Why We’re Building the Best Tool For Tracking Brand Visibility in AI Search Platforms

As a marketer, I’ve been in the room when someone asks, “What’s our presence in AI search?”

Silence. Or worse — guesses.

We check ChatGPT manually. Screenshot Perplexity answers. Slap together slides from a few ad hoc queries and call it a “snapshot.”

It’s not just me. I’ve seen comms teams, SEO leads, and entire marketing orgs scramble to answer the same questions:

• Are we even being mentioned?

• How are we described?

• Why are our competitors showing up — and we’re not?

The shift to generative search has been sudden and messy. And while the surface narrative is all about AI content and automation, the deeper problem is this: We don’t have visibility into how AI engines perceive us.

We explored solutions — some were wildly expensive enterprise platforms. Others offered vague dashboards with no real insight. Meanwhile, the analytics tools we do trust — GA4, GSC, Ahrefs, Semrush — have barely touched the AI layer. So we’ve been stuck: lots of pressure, no clear playbook.

That’s why we built something new. To unpack the real reasons behind AI visibility. What gets cited. What gets ignored. What makes you part of the answer — or left out entirely.

Here’s what we learned in the process of building Probe Analytics — and the 4 biggest visibility gaps that are costing brands trust, traction, and revenue right now.

AI search has created new visibility gaps — and most brands don’t know how to respond

AI platforms like ChatGPT, Gemini, Claude, and Perplexity don’t crawl or rank content like Google. They synthesize, filter, decide, and judge.

That judgment can position your brand as a market leader, describe it with outdated or inaccurate messaging, or leave it out entirely. And the decision is often made without your input, based on content you didn’t know was influencing the answer.

The danger is not only that you’re being out-ranked by a competitor in front of your exact ICP, but also that your brand is being misrepresented, if it shows up at all.

In one audit, we found that 87% of brands weren’t appearing in AI-generated recommendations for the very categories they compete in.

In the sections below, we’ll walk through the three most critical AI visibility gaps we’ve seen and why most brands are unequipped to close them.

Gap 1: You don’t know how AI platforms are describing your brand or if they’re mentioning you at all

The most common (and dangerous) gap we see is total blind spots in brand representation.

Ask most companies how they show up in AI search responses, and they’ll shrug. They’ve never audited AI visibility. They don’t know which prompts trigger brand mentions. They don’t know if they’re being described accurately — or at all.

We’ve seen AI platforms:

• Invent features a product doesn’t have

• Reference outdated messaging from years-old blog posts

• Recommend competitors in direct response to prompts the brand should own

And because none of this gets tracked in Google Analytics, GSC, or Ahrefs… it goes completely unnoticed.

If your brand is left out, you’ve been disqualified before the buying journey even begins. If it’s included but framed incorrectly — outdated, oversimplified, or just plain wrong — you’ve lost control of your narrative in the exact moment trust is formed.

And because none of this shows up in your analytics, you won’t see the drop until it’s already hit the pipeline.

Gap 2: You don’t know what’s driving AI mentions or why competitors keep winning them

Even when your brand shows up in AI-generated answers, you’re often left wondering why. And when it doesn’t, there’s no breadcrumb trail to follow. No keyword to optimize for. No backlink to chase. Just silence.

We’ve spoken with heads of marketing at companies running full-funnel programs — investing in SEO, briefing PR teams, launching landing pages — yet they still can’t answer questions as basic as:

• What prompts surface our brand?

• What claims, content, or citations are actually driving inclusion?

• Why are our competitors getting recommended more often — even when we know we outperform them?

The reality is, AI search doesn’t reward visibility the same way Google does. These platforms respond to intent-rich prompts with synthesized decisions, not clickable lists. A single answer — often based on unseen factors — determines who gets the mention, and who gets cut.

And those prompts aren’t generic. They’re often written by real buyers, spelling out their needs with urgency and context:

“I’m at a 1,500-person company looking for a platform that integrates with Workday, supports mentoring, and prioritizes DEI. Any recommendations?”

Some teams try to reverse engineer inclusion manually. They copy outputs, test different variations of prompts, and try to isolate patterns. But prompt results change with session history, phrasing, model updates, and sentiment, which means whatever you discover today might not apply tomorrow.

Without structured data showing which prompts drive mentions, which claims get cited, and which competitor content is being favored, you’re left trying to compete in a channel you can’t even see clearly.

Gap 3: You don’t know if AI visibility is driving business results

Appearing in AI-generated answers might feel like a win but if you can’t connect those mentions to actual outcomes, it’s just another vanity metric.

We’ve seen companies pour time and budget into optimizing for AI search: rewriting content, briefing PR around prompts, shifting messaging to match synthesized queries. But when asked which AI mentions are driving traffic, which pages are converting, or whether those strategies are working at all — they don’t have a clear answer.

Most teams either look at mentions in isolation or rely on manual prompt testing and screenshots as proof of performance. And while GA4 technically tracks LLM-driven sessions, few marketers have surfaced that data — and even fewer are using it to guide decisions.

