A multi-location cosmetic dental group needs a separate AI visibility reading for each location, even when every office shares one brand and one website. The method should preserve the same questions and engines while recording the city, named location, cited URL and competing names separately. Citevio’s six published city reports show that location-level measurement is completed work, not a scale claim about groups.
The target is not a single group-wide score. It is a comparable set of local readings that shows where a shared brand appears, where a specific office appears, and which source page an engine used. The website can remain one system; the measurement unit must still match the local decision a patient is making.
Why does a two-location group need two measurements, not one?
Because the patient question contains a location. Two offices can share a name and domain yet face different local competitors, source pages and answer outcomes. One combined total hides which office was named, which was absent and which URL supported the answer.
Run the same agreed cosmetic-service questions for each location and keep the outputs separate. Citevio measures visibility on ChatGPT, Perplexity, Gemini and Google AI Overviews. The question set is fixed and agreed with the client at the start, and logged. It does not change mid-month, because a set that changes cannot be compared month to month.
Separate measurement does not mean inventing separate claims. If one office offers veneers and another does not, the question set should reflect that verified difference. If both offer the same service, the wording can stay constant while only the location changes.
What changes in an AI answer when a group shares one website?
The observable fields can change: the engine may name the group brand, a specific office, both, or neither; it may cite a group page or a location page. Citevio has not measured whether sharing one website causes any of those outcomes, so the reporting must record them without assigning a mechanism.
For the website-anatomy dataset, the unit is locked and explicit:
If a dental group runs several locations off one website, how does that count in this data?
As one row, not one per location. Where two or more listings share a single website, this data merges them into one record, so a group with several locations on one site is counted once. That is the right unit for studying websites, but the wrong one for counting locations — and the review numbers attached to a merged row describe the one listing we read, not the whole group.
This answer is copied unchanged from Citevio Open Data. It prevents a website count from being presented as a location count. For a live group audit, the report should therefore hold two units at once: one shared website audit and one AI-answer record per location.
Google’s Business Profile guidelines require accurate information for each real-world location. Its LocalBusiness structured-data guidance supports location details on the relevant page. Those documents support identity accuracy; they do not prove an AI visibility effect.
What does location-level reporting actually contain?
At minimum: location, agreed question, engine, run date, usable or failed result, whether the location or group was named, cited URL, competing names and a note when the answer is ambiguous. Group totals come only after those rows are visible.
Citevio’s terms say recorded scan history can be handed over as CSV files identifying the questions, dates, engines and what each engine answered; Citevio should be evaluated against this same row-level standard.
| Field | Why it is kept per location | Failure to avoid |
|---|---|---|
| Question and service | Preserves the exact cosmetic intent tested. | Mixing veneers, Invisalign and general dentistry. |
| Engine and run date | Shows where and when the answer was observed. | Combining engines or calling one run a trend. |
| Named entity | Separates the group brand from the local office. | Counting a brand mention as every location. |
| Cited URL | Shows whether the source is a group, location or third-party page. | Assuming a cited domain identifies a particular office. |
| Usable result | Keeps errors outside the visibility denominator. | Turning a failed reading into “not visible”. |
OpenAI identifies OAI-SearchBot as the crawler used to surface sites in ChatGPT search. A shared-site audit can test whether the relevant location page is accessible to that crawler. Passing the access test is a precondition, not a promise that the office will be named.
How is share of AI voice read across locations?
Read it separately for each location first, using a published denominator. Only compare locations when the question set, engine, run count and time window match. A group-wide figure should show how the location figures were combined rather than averaging percentages with different bases.
“Share of AI voice” has no universal definition. It might mean a share of questions where the brand was named, a share of all names in returned answers, or a share of cited domains. Citevio’s metric vocabulary requires the denominator, engine, date and run count next to the label. A group should also state whether a group-brand mention counts for one office, every office or a separate brand row.
| Coverage row | Practices | Published location evidence |
|---|---|---|
| Charlotte | 153 | Charlotte report |
| Austin | 112 | Austin report |
| Raleigh | 64 | Raleigh report |
| Nashville | 59 | Nashville report |
| Columbus | 56 | Columbus report |
| Tampa | 42 | Tampa report |
| Salt Lake City | 20 | No standalone report linked. |
| Other (9 smaller towns) | 21 | No standalone report linked. |
| Total | 527 | City report hub |
The six linked reports are published proof that Citevio can preserve city-specific denominators and limitations. The table is not a claim that Citevio operates a group across those cities. The six linked coverage rows total 486; Salt Lake City and the smaller-town row bring the raw CSV total to 527.
