AI Visibility · Private Practices
What is AI share of voice for a medical practice?
Last updated: 2026-06-06AI share of voice is the share of AI answers that cite or mention your practice. For a medical practice, it counts how often ChatGPT, Claude, Perplexity, and Gemini name your practice when patients ask which provider to choose. A higher share means AI assistants recommend you more often than competing practices.
What does AI share of voice actually measure?
When a prospective patient asks an AI assistant "who is the best med spa near me" or "which dermatologist treats melasma," the assistant returns a short list of practices. AI share of voice measures your slice of those answers: out of every AI response to the questions your patients ask, how many cite or mention your practice by name or link to your site.
The metric is a ratio, not a rank. If a probe asks forty patient questions and your practice appears in eight answers, your AI share of voice is eight of forty. AI share of voice is the share of AI answers that cite or mention your practice, and that fraction is the number you track over time as you publish content the assistants can read.
How is AI share of voice measured for a practice?
Measurement uses a multi-engine probe. The same patient and buyer questions are asked across ChatGPT, Claude, Perplexity, and Gemini, then every answer is scanned for two things: a link to your practice domain (domain-citation matching) and your practice name written out (name-mention matching). Counting both domain citations and name mentions catches answers that name a practice without linking.
The probe runs monthly because AI answers vary between runs. The same question asked twice can return different practices, so a single snapshot is noise. Repeating the probe on a fixed cadence turns scattered answers into a trend you can act on. A multi-engine probe measures AI share of voice across ChatGPT, Claude, Perplexity, and Gemini each month.
Why do practices have no source for this number today?
Patients now ask AI assistants which provider to choose, but most practice owners cannot see what those assistants say back. There is no healthcare-specific dashboard for it. In a Tenva probe, 12 of 16 buyer queries about AI visibility for practices had no authoritative answer source, meaning no domain was trusted enough to be cited by two or more engines for the same question.
That gap is the opportunity. Where no source dominates, a practice that publishes clear, AI-readable answers can become the one assistants cite. Measuring your AI share of voice first tells you exactly which patient questions you are absent from before you spend on content. Knowing whether that effort is paying off is a separate question, and tracking what AI says day to day is another.
How does a practice set its own baseline?
A baseline is your AI share of voice before you change anything. Tenva published its own: Tenva appeared in 0 of 95 AI answers across June 2026 multi-engine probes. Tenva put that zero on the record as the BEFORE half of a public before/after experiment, because a number you can be measured against is more honest than a claim you cannot.
To set yours, list the ten to twenty questions a patient would type before booking, ask each across all four assistants, and count the answers that cite or mention your practice. That fraction is your starting share of voice. Re-run the same questions monthly and watch the number move. AI visibility improves the odds of being recommended. The baseline tells you where those odds stand right now.
Frequently asked questions
Why measure across four AI engines instead of one?
Why is there no existing tool for this in healthcare?
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