r/AISearchLab

Been going back and forth with people building in this space and I've flipped my thinking. A single "here's your AI visibility score" snapshot is borderline misleading — answers shift run to run and model to model, so one number on one day tells you almost nothing.

The thing that actually matters is tracking the same brand on the same queries over time, so you can tell whether what you published actually moved anything vs. just noise.

Curious where people land on this — is anyone tracking AI visibility as a trend, or is it still mostly one-off checks? And how are you handling the run-to-run variance?

Anyone use them? How have they worked out?

Most teams I know have dashboards for traffic, rankings, conversions, CAC, all of it.
But when it comes to AI assistants (ChatGPT, Gemini, Perplexity, etc.), there’s basically no visibility into how the brand actually shows up.
Stuff like:
• When someone asks “best [category] tools for [use case]”, are we mentioned at all?
• If they ask non‑branded prompts (“how do I solve X?”), do we show up in the recommended tools or just our competitors?
• Are the answers using our positioning, or describing our category in a way that makes us look like a commodity?
Right now the only “workflow” I see is people manually copy‑pasting prompts into AI once in a while and eyeballing the answers.
Questions:
• Is anyone treating AI visibility as its own layer, separate from SEO?
• Have you built any internal process to track this over time (same prompts, same tools, recurring checks)?
• If you’ve tried, what broke first: consistency, time, or actually making sense of the results?
Not looking for pitches, just trying to understand how people are operationalizing this, if at all.

I was shopping for a cat water fountain, got overwhelmed by recommendations, and just asked ChatGPT and Perplexity instead.

What surprised me: even when I asked about one specific brand, the AI didn’t only repeat the brand’s own pages. It pulled in Reddit, retailer reviews, YouTube, and review sites too.

So I ran a proper small test.

I used one real brand, PETLIBRO, as a public example and tested 15 pet-water-fountain queries across three buyer stages: problem-aware, solution-aware, and brand-aware. I ran each query once on Perplexity and once on Solution-aware, e.g. “best / quietest cat fountain”ChatGPT 5.5 thinking, then recorded the visible cited sources.

Here’s what stood out:

Query stage	Brand shown?	Who AI cited
Problem-aware, e.g. “why won’t my cat drink?”	0/5	Vets, health sites, Reddit, pet-care blogs
Solution-aware, e.g. “best / quietest cat fountain”	4/5	Review media, retailers, brand pages
Brand-aware, e.g. “review / vs / alternatives”	5/5	Brand site + review sites + Best Buy + Reddit + YouTube

The brand’s own site did show up, especially in ChatGPT.

But even on brand-aware queries, it was never the whole answer. Reviews, retailer pages, Reddit, YouTube, and third-party tests shaped the answer alongside the official site.

That changed how I think about AEO/GEO.

Optimizing the website still matters: crawlability, product pages, schema, comparison pages, clear claims, etc.

But for branded AI search, that’s only one layer.

I’d also want to know:

- Which review sites does AI repeatedly cite?

- Do retailer reviews show up?

- Does Reddit show up?

- Are there YouTube tests?

- Which caveats does AI repeat?

- Which attributes does AI assign to competitors instead?

- Where in the funnel does the brand disappear?

My takeaway:

A brand’s website makes claims. Third-party sources make those claims believable. AI seems to use both.

So even on your own branded queries, you don’t fully own the answer. AI assembles owned, earned, and community sources together.

Small caveat: this was 15 queries, two engines, one run each, visible citations only, so I’d treat it as an early signal, not a benchmark.

Anyone else tracking AI visibility seeing the same thing? Do your branded-query answers lean on third-party sources as much as your own site?

>6/27/2026 update

Small follow-up: I went back and classified the cited domains after a few people here pointed out the “neutral third-party” problem.

The interesting part: “third-party” was not one category.

In this dataset, the sources Perplexity/ChatGPT cited included:

- vet / health authority sources

- Reddit / community threads

- affiliate review media

- retailer pages

- competitor brand pages

- seller-owned advice blogs

- manufacturer / supplier content

- YouTube videos

- app-store/review signals

So the sharper takeaway for me is:

Third-party does not mean independent.

A brand page has one incentive. But a review roundup, retailer page, competitor blog, manufacturer guide, YouTube video, and Reddit thread all have different incentives too.

I also checked the “advice-style” sources specifically — the ones that look like neutral reviews, comparisons, or guides rather than obvious stores / Reddit / vet pages. Out of 16 advice-style sources, only one had no visible product-commerce incentive I could verify. The rest were affiliate-disclosed, seller-owned, manufacturer-owned, site-level affiliate, or unverifiable/page-changed.

That doesn’t mean those sources are bad or useless. But it does mean AI product answers are not built on a neutral web. They’re built on an incentive map.

This also made me think the audit question shouldn’t just be “which sources does AI cite?” but “what does each cited source want?”

How do you track if ai chats recommend your products? Seems like chatgpt's approach to suggesting products is still changing. Has anyone managed to properly track it?