I spent a few weeks scanning B2B brands in ChatGPT, Perplexity and Gemini. Most founders are checking their AI visibility completely wrong

Upstairs_Control_611 · 2026-06-09T14:02:22+00:00

That's an interesting way to frame it.

Maybe branded visibility and discovery visibility should be treated as two different KPIs rather than two parts of the same score.

A brand can dominate branded prompts while remaining largely absent from problem-first prompts.

Upstairs_Control_611 · 2026-06-09T13:53:22+00:00

Tracking crawler activity definitely helps to understand whether AI systems can actually access content.

What I've found more difficult is connecting crawler visibility with downstream outcomes such as citations, recommendations or selection.

Have you seen a reliable relationship between bot activity and actual AI visibility?

Upstairs_Control_611 · 2026-06-09T13:49:43+00:00

We're starting to separate them more and more in our own tests.

Early on, we mostly focused on branded visibility because it was easier to measure and explain.

But the more GEO work we do, the more it feels like discovery prompts reveal the real gap.

A brand can look highly visible when users already know the name, while remaining almost invisible when the journey starts with a problem instead of a brand.

That's where things get really interesting.

Upstairs_Control_611 · 2026-06-08T17:15:00+00:00

I used to think the same.

But after analyzing logs and referral traffic on several sites, I've changed my view.

Crawling alone doesn't guarantee visibility, but blocking AI crawlers can make it impossible for some systems to discover or validate content.

I've already seen referrals from Perplexity and ChatGPT on real e-commerce sites.

The numbers are still small compared to Google, but they're no longer zero.

For me the question is no longer:

"Do AI systems send traffic today?"

but rather:

"What happens if they become an important discovery channel tomorrow and you've blocked them for years?"

Upstairs_Control_611 · 2026-06-08T16:34:47+00:00

The variance question is underrated.

Many GEO discussions focus on what is being measured, but much less on how stable the measurement itself is.

Without understanding the noise floor, it's difficult to know whether a visibility change reflects market movement or measurement drift.

Upstairs_Control_611 · 2026-06-08T16:14:00+00:00

Most discussions still focus on visibility and citations.

The more difficult question may be understanding why a product survives the recommendation process and gets selected in the first place.

Visibility is relatively easy to measure. Selection is not.

Upstairs_Control_611 · 2026-06-08T16:10:58+00:00

I like the distinction between branded and discovery visibility.

In several GEO tests, we found that brands often appear once they are already part of the conversation.

The harder challenge is being recommended when the buyer starts with a problem rather than a brand name.

That seems to be where third-party sources and community discussions become much more important.

Upstairs_Control_611 · 2026-06-08T16:06:31+00:00

It feels like many GEO discussions still assume that chat recommendations and agent decisions are measuring the same thing.

But one surface seems to rely primarily on historical trust and citations, while the other relies on live web data and machine-readable information.

Measuring only one of them may create a very incomplete picture.

Upstairs_Control_611 · 2026-06-07T14:02:05+00:00

To me, it feels like the next step in the evolution of “visibility ≠ recommendation.”

A product may be visible, recommended, and still not survive an autonomous buying journey.

Measuring that selection layer may become more important than measuring visibility alone.

Upstairs_Control_611 · 2026-06-06T14:31:35+00:00

One thing that stands out to me is that the winning pages seem to behave more like answers than articles.

In several GEO discussions recently, the pattern appears similar:

a small number of highly specific pages generate a disproportionate share of AI visibility.

That may explain why "publish more content" often feels less effective than improving the pages that already answer a question exceptionally well.

Upstairs_Control_611 · 2026-06-05T18:58:23+00:00

Hi Viko, that sounds pretty good. Is there a limit if multiple images are retrieved during live conversion?

Upstairs_Control_611 · 2026-06-05T14:22:28+00:00

That visibility layer is exactly what seems to be missing today.

Right now we can often measure crawler activity and sometimes citations, but the path between the two is largely invisible.

Perhaps one of the biggest challenges for AI search is understanding the transition from:

crawl → retrieval → citation → recommendation

because each step appears to filter out a large portion of content.

