Moderate AI visibility with 33 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 53/100 - multiple areas need attention. Key strengths include Clean, Crawlable HTML, RSS/Atom Feed, and Table & List Extractability. Priority gaps: llms.txt File, Canonical URL Strategy, and Speakable Schema.
How to Improve
1 sampled page(s) carry a noindex 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.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Add rel="canonical" tags to all pages to prevent duplicate content confusion.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
78/120 images lack explicit width/height - the most common cause of layout shift (CLS)
Generate a comprehensive sitemap with lastmod dates for all important pages.
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 allPublish 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.
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.
Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
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.
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 question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
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.