Moderate AI visibility with 36 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 55/100 - multiple areas need attention. Key strengths include Original Data & Expert Analysis, Fact & Data Density, and Canonical URL Strategy. Priority gaps: llms.txt File, Comprehensive FAQ Section, and RSS/Atom Feed. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.
How to Improve
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.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Generate a comprehensive sitemap with lastmod dates for all important pages.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
762/861 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.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
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.
Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.
Create a dedicated FAQ page with FAQPage schema markup. Cover common questions about your products, services, and industry to become a direct answer source for AI engines.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
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.
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.
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.
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.
Define the primary entity in the first 500 characters, use consistent terminology (same term 70%+), and add "unlike X" signals to help AI engines distinguish your topics.