Moderate AI visibility with 38 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 59/100 - multiple areas need attention. Key strengths include Internal Linking Structure, Content Freshness Signals, and Sitemap Completeness. Priority gaps: llms.txt File, Comprehensive FAQ Section, and Speakable Schema.
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.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
Top Opportunities10
View allAdd question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
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.
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 inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.
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.
Show direct use, testing, implementation, or lived experience with concrete observations, examples, screenshots, and lessons learned.
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.
Sections within pages contain identical or near-identical text. LLMs may flag this as low-quality or thin content, reducing citation authority. Rewrite duplicate blocks with unique angles.
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.