A customer asks ChatGPT for the best [product in your category]. ChatGPT names three brands. They search one of those brands on Google. They buy.
What does your analytics say drove that sale? Google organic search. Maybe a direct visit.
ChatGPT is invisible in the attribution chain, even though it was the moment the customer made their decision.
This isn't hypothetical. It's happening at scale, and most Shopify merchants have no visibility into it.
The attribution problem
Traditional ecommerce attribution works on a simple assumption: you can trace the customer's digital journey. They see an ad, click through, browse, and buy. Each step leaves a traceable footprint.
AI breaks this model.
When a customer asks ChatGPT a question, that conversation happens inside ChatGPT. The recommendation happens inside ChatGPT. The customer then goes to a search engine, types a brand name, and arrives at a store. But the AI conversation that shaped their decision left no trace in your analytics.
The result: merchants are making decisions based on attribution data that doesn't capture an increasingly important part of the customer journey.
If you're seeing unexplained direct traffic, or branded search growing while you haven't increased brand spend, AI influence is a plausible explanation. The customer found you through AI, but they completed the journey via search or direct.
What this means in practice
You're almost certainly undervaluing channels that feed AI visibility. If editorial coverage on a review site generates zero attributed revenue but actually drives AI recommendations that drive branded searches that drive purchases, your analytics make that review site look worthless.
You may be over-attributing SEO. Branded search traffic is often credited to SEO or direct when the real driver was an AI recommendation that sent the customer to Google to find you.
You have no way to know how your competitors are performing in this channel. Unlike Google, where you can check their rankings, you can't check how often ChatGPT recommends your competitor versus you without actively running queries.
This is the AI attribution blind spot: a channel that's already influencing purchasing decisions, with no standard measurement framework, no equivalent of Google Search Console, and no way to optimize what you can't see.
How to get partial visibility now
There's no perfect solution yet. No tool gives you a clean "AI-driven revenue" number. But there are ways to build a rough picture.
Check Google Search Console for AI-pattern queries. ChatGPT users who then search Google often use longer, more conversational queries, the style of what they typed into ChatGPT. In GSC, filter for queries containing "best", "vs", "review", "worth it", "alternative to". If these query types are increasing while you haven't changed your content strategy, AI influence is one possible explanation, though this is indirect and can't confirm causation. It's a signal worth tracking, not a reliable AI measurement tool.
Ask Perplexity and AI Overviews what they say about you. Run 10-15 queries across your customer journey: discovery queries ("best [your product type]"), comparison queries ("[your brand] vs [competitor]"), and trust queries ("is [your brand] worth it?"). Record what each AI system says. This gives you a qualitative picture of your current AI presence.
Track your brand search trend. Google Trends for your brand name, month by month. If branded search is growing, more people are seeking you out specifically, and some portion of that growth is AI-driven.
Run the same queries monthly. AI responses aren't static. They change as models update. Tracking what AI says about you over time, even manually, shows whether you're gaining or losing ground.
The measurement gap is temporary
This is an early-market problem. The equivalent of Google Search Console for AI doesn't exist yet, but the tools are coming.
Perplexity has started showing some analytics to publishers it works with. Google's AI Overviews are increasingly trackable via Search Console for cited domains. Purpose-built AI visibility tools like SeenByAI automate the query-and-score process across the major AI platforms.
The brands that build AI visibility tracking into their measurement stack now, even imperfectly, will be ahead when attribution tooling catches up. The brands that wait until measurement is perfect will find they've lost ground they can't recover.
What you should do
Step 1: Accept that the attribution gap exists. Your current analytics undercount AI's influence on your sales. This means investments in editorial coverage, reviews, and comparison content may be more valuable than they appear in your attribution model.
Step 2: Run a baseline audit. Spend 30 minutes querying ChatGPT, Perplexity, and Google with the questions your customers would ask. Screenshot the results. This is your baseline. You'll want to compare against it in three months.
Step 3: Track branded search as a proxy. If branded search grows, something is driving awareness. AI is one possible driver. Combined with your content activity, you can build a rough model.
Step 4: Measure AI visibility directly. Whether manually or with a tool, start tracking how often you appear in AI responses across the key queries in your category. This is the closest thing to a benchmark that exists right now.
The attribution problem is real and unsolved. But the brands that understand it and invest in AI visibility even without perfect attribution will be the ones whose branded search is growing while their competitors wonder why their organic traffic is softening.
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Written by Stu Miller, Founder of SeenByAI and CEO & Co-founder of Smart Insights. Stu has spent 16 years helping ecommerce businesses grow their digital marketing, and built SeenByAI after experiencing the AI visibility problem first-hand running his own Shopify store.
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