Weak AI visibility with 29 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 49/100 - multiple areas need attention. Key strengths include Table & List Extractability, Canonical URL Strategy, and Duplicate Content Blocks. Priority gaps: llms.txt File, Schema.org Structured Data, and Sitemap Completeness. Topic coherence is 4/10, which caps the overall score at 55. Focusing content on core expertise areas is the single highest-impact improvement.
How to Improve
Generate a comprehensive sitemap with lastmod dates for all important pages.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Add a machine-readable llms.txt file at your domain root that describes your site, services, and key pages for AI engines.
Create a comprehensive llms-full.txt with detailed page descriptions, content summaries, and topic taxonomy.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
62/95 images lack explicit width/height - the most common cause of layout shift (CLS)
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
Top Opportunities10
View allEnsure 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.
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.
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.
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.
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.
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.
Write self-contained definition sentences and single-claim statements that AI engines can quote directly. Avoid pronouns like "this" or "that" at the start of answer paragraphs.
Show direct use, testing, implementation, or lived experience with concrete observations, examples, screenshots, and lessons learned.
Establish a regular content publishing cadence with dated entries in your sitemap. Consistent publishing signals to AI engines that your site is an active, current information source.