AI Search Visibility Query Fanouts: How to Track Every Fanout Query for AI SEO Tools and SaaS Companies

James Dooley: AI visibility query fanouts. Today I'm joined with Jay who is the founder of Radar Kit AI. So Jay, pleased to meet you and obviously we've had a lot of private discussions about query fanouts. Um you've taught me quite a lot to be honest with you about different query fan outs on chat GPT and on Gemini and recently on C-Ilot. So how important do you believe with regards to AI SEO or GEO or LLM optimization is query finance?

Jay: Yeah. So the thing is when we used to do SEO we used to go after the queries that we get into the you know uh from this all these uh tools like HF and all. So we get the volumes and then we go after those keywords and only you know we go after the lowh hanging fruits low KD keywords and we used to create content. But now uh if we want to create content that is optimized for the AI AI tools you know AI search engines like chat GBT perplexity and all we have to go for the keywords that these LLM tools are searching on our behalf. So uh let's say if I'm asking uh you know give me the best CRM tool. the LLM knows that okay this person uh you know is just asking a very vague or let's say very uh you know not not very categorized term but he's asking something where I can give you multiple options so he goes in the background he will search for best AI you know best CRM tool for small business best CRM tool for someone who is looking for an affordable options best CRM tool for large business so it will actually search different things and then it will read all the content on those uh you know on the on the content on the pages that are ranking for those terms and then it will read everything for me and then summarize it and give it give an answer for for me yeah in its uh answer like okay since you asked to best CRM software these are the options you can consider if you're looking for a affordable one these are the options if you're looking for a you know if you're a small team and if you want to use this so the that is why we should use query fanouts if if uh if you want to go for the main keyword but If we are not able to get citations for that keyword, we can actually target the keywords that the AI is actually searching in the background.

James Dooley: Yeah, for sure. So if someone's go searching in the AI and do a a specific search query, it then extrapulates synthetic queries to then try to determine exactly the search intent and get a better kind of set of results for for what you're doing. But for anyone who's watching this, does the different LLMs bring back different query fan out? So if you was to do chat GBT and you was looking at a query fan out for chat GBT is that different than a query fan out on Gemini or a query fan out on core pilot.

Jay: Yeah, that's a good question. So the thing is uh as of now what we have seen only three models are actually giving you the query fan outs. So chat GPT is giving it in the UI. So if you're using Chrome, you can actually catch those fan outs and then copilot is also doing it in the in the UI. Gemini is giving you in the API. So if you're using the API, you can actually catch those uh APIs and yes there are differences. So chat GPT sometimes uses your own uh history. So if it knows that you're a e-commerce owner, so most of the questions it it will actually search for okay so since this guy's asking for a CRM software and I know that okay he's a CRM you know he's a small business owner so let me just suggest him that. On the other hand, copilot uh and you know Gemini AMO and everything they they work as a search engine. So they'll just search you know synthetic things uh nothing personalized for you and that is it.

James Dooley: So on there on the personalization if let's say I owned a large franchise or an enterprise brand would them synthetic queries on the query fan out be different to someone who is always looking for cheap. They're a solopreneur. the AI knows that that's who they are. Would those synthetic queries of query find be different because of the personalization?

Jay: Yeah, if it is on. So in Chady mostly uh most of the times I guess when you sign up right now uh that option is the only the memory option is on personalization is off. So if you if you you have actually turned it on and you have allowed chat to reference your uh you know your uh your history uh for for making its answers then yes the answer will be different because they are on each and every answer they are going to give you a very personalized option. So based on that panouts can be also different.

James Dooley: And then with regards to obviously you're the founder of radar kit and obviously you extrapolate and you get these synthetic queries within radar kit but for anyone that says I don't want to sign up to an AI visibility tool. I don't want to sign up and pay. Can you just share your screen and show anyone that might be able to run a search and then as they run that search then they can then physically see like in the network tab or however it's done how they could go and see what synthetic query find out terms are being used.

Jay: Perfect. Let's do it. Yeah. I'll just show that. Show my share my screen and show you live. Okay. Yeah. One sec. Which one is it that you're going to be as you're going to share the screen now? Which one is it that you're going to be kind of getting the query fan notes for? Would it be chat GPT?

James Dooley: Chat GPD. Yes.

Jay: Yeah. Yeah. Yeah. Yeah.

James Dooley: Can you see my screen?

Jay: Yeah. Your screen's being shared there now. Yeah.

