SPEAKER_03

AI is better at putting the right products in front of the right customers. Are you seeing that Google searches are now being also influenced because more people are using the large language models? People are not using Google search less. They're just using AI models more. But Cole, obviously you've got tens of millions, if not hundreds of millions of dollars that you guys have tested and spent on SEO, but this is not just SEO with new tools, is it?

SPEAKER_01

No, it's it's really a new paradigm. Google itself is actually changing behind the scenes. Like for the last two decades, Search has averaged three words. Now with AI, people are loving this ability to navigate based on meaning. And that's the big difference. Queries are now 16 words long, and voice queries are now 29 words long.

SPEAKER_03

What about the companies that are on here that they're not selling on Amazon, they're not selling e-commerce? Does GEO matter to them?

SPEAKER_01

Yeah, totally. AI discovery isn't just a retail problem, right? But it's a buyer behavior problem. But with AI, if you are not early on in making your content easily and substantially understood by these large language models, you're probably gonna fall behind in the same way that other brands fell behind 30 years ago.

SPEAKER_02

Cole Kasperson is a leading voice in AI-powered marketing and chief data officer at Cranktank. He helps brands understand how AI is transforming search, e-commerce, and customer discovery, showing companies how to get found when buyers ask AI what to trust.

SPEAKER_03

Welcome to Using AI at Work. I'm your host, Chris Dagel. Each week we'll be learning how today's business owners, entrepreneurs, and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now, every business leader is asking the same question. What are we going to do about AI? If this is you, ChiefAIOfficer.com has the answer. We give you a simple path forward where we provide executive and team training so your people know exactly how to safely use generative AI in their day-to-day. We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also guide company-wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs, and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI. Welcome back to another episode of Using AI at Work. My name is Chris Daigle. I'm the host of uh Using AI at Work. And today our guest is Cole Kasperson. And Cole, uh, we're gonna be talking about how how they're doing some pretty sophisticated stuff with AI and marketing. Um, Cole's currently the chief data officer and a partner at a company called Cranktank, and they reached out to me saying, hey, I think we've got some stuff that would be of interest to your audience. I got on the phone with them, had a great conversation uh before we befor today, and they're in a really cool niche. They're certainly world-class marketers, uh primarily focused on e-commerce, um, digital commerce, those sorts of things. But for the outdoor sports um industry, uh mountain biking, skiing, things like that. So, regardless of what your industry is, though, today we're gonna be talking about how an expert level you know marketer that's dealing with well-known brands, how they're how they're like thinking about AI in the the you know, full stack marketing spectrum, how they are seeing the impact of it and what they what they would suggest your company does, what your your company doesn't do. Um, and just really give you uh professionals uh opinion on where you should be leveraging generative AI in your marketing. So, Cole, uh awesome to have you on the show. Thank you so much for taking some time out of your day to share this stuff with our audience and say hello. Awesome. Thanks for having me, Chris.

SPEAKER_01

Uh yeah, look forward to uh having a nice conversation here.

SPEAKER_03

Yeah, yeah. So uh let me ask you, Cole, what had you guys reach out to us about being on the podcast?

SPEAKER_01

Yeah, um, well, we really yeah, we liked the um, you know, I've liked some of your shows. Um, I liked your uh Bruce Clay episode, obviously as a marketer. Um Bruce Clay uh talks, uh you listen.

SPEAKER_04

Yeah.

SPEAKER_01

And um, yeah, and we've just had so many of our clients and so many, you know, auxiliary conversations, even conversations with other agencies about AI. And it just feels like, you know, in some form or fashion, everybody out there had an AI itch to scratch. And from the marketing perspective, um, what we'd really seen from our side of things is that AI is really changing online platforms in that for years the front door of the internet has been search engines. Now, what AI represents is basically multiple new front doors to the internet, and those new front doors work quite differently. Um, in some ways, they work the same. Um, you know, as Bruce talked about during uh uh thing, is that um, you know, SEO still matters. Um but with these new front doors and these new layers, there's a lot of really cool opportunity for brands. Um, again, whether you're e-commerce or you know, any kind of brand that's looking to market or get yourself known and noticed, uh, lots of different ways, lots of new exciting ways for them to actually engage on this new generative engine uh uh doorways.

SPEAKER_03

So, because I guess for the last 25 years, anybody who's wanted to kind of game the system, quote unquote, has been focused on Google and just in general search engine optimization. Now, what are you calling it? Answer engine optimization, generative engine optimization, what do you call it? AEO, GEO?

SPEAKER_01

Yeah, um, yeah, though it's been bouncing around quite a bit. Um it seems to be the the word, the terms that I'm hearing the most, um, I think the targeting the target uh CEO used it in their um earnings call is GEO. Seems to be like GEO is the one that um again with with this market specific. Um GEO tends to be the one that everybody's uh looking at it. But yeah, we've heard the terms AIO, um AEO, answer engine optimization, um SEO 2.0 um is a nice little cachet to it when I heard that said the first time. Uh but really, yeah, I mean it's um the the fun way that we describe it is um you know is just that like you know, no more paying, praying, and obeying to the Google bot. Um is uh is again, and that stuff's still important and Google is a very still important part, a still important front door. But yeah, now there's just layers above that front door. And um, and brands are working hard. And if you've worked hard in the past to, you know, find your keywords, stuff your keywords, you know, all these other games you've played in the past, if you're a brand that's been putting in that hard work, um, you're gonna like how easy and transparent these new layers can be when you approach it from the right angle.

