The Generative AI Report Sucks – Let’s Make It Brilliant
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Harry Clarkson-Bennett 42 minutes ago ⋅ 12 min read Harry Clarkson-Bennett SEO Director at Telegraph Bio Follow Finally, we have visibility into how often our content features in Google’s generative AI features. Now, we can see exactly how many clicks we’ve lost to… Rubbish stuff, or is it? (Image Credit: Harry Clarkson-Bennett) Hello, sorry, is that Sundar? I think the Generative AI report is broken – I can’t see the click data. You what? You meant it to look like that? Oh. Is that because AI features don’t send any cli… No, that’s just a coincidence, you say. Given this has taken up the best part of two years of our working life, I’d have liked something a little more concrete to show to clients, friends and my long-suffering wife. I can’t have scintillating dinner conversation without click-level, generative AI data. Something must be done – and I think I have a solution. Technically, we have generative AI data in search. First-party visibility data should be a huge deal. But there are limitations. Impressions, impressions everywhere, but not a drop to drink. If you’re unfamiliar with how an impression is counted, it’s worth a quick wander down John Mueller trail: “The impressions are based on links to your site being shown in AI Overviews / AI Mode. I don’t know if just a favicon would be linked, but if it’s linked to a page on your site, that would count… a link shown directly can count, while a link that requires activation only counts after that activation.” Directly shown links can count without expansion; links requiring activation count after activation. Not that helpful really. However, I don’t think the report is useless. At all. I think it’s almost useful. It provides first party visibility data in arguably the most used AI interface in the world. At least not directly. Click data would take us halfway there. But to understand your true exposure, you would need to understand how your traffic and commercial value is intercepted by said AI system(s). Server logs give us a proxy for demand but they are an optional extra. You can still get some superb insights with GSC and audience and commercial data from GA4. A step-by-step guide to working out your resilience and exposure using Google’s intentionally half-baked reporting. As ever, you can listen to a short overview of this, with a sneak peek of the workbook here: Take the total sitewide AI impressions from the Generative AI report, then export the page-level data. Worth noting that the Pages export doesn’t necessarily represent every page or impression because of the thousand-row limit. That matters because we’re going to classify those URLs and analyse visibility by content area. To start with, subfolder is more than fine: If you’re smart and you understand how to get more out of Search Console, then you can export the report at a subfolder level and combine data from each property. For smaller sites, this shouldn’t represent much of a problem. The page-level export lets us compare different content areas and answer a few useful questions. Is most of our AI exposure coming from News, Sport or Business? Is that visibility spread across lots of URLs, or concentrated among a handful of ‘performant’ pages? You can still get the trend of AI impressions – up or down over time – directly from GSC. We also need to understand how much of Google’s reported AI visibility our page-level dataset actually represents. If you go over the 1,000 row limit, you are seeing a sample. Now, we know where AI visibility is concentrated. But how much does that actually matter to the business? Pick one primary commercial KPI – revenue, subscriptions, conversions, leads, etc. – and use the same KPI across every subfolder. The metric doesn’t really matter, provided it represents business value and you use it consistently. Please don’t overcomplicate this. Believe me. My locks might be lustrous, but after 10+ rewrites they are grayer than when I started. Now we can start comparing visibility against commercial value. Here, Business has high AI visibility, but higher revenue. Technology has comparable AI visibility, but significantly less revenue. Sport has very low visibility, but a larger portion of revenue. For this, you’ll need some third-party SERP data. DataForSEO is great. Other scraping tools are available, per BBC guidelines. If you already have a representative keyword universe for each subfolder, use that. If not, the top 100 or 1,000 GSC queries per site or section is a perfectly reasonable place to start. For each query, establish whether it triggers an AI Overview or other AI-mediated search experience. This doesn’t tell us that AI actually substituted a click. You’d need some kind of user testing panel for that and I’m not your guy for that level of rigor. You don’t need this data. Substitution is an enhancement, not a requirement. If you have it, great. If you don’t, you can still calculate Commercial Exposure. If you’re new to the game, server logs are fantastic. They give away detail you cannot get anywhere else. They look a little scary and technically, you don’t need them for this. But they add a layer of uniqueness and granularity you cannot replicate. That last bit is increasingly important. Different crawlers are doing different jobs, so rather than lumping everything together as ‘AI traffic’, we can separate activity into training bots, search bots and retrieval bots.
Source: Search Engine Journal
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