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All things Generative Engine Optimization (GEO). A breakdown of all that's happening in the world of AI search.
Hello, and welcome back to The GEO Show. I'm your host, Paris Childress, and we're recording on Friday, August 21. And this is episode two. I've got a crop of new stories that I wanna run through today from my SEO and GEO briefing and give you some of my thoughts. So let's start with the first story, which is that Google's new GEO reporting currently has a data bug.
Paris:Google says a logging error has artificially reduced impressions in Google's Google Search Console's generative AI performance report since August 13 and it remains unresolved. So this is about one week old at the time of this recording and this is very interesting because this is a new part of Google Search Console, the generative AI performance. I think it has just been rolled out globally, and Google is still struggling to get this right. So what it tells me is that first party GEO data is extremely valuable but it's not yet mature enough to trust blindly. That story came from search engine land.
Paris:And for those of you who are not aware, Google Search Console is now showing your basically citations of your pages. So you go into the generative AI performance report and you can see at the page level the number of what they call impressions which effectively means citation appearances in AI overviews and likely AI overviews and AI mode. But don't trust the data from the period of August 13 till well, at least I think until today. Number two story is that SimilarWeb has launched competitive intelligence for ads inside AI Answers. So SimilarWeb's new AI ads dataset tracks placements across ChatGPT, Google AI mode, and AI overviews using user panel data, real user panel data.
Paris:And SimilarWeb says that 26 of ChatGPT responses currently carry sponsored ads and nearly 30% of ad eligible AI mode queries now show ads. So we're talking about a sizable chunk now of responses from ChatGPT and Google's AI mode. 26% of responses from ChatGPT, 30% from AI mode are now in the case of ChatGPT carrying sponsored ads and in the case of Google AI mode eligible to show ads. So this is really proving that the ads have already started to make a major dent in the inventory of chats, of AI chat. So also what's interesting is that now paid search or paid AI search is becoming measurable enough to operate as a real media channel.
Paris:So that's the beginning of a whole new paid advertising channel that's opening up right now and it's gonna be an interesting story to follow. Alright. Moving on to the next story. OpenAI reported in their help center recently has switched on a more aggressive conversion matching system for existing advertisers. So they've enabled something called automatic advanced matching or AAM for existing ChatGPT ads.
Paris:WebPixels by default, the pixel can detect supported customer IDs. Sorry. The pixel can detect supported customer information in forms, normalize what's called SHA-two 56 hash in browser and use it when click IDs are unavailable. Advertisers can of course opt out of the pixel. So that's a familiar term that we've heard before, the pixel.
Paris:I know we've talked about Facebook pixels hundreds of times in our agency and now ChatGPT and OpenAI ads has their own pixel. So they are rapidly acquiring the attribution infrastructure of Google and Meta starting with the Pixel. So that is a real sign of the maturity of OpenAI's ad platform. The next story is coming to us from PPC land and it's about Apple. Apple dramatically expanded Apple bots published crawl infrastructure by adding 4,656 IP addresses across 21 new ranges, which is a 194% increase.
Paris:Apple did not explain that change in any way. But this is a very interesting and meaningful infrastructure signal because it is the first time that I have really even heard or thought about Apple bot. Of course, we've always known about Google bot and now OpenAI's bots. But Apple has Apple bot and Apple bot is dramatically ramping up their infrastructure, their crawl infrastructure. So what could that mean is anybody's guess.
Paris:Are they gonna launch a an Apple AI search engine or an LLM of their own? Who knows? Is that gonna be something that might be on the edge or living on devices on iPhones and iPads and Macs? I think most likely, yes, actually. And then it's probably the reason why Apple is ramping up its investment in its crawl infrastructure.
Paris:I do think that they're headed towards on device AI and that that is gonna be a major play. That's probably gonna be coming later this year or next. Alright. Moving on to the next story. And that is coming from Ahrefs.