SPEAKER_03

Okay, and for those of you listening, if you're not sure what we're talking about with AEO, A GEO, whatever, we're talking about how in the past, if somebody went to Google and searched for something, and ideally in your industry, your website or your advertisement would pop up. People are doing that in the large language models, in their Chat GBT account, in their Claude account, in their Gemini account. They're not necessarily just well, a lot of people still do treat it like uh a Google search term. They just go in and type in a search term and get a result. But just in general, as especially decision makers are using the models as part of their ideation and strategy process and they're digging in and they're finding resources. You want to pop up when they say, Oh, well, well, who's the who's the best at this, or who could help my company with this? If it's something that your company does, you want to show up. And that's a thing now. It's called generative engine optimization, and that's what we're talking about here. But Cole, you obviously you've got you know a lot of uh like tens of millions, if not hundreds of millions of dollars that you guys have tested and spent on SEO, but this is not just SEO with new tools, is it?

SPEAKER_01

No, no, um, it's it's really is a new uh it's it's really a new paradigm, is is that and Google itself, what's really interesting is is that Google itself is actually changing behind the scenes. Um for anybody else in your audience out there who understands how search works, um, whether it's the co-occurrence modeling um or the string matching, is is that for years, the uh search, I mean like for the last two decades, search has averaged three words. You know, somebody types in men's running shoes, right? And then you start clicking blue links to do your research. Uh now with AI, people are loving this ability to navigate based on meaning. Um and and now and that's the big difference is that before you were navigating based on words, now you're navigating based on meaning. So if I type in women's mountain bike shorts or feminine biking bottoms, those in the past were different keywords. Um, you know, and maybe your Google PMAX campaign might match up a little bit there. But those represent the same idea. And so now we're navigating, we we call it concepts over keywords. Um and customers love, I mean, and this has made a huge change in consumer behavior. Um queries are now 16 words long. Um, and voice queries, which are even more uh uh growing in popularity, are now 29 words long. And they're so important in what's going on is that just I think like seven, eight days ago, um, so mid you know, mid-May here, um uh Amazon rolled Rufus into Alexa um just because that voice search is so important. And so they wanted the power and the semantic matching of Rufus uh within the Alexa um uh Aegis. So yeah, so that's the really thing is this the whole idea now is that you can navigate based on meaning. And that's fantastic because you know, in the past it you know, it could be kind of annoying. Like, we'll stick with that men's running shoe example, is is that like you type in men's running shoe and then you're starting to do your research, you know, and you're like, oh wait, but I want a zero drop shoe. And well, I'm running, you know, I only run for like five miles at a time, and I like to run in wet weather, and I, you know, instead, now you can navigate based on meaning, say, hey, I'm I'm a 40-year-old guy who's training for a marathon. I, you know, I'm in the Seattle area, and I prize comfort over speed. And okay, boom, this is the exact um, these are the exact three products for you then. Which which color would you like these three products in? And yeah, and brands that can, and and as your goal as a brand, or you know, whether you're a manufacturer, right, and you're trying to manage a customer relationship, to specifically and naturally uh put content that answer these questions, uh, you know, and cue up the data so the AI can can get their hands on this information to say, you know, so if you've designed, if you're a shoe brand and you have multiple running shoes, like, you know, make sure that you're talking directly about who and what this shoe was designed for. Um that's what we've seen in our own research, actually, is that you've probably heard many times that AI-driven recommendations convert at a higher rate. And the single biggest uh uh factor in that that I can find is that AI is better at putting the right products in front of the right customers. Um the it's almost it's the way that I describe it to some of the SEO professionals is like it's like having the best negative keyword uh you've ever seen because you can keep away unqualified customers. Um in the past, right, Google search would just say, Oh, well, let me put our most popular shoe in front of you, right? Because that's has the most indexing. Yeah. Um now AI is smart enough to say, like, well, you don't want the Air Jordans, you want you know, this one that's you know designed for an older foot or whatever it might be. Yeah.

SPEAKER_03

I got a couple questions. You mentioned a few things. You mentioned that that now search, and I'm assuming like I get it, Google, men's running shoes, everybody had just had a short, quick query. Now it's context they're putting in the window, and that's what as a trainer, that's what we encourage people more context, right? Um are you seeing that Google searches are now being also influenced because more people are using the large language models, and now the average Google search is no longer three characters, it's now context search?

SPEAKER_01

Yeah, I mean yeah, a couple of really interesting data points about the Google search is that what we've seen is is, and this is larger industry stuff, is is that people are not using Google search less, they're just using AI models more. And so they're doing a lot of their research up on the so oh I found the perfect running shoes. It's gonna be ASICs versus Brooks here, right? Now I'm gonna go to Google, I'm just gonna go, I'm gonna search both of those specific shoes, and then I'm gonna jump on the website and you know I'm much further down the funnel now. And the other way, the other really interesting thing is that um, you know, over the last couple over the last few years, Google's been rebuilding that their foundation of search. And so their new system doesn't even look at words anymore, it actually looks at meaning as well. And so when someone searches something like that, um, it understands, it understands the idea of the question. Um in fact, yeah, a lot of AI overviews, what like six out of seven times the AI overviews isn't even answering the question you typed in. It's just answering the the uh the idea that you typed in. And so, and one of the things that we've really seen uh for our brands is that by optimizing their content for these further AI levels of retrieval, um Google's doing the same thing behind the scenes. I mean, Google search cannot work for long queries. Um, it just does not work for these really long-tail queries. And so Google is using what's called by-encoding modeling behind the scenes to help them with search. And and what we've seen is that we as we solve some of the by-encoding problems for small challenger brands for this AI retrieval, it's having a recursive effect and vaulting them ahead of some of the you know titans that they've been behind, you know. Yeah, yeah. We've been in third place for years. As long as we're in the world. Because we're not the biggest ones, yeah. And Adidas, we're fine. But now challenger brands can vault ahead because Google is using these same concepts to keep search accurate. Um, you know, and good for Google, right? I mean, yeah, it's like they've they want to they want to stay in the game for as long as they can. And so and they want to give better search results.

