meterfeeder.com
Weak AI visibility with 17 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Critical AEO gaps at 41/100 - meterfeeder.com is largely invisible to AI engines. Key strengths include Page Speed: Page Size, Entity Density, and Sentence Atomicity. Priority gaps: llms.txt File, Schema.org Structured Data, and Comprehensive FAQ Section.
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.
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.
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.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Top Opportunities10
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.
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.
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.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
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.
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.
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.
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.
Fix It With AI45
Score Breakdown
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Guides for the criteria with the most room for improvement