AI visibility is whether an AI assistant names your dental practice when a patient asks for a local recommendation. We test the same patient-style questions across ChatGPT, Perplexity and Google Gemini, run each one several times because answers shift, and score five things: crawler access, structured data, Bing indexing, reputation signals, and what the engines actually say. The framework on this page is public; the exact weighting behind the score is ours.
This page is the method that our city reports point back to, so you can check our work. It explains what we count, how we count it, and, just as plainly, where the method has limits. Nothing here is a guarantee about your practice. It is a description of how we look.
What we measure
We measure one thing: how often an AI assistant recommends a practice to a patient, and how ready that practice is to be recommended. We test three engines patients actually use to pick a dentist, with the phrases patients actually type, then record whether each engine names the practice, mentions it, or leaves it out.
The reason this is worth measuring is how few names each assistant gives. In its 2026 Local Visibility Index of roughly 350,000 business locations, SOCi found that only 1.2% of locations get recommended on ChatGPT and 7.4% on Perplexity, against 11% on Gemini and 35.9% in Google's local 3-pack. When an answer holds two or three names instead of ten links, being measured accurately matters more, not less.
Source: SOCi Local Visibility Index, 2026, via Search Engine Land.
We test the queries a real patient would ask, swapping in the city and neighborhood. Typical examples are best Invisalign dentist in [city], cosmetic dentist [city], and [city] dentist open Saturday. Practice-name searches are treated separately, because they only prove a clinic exists, not that it gets recommended.
What counts as "visible"
We sort each result into three states. Recommended means the engine puts the practice forward as an answer to the patient's question. Mentioned means the practice appears somewhere, such as a list or a cited page, but is not put forward as the recommendation. Not visible means it does not appear at all. Only the first state wins a patient.
The distinction matters because it is easy to feel visible and still lose the patient. A clinic can be mentioned inside a directory the engine cites and never be the name the assistant actually says. So we count a practice as visible for a query only when the engine names it in its own answer, not when it merely sits on a page somewhere in the sources.
| State | What it means | Does it win the patient? |
|---|---|---|
| Recommended | The engine names the practice as an answer to the patient's question | Yes |
| Mentioned | The practice shows up in a list or a cited source, but is not the recommendation | Rarely on its own |
| Not visible | The practice does not appear for the query at all | No |
How we run scans
For each practice we run a fixed set of patient-style queries across each engine, and we run every query several times over a short window rather than once. We record who gets named each time. Because a single answer is a snapshot, the number that matters is how consistently a practice appears, not whether it showed up on one lucky run.
Running once would be misleading, because AI answers are rebuilt each time from a shifting set of sources. According to a 2025 Profound analysis of about 80,000 prompts per engine, roughly 40–60% of the domains an engine cites for a given question are different one month later. That is why we treat visibility like weather readings: several samples, then the pattern, never a single day.
Source: Profound domain-drift analysis, 2025 (~80,000 prompts per engine, June–July). tryprofound.com
Where our data comes from
Every figure in our reports comes from our own scans, not bought datasets. In June 2026 we scanned dental practices across seven US metros: Charlotte, Columbus, Austin, Raleigh, Nashville, Tampa and Salt Lake City. Each report shows the exact dates its scan was run, so you can judge how fresh the picture is before you rely on it.
Building the data ourselves is the point. It is information no competitor can copy, and it keeps us honest, because we publish the scan window instead of implying the data is live. You can see a full worked example in our AI visibility report for Charlotte dentists, which applies this exact method to one market. When a city is re-scanned, that report is updated and dated again.
What each AI engine reads
The three engines do not share one source of truth, so we check each on its own terms. ChatGPT reads Bing's web index. Perplexity reads the live web and shows its citations, favoring fresh pages. Gemini leans on Google's index and your Google Business Profile. A practice can be strong in one and absent from another, which is why a single-engine check is never enough.
The table maps each engine to the signals it builds local answers from, and to the part of our score that tests for it. It is also why our checker queries all three rather than assuming ChatGPT speaks for every assistant a patient might use.
| Engine | Main signals it builds local answers from | What our score checks for it |
|---|---|---|
| ChatGPT | Bing's web index, plus consistent business details and mentions across platforms | Bing indexing and reputation signals |
| Perplexity | The live web with visible citations; a preference for fresh, well-structured pages | Crawler access and structured data |
| Gemini / Google AI | Google's index plus your Google Business Profile | Reputation signals and the AI answer test |
Sources: ChatGPT's reliance on Bing per Damian Rollison, Search Engine Land, 2025; Gemini's use of Google's index and Business Profile per SOCi's 2026 Local Visibility Index; Perplexity's visible-citation design is observable in the product.