SPEAKER_03

I know that um uh at least during the Super Bowl, there was some uh dust up between Claude and OpenAI related to ChatGPT is now gonna be charge or be advertising, and they were kind of presenting that as a negative characteristic of OpenAI. Um when does that start? And what is your thought on how that's gonna impact like a user experience for sure, but also maybe bias in the the output that I get from my my my input.

SPEAKER_01

Well, I mean, Ian to uh from Chat GPT's perspective, um they have said very clearly, um, you know, and whether you believe them or not, but so and what we've seen is that um, yeah, that the advertisements do not have any any um effect on the results. Um that is that has had no effect on the results. Um and the reason that I think that that that won't happen is that if is that what I've seen on as a our agency handles Amazon, and Amazon has been ahead of the rest of the world by a couple years on AI-based retrieval. And that's simply because Amazon only deals in nouns, right? The only reason you're on Amazon is you're searching a product. Yeah. And so Amazon within this contained sphere has been able to really build a bunch of uh a nice infrastructure of machine learning based retrieval. Uh that now we're seeing, you know, that looks and smells a lot like what now we're seeing with AI retrieval on the open web. And um what Amazon has is that Amazon has a point where it can say, hey, you know, Amazon can make money two different ways, right? There's Amazon ads, and then there's the referral fee on selling the product. And so Amazon has had a always had a choice to say, well, you know what? We can show the product that has the highest bid, or we can show the product that's going to get a sell. And Amazon, you know, again, whether you like them or not, to their credit, they said the value proposition for us is to get the right product in front of the right consumer and not try to optimize for revenue. And given the highly competitive landscape out there uh among all these LLM models, um, I think, you know, for at least the near future and probably the medium-term future, is that their value proposition is going to be in giving the most accurate answers possible, especially when it's like the first time that I sniff that Gemini is trying to push me, yeah, you know, Proctor and Gamble's paying Gemini to tell me something I don't want, I'm just jumping over to Claude, right? So yeah. So that would be my thing, is based on what I've seen in the marketplace. I don't think that um I don't think that's gonna have an effect yet. Um but um historically speaking, based on trends, you're gonna see it in foods before you see it anywhere else. So as soon as you start getting recommended breakfast cereals that don't apply to you, that maybe maybe that's that's gonna put your uh um radar up.

SPEAKER_03

So let's talk about this. So for the the listeners who maybe they've they've had a budget for uh search for search engine optimization as well as like Google ads and ads on other platforms. Um do you have any uh I don't is the ad platform for Chat GPT like can I go buy ads today, or is it still in beta and small group or what?

SPEAKER_01

Yeah, it's still in beta. Um, you know, personally, our agency has uh has applied for the beta. Um and uh and we've talked to a couple other large uh some of our larger clients have already applied for the beta as well. Um and again, it's going to be for just certain levels of accounts. So if you're if you're paid or you have like a professional access like I do, um you're not gonna see the ads. It's more, you know, you're using the free version. So it's kind of like same thing on, you know, like on Netflix, right? Or Amazon Prime. Sure. Some some a big, you know, the super users don't even actually see the ads. Yes. Yeah, or YouTube or whatever, right?

SPEAKER_03

Yeah.

SPEAKER_01

Yeah, exactly.

SPEAKER_03

Okay. So obviously you guys are going to be experimenting with Chat GPT ads. Do you do you have you heard anything that would tell you that all of your years of SEO expertise may not necessarily be applicable in a a paid search environment in GEO or uh LLM?

SPEAKER_01

No, I haven't heard anything like that. It's more just being um like again, SEO is is still a major, you know, base layer of what's going on. And then just kind of seeing behind the scenes on the questions that they're having um and how they want you to syndicate your information. Um I would say what the if you're an SEO person, um, I would be high, you know, or if you're a brand, right, and you're saying, like, how's my SEO experience? I would say um the the big thing that's going to be driving these things, and I think the term is gonna be platform AI, is that the all of these, if I'm Chat GPT, um, you know, and I and I not only am I doing ads, but I'm hopefully doing clickless shopping, right, at some point down the way. Okay. Um I want this stuff all laid out on a nice platter for me. Um and so and a brand as a user or as the company. As the company. And so in the same way that as a brand, like, you know, you're going to be, you know, you get a big benefit by having your product catalog or your services catalog match up with Google Merchant Center and you're laying your products out there exactly how it wants. Yeah, it's gonna be these same, these exact schematics and architecture. Like, you know, that is going to matter um more than it ever has, you know, because it's going to be syndicating your data outwards. Um so architecture for syndication.

