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Measuring AI Discovery: What to Track and Why It's Hard

AI-referred traffic is growing fast but often invisible in standard analytics. Here's what to track and why directional data is enough right now.

By Anthony Gale — Co-Founder, Geoffy

AI DiscoveryEcommerce GrowthAI Search
Measuring AI Discovery: What to Track and Why It's Hard cover image

AI-referred traffic is growing fast. Here’s why it’s often invisible in your analytics — and what to do about it.

Here’s a problem that catches a lot of ecommerce teams off guard: AI-referred traffic often doesn’t look like AI-referred traffic in your analytics.

When someone asks ChatGPT for a product recommendation and then clicks through to your store, that visit may show up as direct traffic, organic search, or simply “unknown.” The referrer data is frequently stripped or absent. And that means teams investing in AI discovery often can’t see the results — which makes it hard to justify, hard to optimise, and hard to report on.

Why attribution is broken for AI traffic

Traditional referral attribution assumes the user clicked a link in a browser. AI assistants change that flow. A customer might ask Perplexity a question, see your product recommended, open your site in a new window, or even just remember the name and search for it directly later. None of those journeys show a clear AI referral source.

This is a known problem across the industry. It’s not unique to any platform or analytics tool. It’s structural.

What you can actually measure

The good news is that some AI referral traffic is trackable with the right setup. Clicks from ChatGPT, Perplexity, Google AI Overviews, and Gemini do appear as referral traffic in standard analytics — you just need to know where to look and how to segment it.

Custom channel groupings and crawler log monitoring give you a directional picture of AI-driven activity. It’s not perfect, but it’s enough to understand trends, identify which discovery pages are generating traffic, and build a case for continued investment.

Why directional data is enough right now

The AI discovery channel is early. Attribution will improve as the platforms mature and standardise referral behaviour. The brands that will be best placed to measure it properly in two years are the ones building structured discovery infrastructure today.

Think of it like early SEO measurement — the signals were imperfect, but the brands that invested anyway built advantages that lasted decades.

The metric that matters most right now

Coverage. How many of the questions your customers ask AI assistants does your store have a well-structured, first-party answer for? That’s the underlying driver of AI recommendation inclusion — and it’s something you can measure and grow deliberately.

Geoffy tracks discovery coverage and helps you understand where your products are recommendation-ready and where the gaps are. See how it works →

Frequently asked questions

Why doesn’t AI traffic show up clearly in Google Analytics?

AI assistants often strip referrer data or users navigate separately after seeing a recommendation, so visits arrive without a clear AI source attached.

Can I track ChatGPT or Perplexity referrals specifically?

Some traffic from these platforms does appear as direct referral traffic in analytics. Custom channel groupings help surface and segment it.

Is AI discovery worth investing in if I can’t measure it precisely?

Yes — the same way early SEO was worth investing in before measurement tools matured. Coverage is the metric to build now; attribution precision improves as the channel matures.

How does Geoffy help with measurement?

Geoffy tracks discovery coverage — how many customer questions your store has a recommendation-ready answer for — and shows you where the gaps are.

About the author

Anthony Gale is Co-Founder of Geoffy, a Generative Engine Optimisation platform for ecommerce brands. He has spent more than two decades working in ecommerce and digital growth, helping retailers adapt to major shifts in online discovery.

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