Moderate AI visibility with 32 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 54/100 - multiple areas need attention. Key strengths include Schema.org Structured Data, Query-Answer Alignment, and Duplicate Content Blocks. Priority gaps: llms.txt File, RSS/Atom Feed, and Canonical URL Strategy. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.
How to Improve
Generate a comprehensive sitemap with lastmod dates for all important pages.
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.
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.
25/40 images lack explicit width/height - the most common cause of layout shift (CLS)
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
Top Opportunities10
View allExpand 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.
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.
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.
Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.
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.
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.
Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
The same paragraphs appear on multiple pages. AI engines may only index one version and ignore the rest. Rewrite shared content so each page offers a unique perspective.
Show direct use, testing, implementation, or lived experience with concrete observations, examples, screenshots, and lessons learned.