SPEAKER_03

Okay. Another question I've got. I I know that at least early on when when paid advertising started being offered on Facebook and Google and stuff like that, it's kind of Wild West. Clicks were super cheap, and the people who nailed it early, like cleaned up. Do you expect that there's going to be some lessons learned from that that are applied to the the the paid environment in Chat GPT that will like you won't really have that opportunity as an early advertiser to kind of not game the system but take advantage of inefficiencies in their pricing in your favor? Or do you think that it's gonna be a little Wild West?

SPEAKER_01

No, I think that it's gonna be a bit of a I think there's going to be a little bit of a Wild West. And the way that it's gonna manifest itself is kind of the same thing that you saw a few decades ago is because what happened early on is the people that, you know, again, if you know, we go back in the way back machine, right? And it's 30 years ago, people are asking the same question like, well, does SEO really matter? You know, does and the people who adopted SEO early had a nice, durable advantage over the other people that didn't. And the the quote unquote good news, if you were behind, was is that at least with Google Ads, you could start to buy your way out of the hole. Um, but with AI, if you are not early on in making your debt your pro you know, making your content easily and uh substantially understood by these large language models, um, you're probably gonna fall behind in the same way that um you know that other brands fell behind 30 years ago. And and you're gonna have a harder time buying your way out of this when you know consumers are gonna have a nice competitive environment where they're like, I don't want Gemini, you know, I don't want Gemini telling me what Proctor and Gamble or whatever other large corporation is advertising. I want true and legitimate answers. So I don't know if you can buy your way out of being behind on this one. Um and that's why we've um you know that's why we've designed our uh our REACH product, which is retrieval evaluation and agentic commerce health, where we can actually measure those layers of AI. Because this is a there's a is a much more transparent environment if you can understand how the large language models work. Because underneath the hood, um, you know, because Google, right, with Google's monopoly, Google.

SPEAKER_03

Before we go down that rabbit hole, Colt, let me ask you who, which listeners need to know this? Do you think that even at the CEO? Level that they should understand what Reach is doing, even if they're like, I got a marketer, we don't, we don't, I don't deal with that.

SPEAKER_01

Yes, I think so too, because the it at the end of the day, what this is is this is your how your company is having a conversation with these large language models about what it what problem you're solving and why the problem you're solving is meant is best for this customer. And so it starts, you know, with some of the smartest CEOs we've talked to. We talked to the CEO of a 10-figure brand, and he was like, sweet, he's like, talk to my yeah, he's like, my marketing guy is gonna call you. But first, do you mind having a meeting? Uh, you know, can we just show the the uh my product development team this really quick because I want them thinking about um and it and it kind of makes sense, right? Is we've kind of grown up in this you know world of SEO, and it's like at the end of the day, the product development team that is designing your product or your service to solve the problem, they're the ones who should be talking about it. Yeah, it's just the marketers who are taking it downstream. And so um, so yeah, so the SEO is the you know, he's the unifying force between product development and the marketers. So, yeah, absolutely. Um yeah, we and some of the best questions, oh yeah, some of the best questions I've had about this have come from CEOs who kind of understand that it's like um the whole thing, like between product development, product launches, and then the the tip of the spear marketing. So for the listeners, like here's my takeaway from that.

SPEAKER_03

Everybody in your organization, maybe they don't need to be AI pros, but they need to understand how this stuff is working. Specifically, how does what I do in and as a cog in this machine impact our business through the lens of that SEO? It doesn't have to be their primary consideration, but if your people aren't aware of this, they're not able to make that that judgment call and go, oh, maybe I'll do it this way because it's better. So I think that's a great tip, Cole. Um so reach, tell me more about this. So what are you guys looking for with this reach protocol that you're talking about?

SPEAKER_01

Yeah, so what we do is actually is that when AI, so when somebody goes out and asks AI a question, right? Yeah, it's just important to understand that the AI has a lot of data at the inference layer, which is basically within its training model, right? So if I go to Chat GPT and I say, hey, tell me about Napoleon, right? It's just gonna be like, cool, it's it's already read every book on Napoleon, it's gonna give me a nice little rundown. If I say, what's the temperature in Palo Alto today? It doesn't have that information. So it has to go out and ask the internet what that is. And that's called retrieval. And so in case you've ever heard the term like rag systems, that's retrieval augmented generation. And so when you're asking an LLM a question and it's saying, like, you know, hey, what's the best bike I can buy today, right? Or what's the, you know, what's the best fishing reel for me to buy my nephew, whatever it might be. Um, it's doing retrieval. It's you know, it's it's sending out a request across the internet and saying, all right, this we need this information. And the way that it gathers that information and rates the information and then sorts the information as part of that generative answer is is understood mathematics, um, basically. It's an understood process and it's very transparent, and everybody kind of does it the same behind the scenes. This is basically it's the uh it's the deterministic part of the modeling, right? And and so basically, if you're right, if you're a if you're designing an LLM, Chris, right, is that what you want to do is you want to say, hey, I want to make everything as repeatable as possible. Yeah. And then when it comes to the final what we're putting on the screen, that's going to be a little bit stochastic, right? There's a little bit of flavor to that, but I want everything ahead of that to be as deterministic as possible. And so what we're able to do with our REACH program is we actually um we follow that deterministic pipeline. And so where everybody else out there is saying, we've, you know, we've had this Google, you know, we're we're used to this Google world where we're just measuring symptoms, right? It's like, how many times am I getting cited in AI? How you know, how many times am I getting cited for these questions? Um what we can do with Reach is we actually say, this is why you're getting cited, or this is why you're not getting cited. Because if you go to a Chat GPT right now and you click on the sources, it's gonna show you the sources on the right-hand side. Um and then you're gonna see who's in the sources. What we're able to do is I'm saying, like, I know exactly what information you know was retrieved as from that source, how that's how that information was scored at every single layer of these AI retrievals, and how to change your content so that it scores higher at these deterministic labels layers to get you retrieved more. So if you're a um if you're a service provider and it's like how you guys do.

