There isn't a reliable pattern to copy from the handful AI does name: 3 practices in ChatGPT, 18 in Perplexity, too few to generalize from responsibly. The measurable pattern is in the 507 of 527 that neither engine named, 96.2% of the sample. Almost all of them already sit above that average and have their site open to AI crawlers. Where they differ: 53.9% have no LocalBusiness or Dentist schema on their site at all, and only 3.4% have complete structured data.
Why not just describe what gets a dental practice recommended?
Because there aren't enough winners to describe one. ChatGPT named 3 of the 415 practices it returned a reading for, and Perplexity named 18 of 297. A pattern built from 3 or 18 data points isn't a pattern. It's a guess wearing a data costume.
Those two denominators are smaller than our 527-practice sample for an unglamorous reason: the engine check failed on the rest. ChatGPT returned a rate-limit error for 112 practices and Perplexity an authentication error for 230, so we dropped those from the engine rows instead of filing them as "not recommended". An error is a missing reading, not a finding.
What we can do honestly is flip the question. Instead of asking what the rare named practice has that others don't, we can ask what the near-total not-named group shares. If 53.9% of 527 practices are missing the same basic piece of infrastructure, that's worth knowing even without a clean before-and-after comparison, because it describes the ground almost every dental practice is standing on, not the exception.
The full method behind these numbers, including how we handle scans that come back as an error rather than a real reading, is in how we measure AI visibility. City-level versions of the same scan are in our AI visibility report for Charlotte dentists.
| Signal | Measured, June 2026 | What it suggests |
|---|---|---|
| Star rating 4.3 or higher | 506 of 523 (96.7%) | Reviews are not the blocker |
| robots.txt open to AI crawlers | 492 of 527 (93.4%) | Crawler access is not the blocker, for most |
| No LocalBusiness/Dentist schema at all | 284 of 527 (53.9%) | This is where the gap is |
| LocalBusiness present, FAQPage missing | 225 of 527 (42.7%) | Partial machine-readable description |
| Both present | 18 of 527 (3.4%) | Complete machine-readable description |
Is it their reviews?
No. 96.7% of the practices we scanned, 506 of the 523 with a rating on file, already sit at 4.3 stars or higher, the level ChatGPT-recommended locations averaged in SOCi's 2026 index. Reviews are close to a solved problem across this group.
A rating level that 97% of practices already meet can't be what separates the 3 or 18 named practices from everyone else, since almost everyone is standing above it. Ratings look more like an entry ticket nearly the whole room already holds than a filter that does any sorting.
Is their website blocking AI crawlers?
For most, no. 93.4% of the practices we scanned, 492 of 527, have a robots.txt file open to AI crawlers. Only 15 practices (2.8%) were actively blocking one or more AI bots, and 20 (3.8%) had no readable robots.txt at all.
This is the cheapest thing on this page to check and rule out yourself. Open yoursite.com/robots.txt and look for a Disallow rule sitting under GPTBot, OAI-SearchBot, PerplexityBot or Google-Extended. It's rare, but when it's there the effect is absolute: a crawler that can't read your site has nothing to describe you with. A full breakdown of how blocks happen, including sites that look open but quietly refuse AI bots anyway, is in are dental websites blocking AI crawlers?
So what do almost all of them have in common?
No machine-readable description of what they are. 53.9% of the 527 practices we scanned have no LocalBusiness or Dentist schema markup at all, and only 3.4% have both LocalBusiness and FAQPage schema in place. That's the one measurable trait shared by the overwhelming majority.
Schema markup isn't a switch that turns citations on. In 2026, Mark Williams-Cook hid a made-up address inside deliberately invalid schema on a test page, with nothing matching in the visible text, and both ChatGPT and Perplexity still repeated the fake address back. His reading: the assistants were reading the page's visible text, not parsing the schema itself.
What schema does is state basic facts, what a business is, where it is, what it treats, in a form a machine can parse without guessing from prose. A practice with none of that is asking every engine that visits to reconstruct who it is from whatever text happens to be on the page. That's a slower, less reliable way for an assistant to get you right, which is a plausible piece of this picture, not a proven cause. The practices that aren't being named share this trait; we didn't run an experiment that isolates schema as the reason. Watch a walkthrough of the schema findings on video, with the four-question audit explained step by step.
