Tracking AI Overviews: What the data actually shows

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Free and premium plans Agent Hub Your central home for building and managing AI agents across the platform Learn more Small Business Bundle The Starter edition of each product, built for startups and small businesses Learn more AEO (Beta) Answer engine optimization tools that track and improve your brand's visibility in AI results Learn more HubSpot Marketplace Connect your favorite apps to HubSpot See all integrations Home Marketing Tracking AI Overviews: What the data actually shows Tracking AI Overviews: What the data actually shows Written by: Erica Santiago THE STATE OF AEO IN 2026 Dive into data about how marketers around the world are adapting to AEO and learn how to implement AEO yourself. AI Overviews have shifted how audiences discover brands. Gone are the days when users would click through multiple search results until they found what they’re looking for. Now, AI Overviews answers questions directly on the results page, meaning brands are either cited or ignored without users ever visiting a website. The changes brought on by AI Overviews mean marketers need to adjust the way they track brand visibility. Here’s what you need to know about tracking AI Overviews and what data actually shows. Traditional rank-tracking tools cannot measure the exposure generated by AI Overviews, which now sit above featured snippets as the highest-visibility position. AI Overviews consolidate multiple sources into a single answer, making inclusion — or exclusion — a meaningful driver of both brand perception and traffic. In my experience, this shift catches marketers off guard precisely because their rankings look fine, making the problem invisible until you know where to look. Volatile citation patterns — Unlike organic rankings, AI Overview citations don’t correlate reliably with ranking position. A page ranking fifth may be cited while the top result is ignored. Tracking reveals which content attributes actually earn inclusion. Query category variation — AI Overviews appear more often for informational and how-to queries than transactional ones. Knowing which target keywords trigger an overview considerably shapes your content strategy. Competitive intelligence — If a competitor is consistently cited for your target terms, that’s a strategic signal you can’t act on without visibility. Measurement gaps — AI Overviews suppress clicks even when rankings hold, creating the “ranking fine, traffic dropping” paradox. Tracking helps explain it. Dive into data about how marketers around the world are adapting to AEO and learn how to implement AEO yourself. The way I think about it, tracking AI Overviews is less like checking a dashboard and more like building a case — one data point at a time. It starts with a baseline: a structured snapshot of which queries trigger AI Overviews, which cite your content, and which surface competitors. Without that starting point, there’s no meaningful way to measure change. From that baseline, each SERP capture adds a data point that either reinforces or challenges what you recorded before. Over weeks and months, those observations become benchmarks — reference points that reflect normal performance and allow you to distinguish meaningful shifts from routine fluctuation. That distinction is what separates reactive content decisions from informed ones. I’ve put together a five-step checklist below outlining how to put this into practice. Step 1: Define your keyword set — Identify informational and how-to queries most relevant to your business. Prioritize keywords where you currently rank. Transactional keywords can be deprioritized for this exercise. Step 2: Establish a baseline — Run your keyword set through your tracking tool and record the initial state: which queries trigger an AI Overview, which cite your domain, and which cite competitors. This snapshot becomes your reference point. If you’re not sure where to start, HubSpot’s AI Search Grader is a free, one-time diagnostic that shows how your brand currently appears in AI-generated search experiences — a useful starting point before you begin logging data over time.

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Source: HubSpot

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