A single screenshot cannot show what account, prompt, or run produced it, so by itself it proves very little. Before trusting an AI visibility claim, ask for the exact question wording, the date it was run, the total pool the result came from, and whether it repeated on a second run. Missing any of the four, the claim is not verifiable yet.
Practices choose an AI visibility agency partly on what shows up in the sales call, and a cropped screenshot of a ChatGPT or Perplexity answer is one of the easiest things in the world to produce and the easiest to make look better than it is. This page sets out what a verifiable claim actually contains, as part of our larger guide to choosing an AI visibility agency, and applies the same test to Citevio's own numbers, including the ones that do not flatter us.
Why does a screenshot prove almost nothing?
A screenshot only shows one account, one prompt, and one moment. It cannot show whether the wording was neutral or leading, whether the account's location or search history nudged the answer, or whether the same result would come back five minutes later. None of that is visible in a cropped image, and none of it is something you can take on trust.
That instability is not a glitch, it is how these systems are built. Both OpenAI and Perplexity describe their search features as live retrieval steps: the model queries the web, or a fresh index, at the moment the question is asked, rather than pulling from a fixed, unchanging list (OpenAI Help Center; Perplexity Help Center). A result captured once is a snapshot of that moment, not a guarantee of what the same question returns tomorrow.
What four questions should you ask about any claim?
These four apply to any AI visibility claim an agency shows you, whether it is a screenshot, a slide, or a line in a proposal.
- What was the exact question? The literal wording sent to the engine, not a summary of it. A leadingly worded prompt, one that names the practice or its city inside the question, makes an appearance far more likely and proves far less.
- What is the denominator? A citation only means something next to the pool it came from. Getting mentioned means something different out of five questions than out of five hundred.
- When did it run, and how often? A single date is a snapshot. A result checked once and a result checked on two separate runs are different kinds of evidence.
- Can you see the raw output? Not a cropped image of one line, but the full answer, including which other names appeared alongside it.
An agency that can answer all four without hesitation is showing you a claim you can check. An agency that can only produce a single screenshot is showing you a claim you cannot. This same framework carries over to vetting the rest of a pitch, covered in our guide to choosing a dental marketing agency.
How do you reproduce an agency's screenshot yourself?
None of this requires special tools. You can do it today, by hand, in about the time it takes to read a proposal.
- Start a new, logged-out or fresh session on the engine in question, ChatGPT, Perplexity, or Gemini, so your own account history does not shape the answer.
- Type the exact question the agency claims to have used, word for word. If they will not give you the exact wording, that itself is useful information.
- Note the date and time you ran it, and save the full response, not just the line that mentions the practice.
- Wait a day or more, then run the identical question again. A result that holds on a second run is stronger evidence than one that only ever appeared once.
- Compare what you see against what the agency showed you. Same wording, same names, same order? If not, ask why.
This is the same basic process Citevio runs at scale, described in full on our methodology page. If you want a faster first look at your own practice, our free checker covers the first two steps automatically.
What does a percentage-increase claim leave out?
A percentage on its own is one of the easiest numbers to make impressive. Going from one citation to two is technically a 100% increase; going from one out of fifty questions to two out of fifty barely moves the underlying picture. Without a starting point, the pool it is measured against, and the date range, a percentage increase is a shape, not a fact. A claim like that is itself one of the common red flags to watch for when vetting a dental marketing pitch.
Some agencies in this space advertise a claim along the lines of a double-digit percentage lift for a client. We cannot confirm or deny a claim like that, because the version published does not include the denominator, the date, the exact question set, or how many runs produced it. That is not the same as saying it is false. It means the claim, as published, is not verifiable yet, and a reader has no way to check it for themselves.
Here is the same kind of claim from Citevio, published with everything the paragraph above says is missing.
| Metric | Value |
|---|---|
| Buyer-intent, agency-selection questions tested | 16 |
| Engines, and runs per engine | 2 engines, 2 runs each (64 answers) |
| Questions where citevio.com appeared as a cited source | 5 of 16 |
| Questions where citevio.com did not appear | 11 of 16 |
| citevio.com's count among the sources cited in those 11 questions | 0 |
Our own numbers come from one measurement window on two engines. By the standard this page sets, that is a limitation — and we publish it rather than round it away. One window is not a trend; our own rule looks for the same pattern across separate measurement rounds before calling it stable, and this is the first. Google Gemini could not be tested at all, since all 16 questions returned a quota error on that engine, so Gemini is not a loss here, it is an unknown. The answer-level records sit in Citevio's open dataset, so anyone can recount them.
Should you check the agency's own site first?
Before signing with any AI visibility agency, run the same four-question test in reverse and ask the engines about the agency itself. If a company that claims to get dental practices cited by ChatGPT cannot get itself cited answering the buying questions patients ask about choosing that same kind of agency, that is worth noticing.
It is also why we ran the test on ourselves first. Across 16 buyer-intent questions, asked twice on each of two engines, citevio.com was cited in five and absent from the other eleven. In those eleven, it did not appear among the sources either engine cited, on either run. We are publishing that alongside the wins, not instead of them.
Two more places to check: whether the agency shows up in independent tracking of who these engines already recommend, and whether its pricing is public enough to compare the same way.
Common questions
Is a single screenshot proof of anything?
Not by itself. A screenshot shows one account, one prompt, and one moment, so it cannot show whether the wording was neutral, whether the result would repeat, or what else appeared in the full answer. It is a starting point for verification, not the verification itself.
Do agencies just game the prompt?
It is possible to write a prompt that makes a mention almost inevitable, for example by naming the practice or its city inside the question itself. That is exactly why the exact wording matters more than the result. Ask for the literal question that was sent, not a paraphrase of it.
What if an agency will not share the exact wording of the question?
Treat that as information on its own. A claim built on a question you cannot see and cannot rerun is not something you can verify, whatever the screenshot shows.
How many runs does it take before a result counts as a pattern?
Citevio's own rule looks for the same result across two separate runs before calling it stable. A single appearance, on our numbers or anyone else's, is a sighting, not a trend.
Sources: FTC, Policy Statement Regarding Advertising Substantiation (1984); OpenAI Help Center, "ChatGPT Search," accessed 14 August 2026; Perplexity Help Center, "How does Perplexity work?," accessed 14 August 2026; Citevio engine panel measurement, 7–8 August 2026 (own data, methodology: how we measure AI visibility).
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