GEO Metrics: How to Measure Your Brand’s Visibility in AI Search

Go ask ChatGPT to recommend the best tool in your category. Then ask Perplexity. Then Gemini.

Did your brand show up? With a link, or just a passing mention? Or did it not show up at all?

If you can’t answer those questions, you’ve found the exact problem Generative Engine Optimization (GEO) is trying to solve. 

SEO experts have spent decades refining how we measure SEO. Rankings, traffic, click-through rates, and domain authority; the dashboard is well-established. 

But when it comes to GEO, there’s nothing of that sort. There’s no position #1 in a ChatGPT response. There’s no SERP to screenshot. And yet, brands are being recommended (or ignored) by AI engines millions of times a day.

Well, the measurement problem is real. And I won’t pretend we’ve cracked it. Nobody actually has. But after working across the SEO and AI visibility space for years, I can tell you that the brands figuring out GEO metrics right now are going to have a massive edge.

At Quattr, we’ve seen this firsthand: Brands that start measuring AI visibility early build structural advantages long before the rest of the market catches up.

Why Traditional SEO Metrics Fall Short for GEO

Before we get into the new stuff, let’s talk about why you can’t just repurpose your existing SEO dashboard for GEO.

When someone types a query into Google, you can track rankings, impressions, and clicks through Search Console. Quite straightforward, right?

But AI engines don’t work that way. When someone asks ChatGPT “what’s the best project management tool for remote teams,” the model synthesizes information from its training data, possibly retrieves live sources (if it’s a RAG-enabled engine like Perplexity), and generates a single, conversational answer. 

Your brand either makes it into that AI answer or it doesn’t. And even when it does, the how matters enormously; are you cited with a link, mentioned by name without attribution, or described vaguely as “tools like X”?

Traditional metrics like keyword rankings and organic sessions simply can’t capture this. You need a new measurement framework. And that framework is still being built, but the foundational metrics are already becoming clear.

7 GEO Metrics You Should Be Tracking

Here are the 7 most important GEO metrics that you should be tracking:

1. AI Visibility Score

The first and the most important GEO metrics is: AI visibility score.

An AI visibility score measures how often your brand surfaces in AI-generated responses across ChatGPT, Gemini, Perplexity, and Google AI Overviews for a defined set of prompts in your space.

It’s typically expressed as a percentage or a composite score across a defined set of prompts relevant to your industry.

However, there’s no universal standard for calculating this yet. Different GEO tools define it differently, weight different AI engines differently, and use different prompt sets. That’s fine. 

One mistake I see teams make: they check their AI visibility score once, feel good (or bad) about it, and never look again. The score is only useful as a trendline. A single snapshot tells you almost nothing. The absolute number matters less than the direction.

So, don’t obsess over the absolute number. What matters is the trend. Is your AI visibility trending up? Is it responding to the content work you’re putting in? That directional signal is what you should look after.

2. Brand Mentions vs. AI Citations

Well, this distinction is critical and most people conflate the two.

A brand mention is when an AI engine references your brand by name in its response. There’s no link or source, just mention, meaning AI knows you exist.

Something like: “Popular tools in this space include Quattr, Ahrefs, and Semrush.”

On the other hand, an AI citation is when an AI model directly references your brand’s content in the AI answer as a link or footnote. It acts more like word-of-mouth in the digital world.

For example, “According to Quattr’s research on search visibility…” That’s the AI engine telling the user: this source was good enough to build my answer on.

Track both, but don’t weigh them equally. Getting mentioned a lot but rarely cited usually means your brand has recognition but your content isn’t authoritative or structured enough for AI to treat as a primary source. That’s a content quality signal, not just a visibility signal.

3. Share of Voice in AI Answers

Of all the GEO metrics on this list, this one changes decisions the fastest.

For a defined set of prompts (the top 50 questions your ideal customer might ask an AI engine, for example), how often does your brand appear versus your competitors? That’s your AI share of voice. 

This is, in my experience, the single most actionable GEO metric. It immediately tells you where you’re winning, where you’re losing, and who’s taking your place.

I’ve seen cases where a brand dominates organic search for a topic but barely shows up in AI answers, while a smaller competitor with better-structured, more frequently cited content takes the AI share of voice.

If you had to pick a single GEO metric to track, this would be my recommendation. It tells you where you’re winning, where you’re losing, and exactly who is winning in your place.

4. Prompt-Level Performance

This is where GEO measurement gets granular, and genuinely useful.

Instead of looking at your overall AI visibility, you zoom into individual prompts and evaluate your brand’s performance on each one. “Best CRM for startups.” “How to improve website speed.” “What is generative engine optimization?” Each prompt is its own micro-competition.

Tracking prompt-level performance lets you identify specific content gaps.

Maybe you’re showing up in 8 out of 10 prompts related to technical SEO, but completely absent from prompts about content strategy. That tells you exactly where to focus your next piece of content.

It also helps you understand which types of prompts your brand wins on. Are you stronger on “what is” educational queries? Or “best tool for” commercial-intent prompts? This kind of insight is incredibly valuable for content planning.

