Consumers have had AI-powered tools at their fingertips for years. The advances they’ve generated in search and shopping are well-known, but the ways they’re used and understood are still evolving. The rate of change is enough to cloud the view of even the closest observers and leave first movers feeling like they’re still playing catch-up.
If your brand is struggling to gauge AI’s influence on customers and your bottom line, you’re not alone. About one quarter of marketing leaders say they can’t connect AI-driven discovery to conversion at all, and as many say their analytics can’t handle AI attribution.1 And with multiple analyses finding that between 40% and 90%+ of searches yielding AI-generated answers end without the user clicking into a new page2, your team could be missing all but the simplest sequences where a user moves directly from an LLM response to your brand page and a purchase.
Consumers are getting recommendations from AI and completing their purchase journey through channels that mask its role. So how do we measure AI’s influence accurately? Your existing marketing analytics actually hold the information you need. You just have to know how to interpret it.
Read on for our breakdown of the three most important ways AI drives a shopper’s journey toward purchase and the best methods of measuring their impact on your products.
What It Looks Like: This is what occurs when someone sees your product recommended by AI, then navigates to a legacy search engine to investigate further. AI steered the process, but you see that another platform brought the customer to your doorstep. Analysis of our work with brand partners shows that this represents the majority of measurable AI-influenced discovery, but most brands misattribute it.
How To Read It: Start by comparing your branded organic search growth to category-level search trends. If your performance is outpacing the category, and if you didn’t buy that performance with increased paid media activity, then you’re probably benefitting from AI recommendations. It’s even more likely if conversion rates are increasing too, as AI shopping queries are often associated with greater purchase intent. It’s no surprise when we see a brand’s search trend exceed the category average after optimizing its product pages for AI discovery.
What It Looks Like: This signal manifests when a shopper sees your product recommended by AI, then navigates to a retailer like Amazon or Walmart to find it. AI’s role here is once again essential, but it’s not the last recorded step in the customer journey. This signal is the one least likely to be attributed to AI, but it’s actually AI’s most meaningful form of influence for most consumer brands. That’s because of the bottom line impact of a shopper with intent reaching a venue for purchase.
How To Read It: Assess the retailer channel performance of a selection of your product SKUs that have already been optimized for AI search visibility; that means high-quality product data, structured attributes, and off-site content consistency. Compare it to that of some similar SKUs that haven’t been given the same treatment. You can use AI intelligence tools to measure differences in recommendation rate and determine which SKUs get recommended, as well as where, when, and how prominently. If an improved recommendation rate corresponds to improved retailer-side traffic and sales, you’re seeing this signal in play.
Organizations where retailer data and brand analytics are relatively siloed should be prepared to build new links between the teams that manage them in order to fully understand AI’s impact on retail performance.
What It Looks Like: A shopper sees your product recommended by AI, then arrives at your page via the AI domain. Its role in the process is clear and easy to track. This is a natural starting point for AI influence measurement, but it’s by far the smallest of these three signals.
How To Read It: Focus on traffic quality instead volume. People doing product research with AI are high-intent shoppers, not casual browsers, and they convert at two to four times the rate of traditional organic traffic.3 That means ChatGPT, Claude, and Perplexity might be driving stronger outcomes for your products with fewer direct referrals overall.
Gemini operates differently because it registers as organic search traffic from Google, which creates a new diagnostic opportunity. Google click-through rates decline dramatically when a Gemini AI Overview appears for a query4, so you can consider it a win for your brand if your performance in the Google channel is growing or outpacing other organic search despite this broader pattern.
Each of these signals is important on its own, but AI’s full impact on your products can’t be determined without a comprehensive understanding of the role it plays as an origin point for searches and a driver of the awareness, intent, and conversion that all brands value. With a firm read on all three signals, your team can grade AI’s influence on performance and respond effectively instead of just counting the easiest clicks to attribute. For more on the subject, check out our latest white paper, or reach out to discover how our AEO is helping more and more brands win in AI search.
1. Branch, “AI Search and Discovery: Enterprise Benchmark Report,” 2025. branch.io/resources/white paper/ai-search-and-discovery-enterprise-benchmark-report. Survey of 300 enterprise marketing, growth, and digital leaders.
2. Estimates of zero-click rates vary by platform and query context. SparkToro’s 2024 analysis found 58.5% of all U.S. Google searches end without a click; SEMrush’s AI Mode Impact Study found rates of 80–93% in AI-specific search experiences depending on format.
3. Multiple independent analyses put AI-referred conversion rates at 2–4x traditional organic. Sources include Microsoft Clarity (3x, across 1,200+ publisher and news sites), Knotch (3.7x site average, 2025), and multiple ecommerce-specific analyses in the 4–5x range. Methodologies and comparison groups vary.
4. Seer Interactive, “AIO Impact on Google CTR: September 2025 Update,” November 2025. seerinteractive.com/insights/aio-impact-on-google-ctr-september-2025-update. Study analyzed 3,119 queries across 42 organizations and 25.1 million impressions.