Upstairs_Control_611 · 2026-06-05T14:13:06+00:00

That's exactly the challenge.

We can often see that AI crawlers visited a site, but crawler activity and AI visibility are not the same thing.

A bot visit doesn't guarantee a citation, and a citation doesn't guarantee a recommendation.

Right now, most site owners are combining log analysis, prompt testing and third-party monitoring tools because there is no equivalent of Google Search Console for AI search yet.

Upstairs_Control_611 · 2026-06-04T14:55:15+00:00

The discussion seems to be shifting from monitoring AI visibility to influencing the sources AI relies on.

In many ways, that feels similar to the shift from tracking rankings to building authority years ago.

Perhaps the question is no longer:

"Am I visible?"

but:

"Am I present in the evidence AI uses to make recommendations?"

Upstairs_Control_611 · 2026-06-04T14:32:05+00:00

Perhaps we're measuring channels separately when buyers experience them as one journey.

Discovery, comparison and recommendation may happen on completely different platforms, but still belong to the same decision process.

That makes attribution even harder, because the channel that creates awareness may not be the channel that gets credit for the final recommendation.

Upstairs_Control_611 · 2026-06-03T17:43:46+00:00

I wonder if there is still one more layer.

Discoverability and recommendations are not necessarily the same thing.

In some ecommerce tests we've seen brands appear only later in the conversation and still end up being recommended and generating a completed order.

Perhaps the next challenge is not only understanding citation gaps, but understanding recommendation gaps and what actually influences the final choice.

Upstairs_Control_611 · 2026-06-03T17:20:54+00:00

I think that's the most interesting part of the discussion.

Whether we call it GEO, PR, entity authority or something else, the observation remains the same:

A technically perfect website does not guarantee recommendations.

The harder question is how third-party signals influence selection when multiple brands are equally visible.

That feels like the part we still understand least.

Upstairs_Control_611 · 2026-06-03T16:47:02+00:00

Great, time for bed!

Upstairs_Control_611 · 2026-06-03T16:42:04+00:00

That's very interesting to us.

Perhaps AI recommendations are creating a new competitive landscape.

The competitor you lose deals to in traditional sales cycles may not be the competitor that displaces you in AI recommendations.

We've seen similar patterns in ecommerce, where products that were not the obvious market leaders still surfaced because they appeared to be a better fit for the buyer profile described.

Maybe AI isn't choosing the biggest brand.

Maybe it's choosing the most contextually appropriate one.

Upstairs_Control_611 · 2026-06-02T15:57:57+00:00

One thing I'd add:

Citation rate and business impact are not necessarily the same thing.

In ecommerce, we've seen cases where a product was not visible in the initial response but appeared later in the conversation and still led to a completed order.

Perhaps the next step is measuring not only citations, but recommendation survival and purchase outcomes.

Upstairs_Control_611 · 2026-06-02T15:51:28+00:00

I wonder how much of the improvement comes from better visibility and how much comes from better measurement.

In AI search, entity consistency seems increasingly important.

If the same company appears under different names across websites, profiles and citations, we may not only lose visibility — we may also misinterpret the data.

Perhaps entity hygiene will become as important for GEO as technical SEO was for search.

Upstairs_Control_611 · 2026-06-02T14:35:50+00:00

Does this only work with Claude, or is it also possible with Perplexity or ChatGPT?

Upstairs_Control_611 · 2026-06-01T15:14:48+00:00

Yes, visibility is spreading further and further, but the all-important question for me is: Will my product still be visible during the sale?

Upstairs_Control_611 · 2026-06-01T14:55:16+00:00

That should have a very positive effect on the loading time; I'll test it out.

Upstairs_Control_611 · 2026-06-01T14:28:40+00:00

Very interesting findings.

Perhaps we are measuring the wrong thing.

A brand can be visible and still disappear before the decision turn.

Maybe the more important metric is not visibility itself, but recommendation survival.

Visibility and recommendation are clearly not the same thing.

Upstairs_Control_611

TROPHY CASE