James Dooley: Yeah. So, let's just go to chatgvd.com and we click on right click. We click on inspect and then

Jay: you've gone in for anyone who's watching the audio version only. You've gone to chatgpt.com. You've rightclicked and gone inspect and then gone through and clicked onto the network tab.

James Dooley: Yeah. Then you search for best CRM software.

Jay: So then you're actually performing the search while that's open.

James Dooley: Yeah. And then you click on the conversation.

Jay: So there's a there's a drop down there for conversation. Yeah.

James Dooley: Yeah. So we go down and we actually search for one second

Jay: and then within the response tab there and presume you're going to search for the actual query.

James Dooley: Yep. So we can just copy everything if you want. You can just open it on edit pad or any editpad just conversations tab. You can just search for the query.

Jay: Yeah.

James Dooley: And we can see that. Okay. So it actually so for this term actually did it did not perform a query fan out one sec.

Jay: Yeah. No it did. So can you see this one?

James Dooley: So there was there was a query called best CRM software 2026 small business enterprise comparisons.

Jay: So this was this was the only query I guess it searched for. So it depends on my search to search history. Sometimes it triggers more than one, sometimes it will trigger more than three depending on the query uh query to query. Since I just searched for best CRM software as you can see it only searched for one uh term that is the best CRM software 2026 small business enterprise and comparison. So it is you you know they they don't use grammar or stuff like that. They just want lot of pages to learn from. So within this one uh it has actually searched for small business as well as uh enterprises as well as comparisons. So what you can do is you can utilize this fan out create content somewhere around you know for a small business around as well as for the year as well. So you can just go for a content uh like best CRM software for small business in 2026. So you you increase your chances of getting you know cited as well as getting more visibility for this storm or or else you can just go for the enterprise and 2026 include that. So this is how like we are tracking it within the UI.

James Dooley: Yeah. I mean what's crazy there is to actually rank for best CRM software is a very very difficult triagram and keyword to go after. But if you then was going after best CRM software 2026, listing all comparisons of small business CRM systems and enterprise systems and stuff like that, and you go in doing all them comparisons on the page and doing maybe versus type keywords, then all those that could come back because of the comparisons could give you better chance of being cited. If you've got like a low domain authority site, you're still able to try to get into the sources within that's specifically on the query fan out of chat GPT. So anyone's watching this obviously if you can go into it there you can go into rightclick inspect go into the network tab and then perform the search and then you can physically see what the query fan out is. Obviously, uh Jay, you own Radar Kit and a lot of my team are using it at present and they absolutely love it. There's other AI visibility tools that people could be using. Um but obviously since me and you having the arguments and debates internally on the query fan outs and you say, "No, James, you're using certain tools there and they're not physically extrapulating the real query fan out terms." I was like, "No, they are. Look, look at this tool." and you're going all what they're doing is coign similarity or looking at like LSIs and variations some of them just using the auto suggest and getting different keywords which is still good and still worth going after but you opened my eyes up to physically using the API and physically going grabbing um the information it's just made it for me so much easier to use Radar Kit to then go and perform that search so I think the team love it obviously they can go and do the search query they and check to see what sources are being cited, but also using radar kit to get those um query find out terms. Is my question to you does radar kit pull is it only chat GPT query fan outs or is there a way of ticking so it can see co-pilot and Geminis as well on the query fan outs?

Jay: Yeah, there is. Should I show share my screen again?

James Dooley: Yeah. Yeah, go on. Yeah, share it. Yeah. So, what I know is I just get the the data output from the team. I just didn't know where it was coming from.

Jay: Yeah. Perfect. Yeah. So the thing is u yeah since I told you uh only chat chip and copilot are actually giving you the fan outs. So what you can do is uh here I have added ch zoho uh since I told you that we track the fan outs from different locations. So this is a Zoho project for Germany and this is a Zoho project for the US. So here you'll open the project you can go on to the query fanouts and then we can just select a model like let's let me just select co-pilot over here. So if I just select copilot you can see that okay you know every time for this prompt the average executions that means average times you know most of the times it just performs a 1.3 uh you know query fan outs for this prompt so you can see that affordable CRM for startups if we see the prompts uh if you see the query fan outs that we get in the copilot is this one like because we are doing it in the US so you'll see that okay it searches for affordable CRM startups USA and then you know a lot of different just little bit variations uh is found inside copilot. If I if I just uh searches for chat GPT you'll see that the answers are way different. It searches a way to long-term and the average execution is actually two. So you'll see that okay if I just just for that one we saw we found only five in copilot here we found 14. So you'll see that okay uh you know Chadri is going like length for the fan house like afford CRM for for startups software options affordable CRM so it goes like way too long and searches lot of stuff uh for you and you saw that okay in copilot they actually used the IP and they considered that okay this person is searching from USA so they did include USA as well if I s see for the same in Germany you'll see that uh you won't see the USA option. So here you'll see that okay there's no USA option being searched because the LLMs if done in the UI they actually catch your network uh as your location as well. So they search based on that as well.

