AI Visibility for Healthcare: Accuracy, Trust and YMYL Constraints
How healthcare organisations earn AI citations under YMYL constraints: clinical authorship, guideline alignment, review dates and the information-versus-advice boundary.

How healthcare organisations earn AI citations under YMYL constraints: clinical authorship, guideline alignment, review dates and the information-versus-advice boundary.
How to check whether Perplexity cites your website, what a Perplexity citation tracker measures, and what to change when competitors are cited instead.

Why ‘near me’ answers now compress to two or three named businesses, and how NAP consistency, map profiles, review text and operational facts decide who gets named.

AI engines favour forums and Wikipedia for structural reasons, not conspiracy. Here is the mechanism behind it and which question types your site can realistically win.

A five-section AI visibility audit checklist covering access, extraction, attribution, current citation rates and the competitive landscape you can run internally.

Which content structures large language models extract most reliably, which ones consistently fail, and the self-containment test that catches most problems.

A practical decision framework for AI crawler policy: what GPTBot, ClaudeBot and Google-Extended actually do, and the real cost of blocking them.

Schema does not guarantee citation, but it removes ambiguity about who you are and what you claim. Here are the types that matter and how to implement them.

Seven concrete, checkable reasons AI assistants skip your site, from blocked crawlers and client-side rendering to entity ambiguity and unextractable prose.

A week-by-week plan to measure, fix and grow how often AI assistants cite your business, using only your existing team and content.
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