Paris:Ahrefs introduced an AI adjusted volume metric for prompt demand. So what does that mean? AI adjusted volume. So now Ahrefs of course has always measured keyword volume. Now this is AI adjusted volume for prompts.
Paris:So So I think what they're attempting to do here is to build a metric for AI prompts that is similar to keyword volume metric. So it's confirmed that brand radar, their AI feature brand radar now estimates platform specific AI demand by taking a Google keyword volume and applying ratios derived from Ahrefs aggregated AI referral traffic relative to Google organic traffic. And AI, Ahrefs explicitly says that the metric is not actual AI impressions or an AI search TAM but they're trying to get closer. They're trying to get closer to keyword volume for AI prompts. So let's unpack this method.
Paris:They're taking keyword volume which they have good accurate data for and they're applying ratios that are derived from Ahrefs aggregated AI referral traffic. So traffic coming to Ahrefs via AI referrals relative to Google organic traffic. So let's just say if for the sake of argument, if maybe their Google organic traffic represents 50% of all traffic coming into Ahrefs and the AI referral traffic is say 5% and they're taking that ratio, so it's a one to 10 ratio from five to 50 and they're saying that effectively that if this key, the keyword volume sending this organic traffic is 50, then that must imply that the AI traffic is worth five and so there, the AI adjusted volume in this case is gonna be that 5% number or the volume of that 5%. I think that's a pretty interesting approach. I do still think though that Ahrefs and any other classic keyword research tool or SEO tool, I do think that they are still very far off from being able to forecast and report on prompt volumes.
Paris:I just don't think that's ever gonna exist. I don't I don't think that even OpenAI through its ad platform is gonna surface that anytime soon. And we already see that Google's AI mode and and AI max is already removing the keywords. So they they also don't want you to start or to continue to research keywords and keyword volumes as you transition into AI Max in Google Ads. So keyword volume is clearly sunsetting here and coming in its place will not be prompt volume.
Paris:So that is not great for attribution and measurement but that is the real world we're heading towards. Alright. Let's go on to the next story. There's new brand research highlighting that AI has a categorization problem. A company called Fractal has analyzed, search engine lands generated 4,320 responses and 8,500 unique brand references across multiple models.
Paris:It found a strong traditional, it found that strong traditional search brands that barely appeared for categories they expected to compete in while other brands maintained materially, while other brands materially overperformed their SEO authority. Bottom line, what this means is that a model can know a company extremely well, yet fail to associate the company with the category that it wants to own. So what does this mean actually? It's really interesting because AI can still have a lot of accurate information that it provides about your brand but still miscategorize you. So that is a GEO problem, category association.
Paris:So a lot of the SEO and the GEO work that we should be doing is also not only informing LLM crawlers about our brand and with accurate claims about our brand, but also reinforcing our positioning through comparisons and customer proof, partner references, reviews, and earned media. But by comparing our brand to other brands in the category, we are reinforcing our category position and hopefully giving the right categorization information to AI crawlers. Alright. Now we are moving on to the next story. Let's see here.
Paris:Alright. Alright. This will be our last story of the day. ChatGPT's different modes increasingly search different webs. That's interesting.
Paris:So this is from search engine land. According to Resoneo's August update, which found that found Freethink drew 74.7% of results from OpenAI's own retrieval system while paid thinking drew roughly 75% from Google derived results. Paid thinking also narrowed its source set from July to August while use of site colon searches increased sharply at higher reasoning levels. This is observational vendor research. It's not OpenAI documentation.
Paris:The interpretation here is that ranking in ChatGPT is becoming an almost meaningless single KPI. And that's something that I think we've always suspected as we move from SEO into GEO, which is that this is no longer a game of ranking. We are not trying to rank pages. We are trying to surface brand passages that are embedded in pages but we're not trying to rank pages because it's essentially a meaningless exercise. There's too much volatility.
Paris:Alright. That's a wrap for this episode number two, and hope you all enjoyed it and looking forward to seeing you next time. So long.