemap.xml
medium|low
Add internationalization signals
critical|medium
Fix HTML structure and meta tags
low|low
Improve server response efficiency
low|low
Reduce render-blocking resources
low|low
Reduce document weight
low|low

Top Opportunities10

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.

Expand articles to 1000+ words with structured H2/H3 sections, comparison tables, and expert analysis. Thin content (under 300 words) is rarely cited by AI engines. Deep, well-structured articles demonstrate expertise.

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.

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.

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

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.

Add Organization schema with consistent name, address, phone (NAP). Include sameAs links to social profiles and authoritative directories to strengthen entity recognition.

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.

Add specific numbers, percentages, statistics, and data points throughout your content. Fact-dense content gives AI engines concrete data to cite rather than vague claims.

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Site Pages

www.runlocal.aiD44
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www.runlocal.ai/book-demoF25
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Changes since v1Last audited 70 days ago
47
49
+2
View full comparison →
Add Original Data & Case StudiesIncrease Content DepthFocus Content on Core TopicsAdd Structured Tables & ListsImprove Internal Linking ArchitectureAdd Direct Answer ParagraphsAdd Owned Data SignalsStrengthen Entity Authority (NAP)Add Content Freshness SignalsIncrease Fact & Data Density

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