SPEAKER_03

Yeah. Like it it's not a monitoring, it's not a uh passive action, it's an active participation from you guys to make sure that my website is optimized for uh considered resource for the models.

SPEAKER_01

Yeah, no, I mean, yeah, because if you think about it this way, it's like any question you ask an LLM, Chris, um, is is there's basically 30 pages on the internet that are going to be used to answer that question um outside of the inference layer. Um and we're able to show you, well, these are the 30 pages, and this is the the order in which they are, and this is how they worked. And so if you're not one of those 30 pages for the question, but your competitor is, this is their content, and their content scored higher at some of these layers. Um and there's entire industries.

SPEAKER_03

Go go ahead. So it's not so much and I I say gaming, I don't want people to think that we're like doing anything gray market or anything, but but like like making an active effort to influence the outcome, let's say. When I say gaming, the so I'm not gaming the large language model, I'm gaming the retrieval activity.

SPEAKER_01

Correct. Yeah, yeah. We don't even the cool thing is like we don't even follow your brand. What we when we are engaging with the client is we say, what is the question, right? Yeah. It's like what this product that you have here, what is it meant to solve? And and tell us forthrightly what that problem is meant to solve. And then we build questions around the problem, and then we take that question and we send that question out, and we emulate um to exactly how they do it. And we use the same embedding models that these uh Chat GPT uses. We use the same retrieval, um, yeah, all sorts of different things um that we just match to what's going on there. It's not, I mean, I could actually do better retrieval than AI does, but all we do is we do exactly what they do, right? Because they have latency parameters, they have they got to get an answer quick. And so we follow the question, and at every kink in that retrieval pipeline, we can show you who's winning at that kink and why. And true. And so and we see it all the time where it's like your biggest competitor is showing up behind you in search and then ahead of you on the middle layers, and then you're coming back to the top on the final layers. So it's like, all right, those middle layers represent a by-encoding model. What they are, those are a single vectorization that the LLM is doing to measure um, so this is GEO. What we're doing right now, that this is GEO. Okay. Exactly. And so, yeah, it's basically generative engines. So it's like, yeah what goes on in the generative, and we're showing you exactly what happens in the generative. And then what we can do is we can actually test the content because it's like, no, yeah, keep your brand voice, don't just try to game it for the bots. But it's like like you can walk and chew gum at the same time. Like, yeah, let's talk about it here. And all of these LLMs they have what are called training data priors or biases. Um, yeah, there's actually certain features that matter a lot more um to the LLMs than other features. Like you may want to talk about you know how well your umbrella works with your ear pads, right? But LLMs don't have any training data to talk about how that matters. Here's what matters. Hey, so let me ask you, Cole.

SPEAKER_03

Like um, I'm following what you're putting down for sure, but your um mechanical understanding of what's happening with the the engines, did a lot of that come from that MIT class?

SPEAKER_01

Yeah, yeah. I mean, it was it actually came from Amazon as well, because um MIT and Amazon have a relationship going back um quite a ways on some of the early like A9 modeling and stuff like that. So yeah, I mean that's really um I mean Amazon uses a multi-node inference model, but yeah, I mean it's basically um uh like so let me just put it in is is it so yeah, Amazon's had these uh uh machine learning driven retrievals since like the early 2010s. Um then you know they had A9 and then the A10 used some mixed in off-platform signals and then Cosmo and Rufus. Um and so what you were learning if you were an aggressive Amazon seller, um and of course we have a significant Amazon portfolio as our company is that like the Amazon brands that were winning got there because they understood the retrieval architecture early, or at least they were playing along nicely with that retrieval architecture.

SPEAKER_04

Yeah.

SPEAKER_01

And so um it's just a matter of saying, like, well, this is what brands had to think about in Amazon, where it was a very straightforward competition. But that that competition is now emerging onto the open web as AI is is is coming there. So the brands that think about this, you know, that um that think about this, they're going to discover the traffic they thought was organic is actually retrieval mediated when you're taking these right these right steps. Um and that's one of the big things that we see is that if you're doing AI retrieval right and you want, you know, you come back and you're like, hey, Cole, what is six months of this, you know, meant for us, Mike? You're gonna see higher organic and you're gonna see higher brand search because we talked earlier about how people are doing all of this research and they come back and then they search for you know ASICs or Brooks, right? And as they're seeing a lot more brand searches.

SPEAKER_03

Random question. What a lot a lot of the clients that we work with as chief AI officer, our main company, where we we do the thing, like we go in and train and then deploy and all that, most of them are using Chat GPT. In the past few months, um, you know, I'm surprised, but new comp companies new to AI are choosing Claude. So that you know, that's some shift in the market for sure. But for the ones that we we mostly deal with ChatGPT, what is the search engine that ChatGPT is using for its retrieval?