Without that feedback loop, it’s easy to waste resources. You might be optimizing pages that aren’t generating traffic. You might be ignoring pages that are quietly pulling in high-intent sessions from Perplexity or ChatGPT. And when performance drops, you have no trail to trace it back.

AI visibility without attribution is a dead end. You need to see which mentions are turning into sessions — and which sessions are turning into business value.

How we’re solving for these gaps with Probe Analytics

We kept seeing the same pattern.

Marketing teams were investing in AI content, revamping landing pages, updating product messaging — but when we asked how they were tracking visibility in AI search, they didn’t have an answer.

Some were screenshotting ChatGPT. Others were pasting prompts into Perplexity. A few had spreadsheets of branded queries they were manually checking each week.

None of it scaled. None of it gave a clear picture of how AI platforms were shaping perception — or what to do about it.

And yet, these AI engines were becoming the first touchpoint for high-intent buyers.

People were asking LLMs:

• "What’s the best X for Y?"

•  "What should I use instead of [competitor]?"

• "Compare [your product] to [category leader]."

And based on what the AI surfaced — or didn’t — deals were being won or lost before a rep ever got involved.

That’s why we built Probe Analytics: to help brands track, measure, and influence how they show up in the new reality of AI-driven search.

Here are ways Probe Analytics can help you with your AI visibility challenges.

1. See how AI platforms describe (or ignore) your brand and take back control

You can’t fix what you can’t see. And right now, most teams are flying blind — hoping their AI strategy is working, without knowing how (or if) they’re showing up in the answers buyers trust most.

We’ve heard it from CMOs and SEO leads alike: "We’re investing in AI content, but we have no clue what ChatGPT is actually saying about us." Meanwhile, AI search platforms are shaping brand perception in real-time — describing your product, comparing it to competitors, and recommending solutions. Whether they get it right or wrong, the impact is the same: you don’t get a second shot.

Probe puts you back in control.

You can now type in any prompt  (just like a buyer would) and instantly see how you show up across ChatGPT, Claude, Gemini, and Perplexity. You’ll see who’s being mentioned, what’s being said, and how your brand is positioned in real responses.

Behind every result is structured insight:

• A real-time Prompt Table showing your share of visibility per prompt

• Mention graphs broken down by model, topic, and prompt category

• Sentiment and framing analysis at the prompt level

• Alerts when you’re added, removed, or misrepresented in answers

Want to see how your visibility is shifting week over week? Track any prompt. Monitor how your brand moves up (or down) as your content, PR, or SEO strategy changes. See exactly when a competitor displaces you and why.

If ChatGPT describes you as a minor player — or doesn’t mention you at all — it’s not just a missed click. It’s a lost deal. A missed shortlist. A narrative you didn’t get to shape.

Probe doesn’t just tell you if you show up; it tells you why, how often, and what’s driving it. From prompt phrasing to citation patterns, Probe reveals the levers behind AI inclusion so you can take back control.

2. Understand why competitors win prompts and close the gap

Getting mentioned in AI answers is complex. Some brands keep showing up, others keep getting ignored. Probe shows you exactly why.

Start by tracking your most important prompts — the high-intent queries your buyers are likely to ask. You can track up to 30 per month (and more on custom plans). These are the core of your AI search TAM.

Every day, Probe reruns those prompts across ChatGPT, Claude, Gemini, and Perplexity. It captures where you show up, who else gets mentioned, your position, sentiment, visibility score, and citations — all in one table.

From there, you can:

• Sort prompts by visibility or rank

• Click into any prompt to see the full response across models

• See how your position has changed over time

• Monitor where you’re gaining — or losing — ground

Not sure which prompts to track? Probe suggests high-signal prompts based on your industry, competitors, and existing mentions — and you can accept or reject them with one click.

All of this rolls up into a full Competitive Insights dashboard:

• Your brand’s share of voice in AI search

• Average rank vs. key competitors

• Citation frequency and which content gets cited

• Recent mentions by model, prompt, and ranking

Mentions alone don’t matter. What matters is knowing what’s getting your competitors ranked — and how you can beat them.

3. Track real AI traffic and turn mentions into outcomes

Mentions are a start. Traffic is the outcome.

Most tools will tell you if you showed up in ChatGPT. Few tell you if that actually drove a session. Even fewer tell you where that traffic went or how it’s trending over time.

Probe closes that gap.

You’ll see:

• Total AI referral sessions across ChatGPT, Perplexity, Gemini, Claude, and more

• AI’s contribution to total site traffic (down to the decimal)

• Session trends over time, broken down by model and referrer domain

• Drop-offs or spikes that signal a visibility shift in the LLM layer

You can also track which landing pages are getting AI traffic — and which ones aren’t. Not every page that gets mentioned gets visited. Probe shows you which URLs are pulling sessions from ChatGPT and others, so you can spot high-performing assets, identify pages with visibility but no engagement, and rework what’s not converting. This is where visibility meets conversion strategy.

No more guessing if your AI visibility is making an impact. Beyond being an effective AI visibility optimization tool, Probe  ties model mentions to real traffic, so you can see exactly which AI platforms are sending visitors, what pages they’re landing on, and where your strategy needs work.