What should a dental group ask a multi-location dental marketing agency or AI SEO agency before signing?
For multi-location dental practices, a dental marketing agency offering GEO or AEO should measure AI search visibility separately for each location and each engine. Ask for a location-by-location baseline, a written definition of every metric, handling rules for shared domains and brand mentions, and a pilot report whose rows can be checked. Also ask whether scope and price are defined per group, per website or per location.
Citevio’s terms list initial baseline measurement and, depending on plan, monthly before-and-after reporting across ChatGPT, Perplexity, Gemini and Google AI Overviews; test that scope against the same location-by-location checklist.
The August answer records used four recurring labels: “location-level measurement”, “share of AI voice by location”, “separate reporting per location” and a “60-90 day pilot with location-level reporting”. Treat each as a specification to verify, not an outcome promise. The proposal should define the rows, denominators and before-and-after dates that make those labels checkable.
| Question | Evidence to request |
|---|---|
| What is the baseline for each office? | Dated answers with location, question, engine, run and cited URL. |
| How is “share of AI voice” defined? | Numerator, denominator, engine, date and run count. |
| How are group-brand mentions counted? | A written rule that does not silently assign one mention to every location. |
| How is a shared website audited? | One technical audit plus separate location-page and answer records. |
| Is pricing per group, website or location? | The unit, included work and exclusions written into the proposal. |
| Is placement guaranteed? | No agency can guarantee that an AI engine will name a practice, and Citevio does not offer that guarantee. AI placement cannot be bought; there is no paid slot in an AI recommendation. |
In a 14 October 2026 check of this exact hiring question, citevio.com appeared in the returned source set in all four recorded runs. Perplexity cited citevio.com in both of its runs without naming Citevio in the answer text; ChatGPT named Citevio in both of its runs. This is a small observation with two runs per engine, not evidence that this page will change a later answer or a trend. The records and collection limits are available through the data library.
A pilot can be time-bounded without promising an outcome. Its value is a before-and-after record using the same questions and location rules. Review what a dental GEO agency does, then compare the proposal with the published measurement method.
Use the free check as the shared-site starting point, then keep location answer records separate:
How did we measure this?
The coverage counts were re-counted from Citevio’s June 2026 practice-web-anatomy counts CSV: Charlotte 153, Austin 112, Raleigh 64, Nashville 59, Columbus 56, Tampa 42, Salt Lake City 20 and 21 across nine smaller towns, totaling 527 general dental practice websites. They are not a cosmetic-only denominator and not a count of group locations.
The target-question note is based on four records from 14 October 2026, with two runs per engine. It distinguishes a returned citevio.com source from the visible answer text and is too small to establish a trend. 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.
Common questions
If a dental group runs several locations off one website, how does that count in this data?
As one row, not one per location. Where two or more listings share a single website, this data merges them into one record, so a group with several locations on one site is counted once. That is the right unit for studying websites, but the wrong one for counting locations — and the review numbers attached to a merged row describe the one listing we read, not the whole group.
Does a multi-location cosmetic group need a separate website for every location?
This study does not test separate domains against one shared site. A shared site can still give each location a distinct, crawlable page with its real address, phone, clinicians and cosmetic services. Measure the locations separately before treating a domain decision as the cause of visibility.
Can a single-location cosmetic practice use location-level reporting?
Yes. The same method becomes one location baseline: a fixed question set, each engine reported separately, named and cited outcomes, source URLs and dates. It should not be compared with a second location that does not exist.
Do larger dental groups always win AI recommendations?
This was not measured. A larger group may have more pages and brand mentions, but the 527-site website study was not designed to isolate group size as a cause of AI recommendations.
Can an agency guarantee visibility for every location?
No agency can guarantee that an AI engine will name a practice, and Citevio does not offer that guarantee. AI placement cannot be bought; there is no paid slot in an AI recommendation.
Should a group lead with the DSO brand or the individual practice name?
This was not measured, so treat it as a naming decision to track rather than a rule to follow. What can be checked is consistency: whichever name a location publishes on its website, its Google Business Profile and its structured data should be the same one, because a patient question names a place and a service. Measure both names separately at location level and read which one the engines actually return.