SPEAKER_01

Um so what they do is well, it depends on the kind of retrieval that's going on. Is is that um Chat GPT, of course, had a long-standing relationship with Microsoft. Yeah, so um they do rent the Bing index from Microsoft. Um and no bueno, right? Like it's uh, you know what? They've actually done some pretty good indexing in terms of like just like raw, yeah. I mean, yeah, no, it's like it's not like it doesn't seem nearly like a volumetrics like Google Search does. But in terms of like what indexing does and how indexing cues up the data, um, I think Perplexity still uses the Bing index as well. Um really. Yeah. Um and then of course Gemini, um, you know, is in the Google family, um, is happily using that. Um Claude uses Brave search. Um and they, you know, the good thing about Brave search is that Brave tends to try to be um uh unaffected by you know advertising and stuff as well. So um but you know the behind the scenes is that like when you go into the big difference is like when you go into like research mode, um like you know, when you're Claude, right, or ChatGPT and you use research mode rather than search, that's a different, it's typically a different retrieval architecture. Because what they're doing is as we talked earlier about how what AI is doing is it's what we call the candidate generation list. It's like, bring me back the web pages that relate to this, and then we're gonna start to analyze their content. Um with deep research, it's like, hey, if there's a page, um, like you know, if if your collection page, right, or your your main services page on your websites, you know, gets you in the door, the deep research actually crawls your whole site and pulls data from you know the rest of your um schema markup um or you know, the rest of uh you know your associated web pages. So um, yeah. And and the other thing too, though, is that what really surprises a lot of people is that when we talk about how retrieval on you know, this retrieval of and this new AI landscape affects them, is that everybody like already knows about the conversational chatbots. And yeah, and you should totally do that. Uh and it's the fun part of AI. But there are AI shopping agents out there with various layers of handoffs and chaining that go all the way to checking out for the consumer. And there's autonomous AI browsers that'll surf the web on someone's behalf the way a person would. And then these vertical special AI tools that are embedded inside other apps and platforms. Um Home Depot, right? Um, you know, good when you're at Home Depot this weekend, they've got a thing called Magic Apron that's an AI vertical inside of there helping to describe these things. If you're using Kayak or Expedia, um any of these other things, there's so much retrieval. I I saw a stat, um, I couldn't source it, but I remembered it. It was like 60% of the time that you're being part of a retrieval as a consumer. Um, 60% of the time that the answer is part of a retrieval request, you don't even know it. Um it's you're just engaging all the levels because it's if you think about it, if you're a service provider, right? Or if you're somebody who's trying to give a consumer an answer, this AI mediation is so useful that you're using it, you know, not to try to pull the wool over everybody's eyes. It's just here, I want to give you the right thing. So um, so yeah, so it's not just about Chat GPT. If you just think about all of these different ways that consumers can find their way to you, and all of these ways that AI exists before the consumer relationship, um, it's it's a I I mean, I think we tried to count the touch points once, and um, it's over 300 different AI-mediated touch points at this point out there. Um, and they're inventing ones right now that we don't even know about. So um uh, you know, it's yeah, it's pretty cool. And that's why we've built REACH the way that we did as a deterministic modeling, is because if you had built like if you had optimized your site for Claude 4.6, right? Let's just say like, hey, my genius, you know, my genius marketing guy has figured out how to make us just for whatever reason be the best in 4.6. Um, when Cloud came out with 4.7, there was you know some significant adjustments that would have you know messed with a lot of people, you know. So you can't optimize to a single model and you can't optimize to a single version, but what you can optimize for is the and what is the majority of what's going on behind the scenes are is all this determinism that's occurring behind the scenes. And and it's all open source. It's not it's not a black box like you know, like PageRank is with Google or Hummingbird.

SPEAKER_03

So yeah. You know, so if if you're listening to this, right, you're you're thinking, oh, I just go to Chat GPT, I've like a drive-thru window. I ask for something, it gives it to me, I leave. But the reality is there is so much more happening behind the scenes. Like, like I would consider myself an expert level user of generative AI and in business operations, right? But I don't necessarily like I can drive a car fast, but I don't know anything about the engine. And that's kind of how I am with generative AI. And I don't say I don't know anything about the engine, but like my question about the MIT, like, did you learn some of this mechanical stuff, which was I find fascinating. But also all of these, like you know, I I just assumed it was on-site optimization, and when they went out and when ChatGPT went out and stole all the information from the internet one more time, that I would somehow like pop up to the top of the list just like an SEO. But what you've shared with me today is um like SEO is child's play compared to what we're doing with the the GEO effort. I mean, there's it's not just you're not playing in one field, you're playing on multiple levels in multiple fields because there still is some SEO uh prowess that would be expected from this. But there's also if I didn't understand the uh the retrieval and at each kink and and why it's like if I didn't understand that that was even happening, like there's no way that I can I can not again game the system, quote unquote. There's no way that I could have my site optimized so that it would be a result that showed up in the retrieval. This has been uh eye-opening for me for sure. Now, as a a business operator, do I am I going to use this? No. But going back to this reference with the CEO earlier about hey, the CEO wants us to explain this to their product team so that product can now think about it through a completely different lens that's probably gonna be more relevant in five years than search is, right? Um like that's the way any listener here who's like this is fascinating stuff, but I don't do SEO, I'm not gonna go and optimize for GEO. No, but you should understand it so that you walk into the room to have the discussions with the rest of your team more informed, right? Like just like huge, huge gain. Thank you for this.

