Weak AI visibility with 28 of 48 criteria passing. Biggest gap: content cannibalization.
Verdict
Below-average AEO readiness at 46/100 - multiple areas need attention. Key strengths include llms.txt File, Schema.org Structured Data, and RSS/Atom Feed. Priority gaps: Content Cannibalization, Evidence Packaging, and Owned Data Density. HTTPS is not enabled, which caps several criteria scores and reduces AI crawler trust. Topic coherence is 4/10, which caps the overall score at 55. Focusing content on core expertise areas is the single highest-impact improvement.
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Guides for the criteria with the most room for improvement
You have three pages about "live chat pricing." AI doesn't know which one to cite - so it cites none. Content cannibalization is when your own content competes with itself, splitting the authority signal and confusing AI engines.
A statistic without a source is a liability. A claim without attribution is invisible. We track evidence packaging across every audit and the pattern is clear - sites that cite their sources get cited by AI. Sites that state facts without attribution get skipped.
AI can't see your images. It reads the markup around them. A product photo with alt="image1.jpg" tells AI nothing. A figure with a descriptive figcaption and 8-word alt text tells AI exactly what it's looking at - and that context feeds directly into citation decisions.
No date on your page? AI engines treat it like a rumor -undated and deprioritized. Here's how we audit whether your timestamps are actually machine-readable.
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