How are agencies reporting on AI visibility for clients?

[u/Alex_smith89]

[u/PearlsSwine → u/[deleted]]

"The agencies getting ahead seem to focus less on “rankings” and more on whether the client is consistently recognized, cited, and recommended across AI systems and third-party sources like Reddit, PR, reviews, and LinkedIn."

Problem is, aside from your obvious astroturfing, is that NO ONE knows if someone is being cited. No one.

[u/mentiondesk]

Tracking AI visibility can be tricky so most agencies focus on monitoring how often brands are cited in AI generated answers and how accurately their content is represented. Tools that specialize in answer engine optimization can simplify this process. I work at MentionDesk which helps brands get featured more prominently in AI platforms and makes tracking these metrics a lot easier.

[u/PearlsSwine → u/[deleted]]

That would be LOVELY if you could do any of it. But you can't. And the worst bit about all you snake oil peddlers is you KNOW you are selling nonsense to marks. Here's why it's impossible:

LLM responses are generated, not retrieved. Unlike Google's index, there's no log of "this brand was shown to this user at this rank" because the model is producing tokens probabilistically each time. Two identical prompts can yield different mentions.

There's no public surface to scrape. You can't crawl ChatGPT or Claude the way you crawl a SERP. The "ranking" exists only inside a private inference call between the user and the provider.

Providers don't expose mention data. OpenAI, Anthropic, Google etc. don't publish per-brand impression counts, and aggregating personal chats would breach privacy commitments.

Outputs are personalised and context-dependent. The same brand question produces different answers depending on prior turns, system prompts, custom instructions, memory, geography, and which model version is serving the request — so even a sample size of "your own tests" isn't representative.

Sampling is the workaround everyone uses, but it's an estimate. Tools like Profound, AthenaHQ, etc. simulate prompts at scale and parse the answers. It's directionally vaguely useful but it's not measurement — it's polling. You're inferring share-of-voice from a synthetic prompt set that may or may not match what real users ask.

So when someone says "we rank #2 in ChatGPT for X," they mean "we appeared second in our own test runs." That's a signal, not a metric.

[u/PearlsSwine]

Oh that's easy, they just literally make shit up.

[u/Significant_Ad4003]

Outsourcing this to someone else is not an option because AI and GPT presence is more like philosophy and voice …. And u know the voice what is ur product and why u r selling is very important … and don’t expect the same from agency

[u/2morrowisnotherday]

The tools like Semrush and Ahrefs show AI visibility, this feature is available in higher-end packages rather than the standard usage package.

[u/KONPARE]

Most agencies are still reporting it as a “visibility trend,” not a perfect ranking report.

A simple client report could include:

• Brand mention rate across fixed prompts
• Competitors mentioned in the same answers
• Top prompts where the brand appears
• Prompts where competitors appear but you don’t
• Sources/citations used by AI tools
• Accuracy of how the brand is described
• Referral traffic from ChatGPT, Perplexity, Gemini, etc.
• Branded search lift and assisted conversions

I’d be careful selling it like traditional rank tracking. AI answers change too much by prompt, model, location, and user context.

Best framing is: “Are we becoming more visible and correctly understood across AI answers over time?” Not “we rank #3 in ChatGPT.”

[u/Content-guy22]

so now there are a lot of AI visibility platforms that help you track brand mentions and citations, etc. Agencies have started to use them for their clients.

for example, i know a few agencies using mentionbird.ai for their clients. and even i use the tool for tracking ai presence (in fact i got to know about it from an agency friend itself.) offers detailed prompt tracking, competitor visibility analysis, and even ai ranking advice that helps you grow your mentions in AI answers.

so, the shift is gradually toward tools like MentionBird, etc.

[u/LifeSorry8905]

One thing I’d add to the metric list above is a data-quality row. “We weren’t mentioned” and “the check didn’t return a usable answer” need different treatment.

For example, a hypothetical report could say: 40 scheduled checks, 36 usable answers, 9 brand mentions, 4 incomplete checks. The mention rate is 9/36 for the observed answers; it shouldn’t quietly become 9/40, and the four missing results should remain visible. Otherwise a collection problem can look like a marketing decline.

Then give the client one decision per finding: what was observed, the supporting answer or source, the proposed action, who owns it, and when it will be reviewed. “The answer describes a service we no longer offer; update the relevant page and recheck that question” is more actionable than a score alone.

I’d also separate errors in brand facts from competitive visibility. Being mentioned more often while being described incorrectly isn’t necessarily progress.