SPEAKER_01

Yeah, no, I mean, and the interesting thing is let's talk about the takeaway for the CEOs is that, like, yes, your, you know, and particularly the ones in the service industries and stuff is like, yeah, your consumers are still relationship driven, like totally. Um, but the way that your consumers or new consumers are building that short list of people they're considering before the relationship starts has has completely changed. Like that's what has really changed. And so they're not asking their network as much as they used to, they're asking an AI, you know, and sometimes they may not even know it. Um, and so AI is now sitting upstream of that relationship, um, not replacing it. So the brands that figure out how to manage that visibility are the ones that are gonna get the call.

SPEAKER_03

Interesting. Now, I'd like to kind of shift gears a little bit. I'm always curious about what the AI journey has been like for your company, for Crank Tank. And I know that when we got on um for the listeners, what we always do, we we never bring anybody on cold. We we want to do a pre-interview and make sure that like we oh, okay, I get what you guys do. Oh, that's great. Oh, that's fascinating. So that we come to the podcast ready to record with a little bit of rapport and you know, like some clarity on what we're gonna talk about. Scott, one of the co-founders, was also on that original call, but he said you were the really the the one that led the push inside crank tank. Yeah. What what were they doing? Like, what was there prior to your pushing? What was the discussion about AI like in in the business? Because you guys have, I mean, like you're not a new company. You guys have been successful for a long time. You got uh a great catalog of like trophy clients and all that sort of thing. So what what was that? When was that? And what was the catalyst for Scott to say, hey, who's gonna lead AI internally?

SPEAKER_01

Yeah, no, I mean, because obviously AI has been out there in multiple forms, and in our case, you know, so many of our clients are using uh Google PMAX campaigns, right? So Google, Google, of course, is using AI as part of how it syndicates those performance max campaigns. Google has their advantage, or I'm sorry, Emeta has their advantage plus. Um, your retention marketing, if you're using a brand like Clavio, right? They've got AI inside of it. So we were seeing AI emerge as this big part of how a responsible agency would say, like, you know, at the end of the month, it's like, did we deliver value for our customers? Did we make sure their Google ads ran as well as possible? It was like this pressure for AI started to build and to build. And we'd really seen a lot of growth with our Amazon clients. Um, like our Amazon clients were succeeding beyond everybody else. And that was really the big signal that said, like, I'm like, well, I obviously, you know, Rufus, right, is like I have a copy of Rufus' patent documents in my office, actually. It's like, we know exactly how Rufus thinks and how, and so we're optimizing for, you know, we have a running joke where it's like, if Rufus wants to know if this product is bigger than a cantaloupe, like, I don't care, you know, if it's a $5,000 product, I'm gonna tell Rufus exactly what Rufus wants to hear. And so we started to triangulate these things and say, like, okay, well, these Amazon, the way Amazon's working and the way that Amazon has grown to 41% of the US you know e-commerce market um is you know, is something that works. And this is now moving to the open web. So how do we how do we help take the same success we've seen on Amazon and ensure that our webs, you know, that our web clients are seeing the same success and that we're that we can know that we're doing is the best possible job for them on our Google PMAX, Meta Advantage Plus, you know, all of these different AI touch points that are now that drive their classic uh programs. And so between all those things, it's like, well, you know what we can actually do is we can actually see inside the beast. And um, and that's been the one thing is I mean, they a lot of you know, a lot of people, I mean, Google's been really good in a lot of things. Um, but I think a lot of CEOs are a bit frustrated after years of saying, like, well, we keep changing our site, or they keep saying to spend more. And it's like, you know what? With this generative engine stuff, you can, you know, one of the things we've seen, right? AI overviews are good in a lot of ways, but it's really driven down organic clicks, right? Is this that as AI had been growing and growing, it was taking making organic smaller and smaller. But once, but now AI is available for brands to grab from themselves to put organic um as a bigger part of their of their platform. So um, yeah, and organic is it's not free, right? But it it doesn't show up on your PL. So um yeah, which which you know was good. So that was really the it was just I I think the same reason that so many other people are asking AI questions is it's just coming from every single direction. Um yeah, no doubt.

SPEAKER_03

And like especially now. So I'm for the listener, I want to clarify we we the way that I explain quote unquote AI to non technical business professionals, and I is I tell them there's kind of two paths. There's analytical AI, which is more like machine learning and data science. And that's what we're talking about here. For most of you, uh, you know, if you're not familiar with that side of it, the other side of it is what we call a policy. Applied or operational AI. How do I use generative AI and the operations of my business? And that's what most of you are probably where you're at. I'm sure some of you are maybe you've done the MIT uh, you know, AI program and that sort of thing. Maybe you've done some stuff like that. But so if you were a little confused about, well, how is he using Chat GPT for that? It's what he's talking about is more like the machine learning, the the sophisticated stuff that's not for the layman like like me and uh some of our other listeners.

SPEAKER_01

So um the good news, Chris, is that um oh one of the one of the really good things is that yeah, like this the stuff that you you know the chief AI officer is really good at doing, helping to basically take your existing infrastructure, right, and then start to harness that with the power of agents to run your agency better. Yeah. Is if you just imagine it's like if you take your website and your services offering or the way that you're describing how your warehouse works, right, and you're cleaning that all up and you're doing that optimized for the open web technical, you know, that we talk about. If that's you know, if if it's if it's semantically optimized for that end of things, that same semantic optimization is going to be fantastic for all of the stuff that that chief AI officer does, right? Is that your the the way that your product speaks into the rest of what's going on here? The same way that you yeah that you syndicate inventory signals, um, your chat bot, right? If you know chief AI officer is like, hey, let's help you build a better chat bot, that chatbot is going to run smoother when your products are designed from the bottom up with this semantic matching in mind. So all those downstream effects work better. So it is definitely layered.

