Weak AI visibility with 1 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Critical AEO gaps at 3/100 - [email protected] is largely invisible to AI engines. Priority gaps: llms.txt File, Schema.org Structured Data, and Q&A Content Format. HTTPS is not enabled, which caps several criteria scores and reduces AI crawler trust. Topic coherence is 0/10, which caps the overall score at 35. Focusing content on core expertise areas is the single highest-impact improvement.
How to Improve
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
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.
Generate a comprehensive sitemap with lastmod dates for all important pages.
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.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
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.
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.
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.
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.
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.
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%.
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.
Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.
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.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.