What our score means
Our score runs 0 to 100 and rolls up five categories: crawler access (can AI bots reach the site), structured data (can engines read the practice correctly), Bing indexing (is the site actually in Bing), reputation signals (reviews, ratings and consistent details), and the AI answer test (what the engines say when asked). We publish these categories. We do not publish the weighting between them.
We keep the categories in that order for a reason: reach and reputation tend to move the needle before anything technical does. Across 75,000 brands, Ahrefs found brand web mentions correlated with AI visibility at r≈0.664, far ahead of backlinks at r≈0.218 — mentions and reputation, not link counts, are what these engines lean on. Muck Rack's May 2026 study of more than 25 million AI citations points the same way: earned media supplied about 84% of them, and has stayed in the 82 to 89% band across its editions.
Sources: Ahrefs study of 75,000 brands, 2025 (ahrefs.com); Muck Rack "What is AI Reading", May 2026 (muckrack.com).
One deliberate limit: structured data sits in the score as reading infrastructure, not a citation trigger. Schema helps an engine read your name, address, hours and services correctly. It does not, on its own, make an engine cite you. We score it for what it does, and no more.
A note on reputation signals. Engines favor practices above a review-rating floor, around 4.3 stars for ChatGPT, and they weigh how consistent and recent your reviews are. That is why two clinics with the same technical setup can score differently: the one patients rate and describe more often reads as the safer recommendation.
Limitations
This method has real limits, and hiding them would make the data less useful. AI answers change from run to run, so even several samples are a recent picture, not a permanent one. Some scans check Gemini manually rather than through the same automated pipeline. And a scan measures what an engine says, not why, so we report visibility, not a guaranteed cause behind it.
- Answers move. With 40 to 60% of cited domains changing monthly (Profound, 2025), a practice that is visible today may not be next month, and the reverse.
- Gemini is sometimes manual. Where a scan did not include Gemini in its automated column, we checked it by hand and say so in the report rather than inventing a number.
- It is a point in time. Each report carries its scan dates. We do not present month-old data as if it were live.
- We measure, we don't promise. Higher scores line up with getting recommended, but no honest method can guarantee a spot in an answer no one controls.
See where your practice stands today
The fastest way to understand this method is to run it on your own clinic. The free checker below reads your website and scores its AI-readiness in seconds, using the same categories described above. No email and no call.
Want the manual version first? See how to check what ChatGPT says about your practice, or the deeper AI visibility checker for dentists.
Frequently asked questions
What is an AI visibility score and how is it calculated?
An AI visibility score is a 0 to 100 read of how ready a practice is to be recommended by AI assistants. Our score checks five categories: whether AI crawlers can reach the site, whether its structured data lets engines read the practice correctly, whether the site is in Bing's index, the strength of reputation signals like reviews and consistent details, and what ChatGPT, Perplexity and Gemini actually say when asked a patient-style question. The framework is public. The weighting behind the number is ours, so the score stays hard to game.
Which AI engines do you track?
ChatGPT, Perplexity and Google Gemini, because those are the assistants patients use to find a dentist. Each builds its answers differently: ChatGPT reads Bing's web index, Perplexity reads the live web with visible citations, and Gemini leans on Google's index and Google Business Profile. Where a scan checks Gemini by hand rather than through the automated pipeline, the report says so.
How often do you re-scan?
Every report shows the date its scan was run, so you always know how fresh the data is. Tracked cities are re-scanned periodically rather than on a fixed public calendar, and because a single scan is a point-in-time picture, we run each query several times within a scan. When a city is re-scanned, the report is updated and dated again.
Why do AI answers change between runs?
AI answers are rebuilt each time from a shifting set of sources, so the same question can name one practice today and a different one next week. According to a 2025 Profound analysis of about 80,000 prompts per engine, roughly 40 to 60% of the domains an engine cites for a question change within a month. That is why we judge visibility by how often a practice appears across several runs, not by a single result. You can see this reading applied in our Charlotte dentists report.