Source: Mark Williams-Cook, 2026; Citevio scan, June 2026.
| Surface | Locations recommended nationally | Our June 2026 scan |
|---|---|---|
| ChatGPT | 1.2% | 3 of the 415 we could read (0.7%) |
| Perplexity | 7.4% | 18 of the 297 we could read (6.1%) |
| Gemini | 11% | Not measured |
| Google local 3-pack | 35.9% | Not measured |
Our rate sits below SOCi's national brand average on both engines, which fits: multi-location brands typically carry more schema, more third-party mentions and more crawl history than an independent single-location practice. That doesn't change the finding above. If anything, it's more evidence that a small, independent dental practice starts this race without the infrastructure larger, multi-location businesses already have in place. The ChatGPT and Perplexity rows above already show one engine recommending a practice far more often than another; how often AI engines agree with each other looks at that gap directly.
One limit worth stating on the Perplexity row: 3 of those 18 come from a Columbus batch where the city label inside the query was malformed, so the engine was answering a slightly different question than we intended. They are reported rather than dropped because a reading is kept or excluded on a written rule set before the scan, not on how it reads afterwards; the number should be taken as 15 clean plus 3 qualified rather than a flat 18. What that batch does and does not support is written out in the AI visibility report for Columbus dentists.
The dataset supporting the comparison above is preserved under DOI 10.5281/zenodo.22016876.
Does fixing my schema guarantee I'll get recommended?
No, and no page should promise that. What the data supports is narrower: schema is foundational infrastructure that most dental practices are missing, not a lever that reliably produces a citation. Mentions elsewhere, crawl history and the text on your own pages all factor in too.
We cover the mentions side of this in more depth in why isn't my dental practice showing up in ChatGPT, and the step-by-step fixes in getting your practice recommended by ChatGPT.
When your details disagree across the web, which version does an engine repeat?
Nobody has published the answer, and that is the finding. Your practice's information does not sit in one place — Google says profile information is compiled from crawled web content, licensed third-party data, user contributions and Google's own interactions with the business. What Google does not document anywhere is which source wins when those four disagree. So consistency is not a ranking tactic. It is error reduction: you are removing the disagreements rather than winning them.
Source: Google Business Profile Help, how Google sources and uses information in Business Profiles, read 18 August 2026. That page documents the sources; it does not state how conflicts between them are resolved.
Our own scan gives a sense of how much of this surface is even readable, and the honest headline is: less than you would expect. Directory presence was checked on two services, and on both the number of practices we could get a reliable reading for was far below the full sample.
| Directory | Practices with a usable reading | Listing in order | Incomplete or missing |
|---|---|---|---|
| Bing Places | 291 of 527 | 256 (88.0%) | 35 incomplete (12.0%) |
| Foursquare | 146 of 527 | 66 (45.2%) | 47 incomplete (32.2%), 33 missing (22.6%) |
What this does not show is that inconsistent details are why an engine skipped a practice. No such measurement exists here: nothing was corrected and re-measured, and no practice was tracked before and after a fix. Anyone presenting a consistency audit as the reason you are invisible is selling a correlation they have not established, and the honest version of the argument is duller — information gets compiled from sources that can disagree, the resolution rule is undocumented, so fewer disagreements means fewer ways for the wrong version to travel.
Where this stops being about consistency and starts being about an engine stating something false about your practice — wrong hours, a treatment you do not offer, a provider who left — that is a different problem with a different measurement behind it, and it is covered in what AI gets wrong about you. The Google Business Profile side, including the three things Google's documentation deliberately does not address, is in where your Business Profile fits. The directory counts above are in the downloadable Citevio dataset.
Citevio's dental market research is published openly under CC-BY-4.0 with a DOI, so the numbers can be checked and reused; client data is never published.
Crawler access and schema both leave a trace on your own site, and the checker below reads it in under two minutes.
Prefer a deeper look? The full AI visibility checker for dentists tests what ChatGPT, Perplexity, Gemini and Google AI Overviews actually say about you.
One reminder before you go. Ahrefs' correlation work across 75,000 brands found mentions of a brand on other sites tracking AI Overview appearances at r=0.664, against 0.218 for links pointing at the site, a sign that what's on your own site is one part of the picture, not the whole one. And any snapshot like this one ages: Profound found that roughly 40-60% of domains cited in AI answers changed within a month for identical prompts, which is why this page carries a scan date instead of a number we treat as permanent.
Sources: Ahrefs, May 2025; Profound, July 2025.
Common questions
Does my star rating affect whether AI recommends my practice?
Not on its own. 96.7% of the practices in our June 2026 scan that had a Google rating on file, 506 of 523, already sit at 4.3 stars or higher, the level ChatGPT-recommended locations averaged in SOCi's 2026 index. A rating level that almost everyone already meets cannot be what sorts the handful that get named from everyone else.