We’ve started treating prompt-level tracking at Quattr the way we used to treat keyword-level tracking in SEO.

5. Citation Quality and Depth

Getting cited in a Perplexity footnote is different from being quoted in the opening paragraph of a detailed ChatGPT response. Position, depth, and context all matter.

When auditing citation quality, I look at a few things: Is your brand mentioned in the first few sentences (high prominence) or buried at the bottom? Is the AI quoting or paraphrasing your content directly? Does the link point to a specific high-value page, or just your homepage?

This metric is harder to quantify systematically, but it’s worth auditing regularly. 

I recommend doing a manual citation audit at least monthly, pick 20-30 of your highest-priority prompts, run them across major AI engines, and evaluate the quality of each citation you receive. It’s time-consuming, but the insights are unmatched.

6. Sentiment in AI Responses

This is the GEO metric that the majority of people aren’t tracking yet, and it should concern more people than it does. Think about: what is the AI saying about your brand when it mentions you?

An AI engine could mention your brand and still frame it negatively: “Brand X is popular but frequently criticized for its steep learning curve” is technically a mention, but it’s not doing you any favors.

Tracking sentiment in AI responses tells you whether you’re being positioned positively, neutrally, or negatively when AI engines bring you up. This is especially important for brands in competitive categories where AI engines might surface reviews, comparisons, or Reddit threads that don’t paint you in the best light.

If you spot negative sentiment patterns, that’s a signal to invest in reputation management, publish more positive proof points (case studies, customer stories, third-party validations), and work on shaping the narrative around your brand online.

7. AI Referral Traffic

This is the most familiar metric on this list, and the easiest one to start tracking today.

AI engines that cite sources with links (Perplexity, Google AI Overviews, Bing Copilot, and increasingly ChatGPT) can drive actual referral traffic to your site. You can track this in Google Analytics by filtering for referral sources from AI platforms.

Now, I’ll be transparent: AI referral traffic is still a small fraction of total traffic for most sites. 

But it’s growing fast, and the quality tends to be high. People who click through from an AI-generated answer have already read a summary of your content; they’re coming to your site with context and intent.

The volume matters less than the trendline. A consistent uptick in AI referral traffic is the most tangible proof that your GEO work is translating into real-world results.

Building Your GEO Measurement Framework

If you’re wondering where to start, here’s a practical approach.

1. Define your prompt universe. Identify the 30-100 prompts most relevant to your brand and category, what your ideal customer would ask ChatGPT, Perplexity, or Gemini. This is your GEO keyword list.

2. Benchmark your current state. Run those prompts across major AI engines and document where you appear, how you appear, and who else shows up.

3. Pick your primary metrics. Start with the share of voice, the AI visibility trend, and the AI referral traffic. These three give you breadth, competitive context, and a hard business outcome.

4. Set a review cadence. AI answers shift as models update and competitors optimize. Monthly reviews at minimum, weekly if you’re actively running GEO campaigns.

5. Connect metrics to business outcomes. Your executive team doesn’t care about AI visibility scores in isolation. Build the bridge between “we got cited by ChatGPT for 15 new prompts this quarter” and “that drove X qualified visits and Y conversions.”

GEO Measurement Is Early. That’s Exactly Why It Matters.

GEO is still in its early stages, and metrics aren’t standardized yet. There’s no universal “GEO Search Console” that everyone agrees on.

But here’s what I’ve learned from years in the SEO space: the brands that started measuring SEO seriously in the early days, even with imperfect data, are the ones that dominated later. The same pattern is playing out with GEO right now.

You don’t need perfect data. You need a consistent habit of measurement, a willingness to adjust as the ecosystem evolves, and the understanding that in AI search, unmeasured is the same as invisible.

And in a world where AI is increasingly writing the answers your customers read, being unmeasured is the same as being invisible.

How Quattr Approaches GEO Measurement

Most companies reading this will agree that GEO measurement matters. Very few will implement it in a way that compounds.

The gap is not awareness. The gap is in operational capability.

Tracking prompt universes manually works for a few weeks. Auditing citation depth once a quarter feels responsible. Watching AI referral traffic tick upward looks promising. But without a structured system connecting prompt tracking, entity strength, citation quality, and execution velocity, the effort fragments.

That fragmentation is where most GEO strategies quietly stall.

At Quattr, we built our GEO measurement layer specifically to close that gap. Not as a vanity “AI visibility score,” but as an operational system that continuously maps:

• Which prompts you to win and lose
  
• How often are you cited versus merely mentioned
  
• Where entity ambiguity weakens AI confidence
  
• How shifts in AI visibility correlate to real pipeline signals
  

Because measurement in isolation is noise. Measurement tied to execution is leverage.

If your team is serious about building citation share before the ecosystem standardizes, the advantage window is now, not later.

Explore how Quattr operationalizes GEO measurement and execution, and see what your actual AI visibility looks like across the prompts that matter.