James Dooley: So this personalization from the geo location as well just on there though as well. So on there it's saying the average amount of query fan outs being used is like 1.5 or 1.3. Some of them for the longer tail might be like two or 2.4 let's say for query find outs. But where are you getting the query count from then? Are you performing different searches yourself? Or once you get one of them, you perform that and see if there's any others that come from that. How come it says like 1.3 but then the query count has got let's say 16 or eight or 10.

Jay: Yeah. So basically it is the data of last seven days and the thing is uh you know every time we since we have built our own browser to do all this so we won't be performing any extra prompt based on the prompts that we have given. So whatever prompts you have added because if you are doing any business you must be knowing your prompts. So you have added your prompts we track your prompts on your prompts what are the query fan outs we give you the data of those prompts with and then we just divide it by you know like this prompt gave three uh fan outs. So obviously average execution three next time when we prompt after 24 hours if it gives you just two then we'll just make it 2.5. So it is just the average out you know we just doing the quick math over here. Sometimes it's giving three, sometimes it's giving one, sometimes it's giving one uh you know zero sometimes as well. So based on that we're just giving you know the average out position. Uh there is no specific data that we have that okay every time charge GP would be performing like just three fan outs for you. So there is no specific data for that. Sometimes it's doing two. So because it's very probabilistic these LLMs we don't know uh you know what what are their updates because in Google we know that okay every every year they are just pushing two two updates and these LLMs they are changing every day and you know we don't know how they act how they search so based on that we just captured the data that they are performing in the background via our browser and that's it that is what we are giving it to you

James Dooley: so on that query count so over the last seven days the query count could be 15 the average amount of actually fan out might be like let's say 2.4 but over the week there has been 15 different synthetic queries within the query fan out that's been done. So literally from one day to the next with exactly the same query it could perform different query fan out searches.

Jay: Well I didn't I didn't I didn't get the question. Can you repeat? So on that if if I went and searched for today um affordable CRM for startups and it did let's say two query fan out terms are you saying tomorrow when you go and run that search again for affordable CRM for startups it could bring maybe two or three again but they could be different query find out search queries that come back.

James Dooley: Yes. Yes. Yes. That is why we have mentioned this as well that okay seven queries were found but this one was find found twice. So we mentioned those as well. Yeah this one was found once this one was actually being repeated. So the ones that get repeated you can go after that. So that is what we suggest. Yeah, the if if like if your domain is way too new and you know if you're not uh if you haven't established any topical authority or any you know what do you say any any pages who are like it's it's fairly new websites then we suggest go for the longer ones create a topic around that and then you know in in hope that okay uh the LLM sites us next time.

Jay: Yeah, for sure. And then obviously from there then every one of the query fan out searches you can try to optimize load them in the rank tracker for AI visibility and check to see whether you're now starting being cited more for the longer tail easier to rank for query fan out terms that's coming back.

James Dooley: Yeah. And if you have got money then you can just go to the citation data you can see that okay which citations I mean which websites are being favored the most for these LLMs. Like if you just search for I've just selected all the LLM models. So let's just see that okay for Zoho you know if tech radar is being cited the most it is being favored the most by these LLMs. So if I have got the money I'll just outreach tech radar and target my query fan out keyword you know placement on that. So you know it it will just you know uh speed speed up my process uh of getting more visibility.

Jay: Yeah for sure. To anyone who's watching this, I'd highly recommend checking out Jay's AI SEO tips YouTube channel. He's doing daily videos on there comparing all the different AI visibility tools. He's got an amazing tool with Radar Kit AI that performing all these query findout terms and doing all these AI visibility checks. Jay, it's been an absolute pleasure and I hope you like the video and podcast series on query fan out terms with to do with chat GBT Gemini and also co-pilot.