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bodysim.com
SUMMER 2019

bodysim.com

Moderate AI visibility with 27 of 48 criteria passing. Biggest gap: llms.txt file.

53/100
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
7/10
Trust & Authority
~15% weight
4/10
Technical Foundation
~10% weight
4/10
AI Discovery
~10% weight
4/10

Verdict

Below-average AEO readiness at 53/100 - multiple areas need attention. Key strengths include Table & List Extractability, Fact & Data Density, and Content Cannibalization. Priority gaps: llms.txt File, Schema.org Structured Data, and RSS/Atom Feed. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

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How to Improve

Current
53/100
Projected
78/100
43Total Fixes
15Quick Wins
~90hEst. Effort
Quick Wins
Create /llms.txt fileAdd question-based headingsConfigure robots.txt for AI crawlersLink orphan pages into site navigationAdd definition-style contentAdd ai.txt and content licensingEnhance author and expert schemaFix canonical URL strategyAdd visible date signalsIncrease content depth and structureImprove citation-ready writing qualityReduce extraction frictionFix duplicate content blocksEliminate cross-page duplicate contentImprove server response efficiency
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Configure robots.txt for AI crawlers
critical|low
Fix canonical URL strategy
critical|low
Fix HTML structure and meta tags
low|low
Add internationalization signals
critical|medium
Improve server response efficiency
high|low
Reduce render-blocking resources
medium|low
Reduce document weight
low|low
Create complete sitemap.xml
low|low

Top Opportunities10

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.

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.

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 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%.

Write 20-25 word self-contained answer sentences immediately after each H2 heading. 72.4% of AI-cited posts use this pattern - it gives engines a ready-made snippet to quote.

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

Implement JSON-LD structured data (Organization, Service, Product, FAQPage) on key pages. Schema markup helps AI engines extract and cite your content accurately.

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

Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.

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