Is my website blocking AI crawlers without me knowing?
Probably not, but it takes one minute to check. In our scan, 93.4% of practices had robots.txt open to AI crawlers and only 2.8% were actively blocking one. Open yoursite.com/robots.txt and look for a Disallow rule under GPTBot, OAI-SearchBot or PerplexityBot.
If I add schema markup, will ChatGPT start recommending me?
There's no guarantee, and any claim otherwise is worth doubting. What we can say is that 53.9% of the 527 dental practices we scanned have no LocalBusiness or Dentist schema at all, so most practices are missing this basic layer of machine-readable description. It's foundational, not a lever with a promised payoff.
How many dental practices does this data cover?
527. The raw diagnostic set held 611 unique website scans, and 84 of those were not dental practices at all, such as retailers, salons, dental laboratories and plastic surgery practices, so they were removed before anything was counted. The remaining 527 are spread across 7 US metros, Charlotte, Austin, Raleigh, Nashville, Columbus, Tampa and Salt Lake City, plus 9 smaller towns, scanned June 6-26, 2026.
Out of the 527 practices, how many were actively blocking AI crawlers?
Very few. 15 of the 527 practices (2.8%) were actively blocking one or more AI bots in robots.txt, and 20 (3.8%) had no readable robots.txt at all. Combined with the fact that 93.4% had an open robots.txt, crawler access clearly is not the main reason most practices go unnamed.
What share of the scanned practices have complete schema markup versus none at all?
Most have neither extreme: 53.9% (284 of 527) have no LocalBusiness or Dentist schema at all, 42.7% (225 of 527) have LocalBusiness present but are missing FAQPage schema, and only 3.4% (18 of 527) have both in place. Complete, machine-readable description of the practice is rare across the sample.
How does your scan's recommendation rate compare to the national average for local businesses?
Lower on both engines we measured. SOCi's 2026 index found ChatGPT recommended 1.2% of locations nationally and Perplexity 7.4%; in our 527-practice scan, ChatGPT named 3 of the 415 practices it could read (0.7%) and Perplexity named 18 of the 297 it could read (6.1%). Gemini and Google's local 3-pack weren't measured in our scan, so no comparison exists for those.
Why is your recommendation rate lower than SOCi's national average?
SOCi measured multi-location brands nationally, and those brands typically carry more schema markup, more third-party mentions and more crawl history than an independent, single-location dental practice. That's a plausible explanation for the gap, not proof: it fits the finding that 53.9% of the practices we scanned have no schema at all, which is the kind of infrastructure a multi-location brand is more likely to already have.
Is the Columbus figure in your Perplexity count fully reliable?
Treat it as directional rather than exact. 3 of the 18 practices Perplexity named come from a Columbus batch where the city label inside the query was malformed, so the engine was answering a slightly different question than intended. We report the number as 15 clean plus 3 qualified rather than a flat 18, because a reading is kept or excluded on a rule set fixed before the scan, not on how convenient it looks afterward.
When my business details disagree across different websites, which version does an AI engine repeat?
Nobody has published the answer, and that is itself the finding. Google states that Business Profile information is compiled from crawled web content, licensed third-party data, user contributions and Google's own interactions with the business, but does not document which source wins when those four disagree. So consistency isn't a ranking tactic you can game; it's error reduction, since you're removing disagreements rather than winning a documented contest.
How many of the scanned practices have a complete Bing Places listing?
We could get a usable reading for 291 of the 527 practices. Of those, 256 (88.0%) had their listing in order and 35 (12.0%) were incomplete. Bing Places matters here because ChatGPT draws on Bing for local questions, covered in more depth on why isn't my dental practice showing up in ChatGPT.
What about Foursquare listings?
Coverage was much thinner. We could get a usable reading for only 146 of the 527 practices; of those, 66 (45.2%) had their listing in order, 47 (32.2%) were incomplete and 33 (22.6%) were missing entirely. Bing Places and Foursquare returned usable readings for different numbers of practices, so the two rates can't be compared directly to each other.
Does inconsistent business information explain why AI skipped a practice?
We don't have a measurement that shows that. Nothing was corrected and then re-measured, and no practice was tracked before and after a fix, so there's no before-and-after evidence linking inconsistent details to being skipped. What we can say is duller but honest: information gets compiled from sources that can disagree, the resolution rule isn't documented, so fewer disagreements means fewer chances for the wrong version to travel.