SPEAKER_03

Yeah. So at this point, I would uh based on the conversation, you guys are offering GEO services for your clients.

SPEAKER_01

Correct. Yes. Um yeah, and and yeah, part of it is that yeah, we get um we have different packages where you can um do as many queries as you would, you know, as many queries as you as you want to pay for. Um we do not sell it as SaaS. Um, it is not just a dashboard where you're like, okay, God help you. Um everybody per every member of my reach team is certified in at least one major online platform. So they understand when we say, hey, let's change your content in this manner, or let's address the semantic depth with this. They understand um the trade-offs of saying, like, okay, if we're gonna put an FAQ on your page, we're gonna do a product comparison on each and every one of your collection pages, we understand what that means from a depth perspective and how to do that and make it look good for humans.

SPEAKER_03

So what about the companies that are on here that they're not selling on Amazon, they're not selling e-commerce, quote unquote. Does GEO matter to them?

SPEAKER_01

Yeah, totally. I mean, it matters in a couple different ways. Is is that on the one hand, we talked about those custom those the uh um the relationship management, right? I mean, yeah, AI discovery isn't just a retail problem, right? Um, it becomes really easy to solve retail problems, but it's a buyer behavior problem. Um, AI retrieval is. Is is that, and buyers in every category, you know, whether you're buying an e-bike or you're just buying, you know, steel, you know, steel ingots or a 3PL contract, um, a managed services agreement, that they're all converging on the same behavior, right? Um and so, and so, and they're asking AI before they ask the vendors. And so it's just basically those kind of customers, you're you're probably going to tend, you know, to exist a little bit further up the funnel. But um, you know, again, that's that's all moved uphill, upstream of the relationship. So again, whatever service you're offering, right? If you're putting that service out on the internet and you want attention, this is how you can maximize uh the attention that you're getting under this new protocol where people are wanting to navigate based on meaning rather than just off of a three-word sentence. Mm-hmm. Now fascinating stuff. And then the other one too is that um is uh uh you know, the marketing teams, like if you're if you're a CEO, right? Whatever you're doing is that your marketing, a lot of your brand story gets told by other people, right? Is is that retailers or journalists, customers on forums are doing that, are are also giving signals about your brand story. Um and so when a Chat GPT or Perplexity or AI answer question, um, those systems are literally saying what source is it pulled from. And so marketers forever, right, have been having that question of saying, like, who's actually telling my story right now? Yeah. And that's why we don't put any intent filters on Reach. What Reach does is again, we're just asking the question and we're exposing the entire pipeline so we can show exactly who is telling your story. So if you are a so if you are a logistics company CEO listening to this right now, and you're saying, how come we're not getting these kind of contracts, we're not getting these kind of calls, you know, following the question saying, like, hey, I have you know 25,000 packages a month and I'm looking for it to ship out of the mid, you know, Midwest. Um you know, we can we can show and say, like, these are the people that are telling the story. Because at the end of the day, there's 30, you know, again, this is very simplistic, but there's 30 pages on the internet that are contributing to the generative answer that has been put in front of your customers. Are you one of them? Are the ones that are on there talking about you? If so, what are they saying? If not, why? And then we come in and say, well, this is how you do it. And then you can imagine that this level of insight that we're able to have has a tremendously positive impact on how we can run your meta campaigns or your Google campaigns or your retention marketing. So, you know, so some brands come in and they're like, dude, this is awesome, this is great. You know, we just we want the whole package, but let's just focus on one query at a time. Let's focus on this product launch that we're doing and then take everything you're doing and and help make our Google ads better. And that's one thing that we really like to do is that we will scale it around the needs that you have. Yeah. Because, you know, navigating based on meaning isn't just easier for consumers, it's easier for an agency that is, you know, has the whole picture in mind. Sure. No, I love it.

SPEAKER_03

Now I've learned a lot today, Cole. So for the individuals who are interested in either following what you're up to, because again, we've had you know, we've had Bruce, we've had people like that on the show. Great episodes, but I think I've learned more about the the how today than I have on on the previous. So if other individuals that want to dive in with with either your approach or to find out more about what crank tank's up to, best places for them to go and either follow you as a thought leader or you know, uh see see like use cases.

SPEAKER_01

Yeah, come come visit reach.cranktank.net um and you can sign up for your own free query. Um so if you're a business owner out there, um a CEO or a marketer, um, come check out reach.cranktank.net, go down to the bottom of the page, um uh put out your information, tell us the question that you want at like what is the question we've we've been talking this whole episode, Chris, right? And I'm sure these you're the um the people who've been listening have been like, oh yeah, well, what is the single most important question that matters to this product or service that I'm thinking of now? Give us that question, we'll give you a free demo and show you, show you what it looks like. Um very cool. And some brands are pleasantly surprised, others are like horror stricken. Um so yeah, it'll be but no matter what's happened, you know, at any stage of the thing and any size of the company, the the one unifying thing is that people are like, wow, this was this was totally worth my time. Thanks for showing me what it looked like. Um, you know, and then from there, it's like we we talk about next steps, and um, yeah, it's just fun to and and the rewards. I mean, companies, the thing I would really like to stress is that companies that want to talk conversationally and authentically about their products, um, yeah, a those companies are fun to help. So yeah, so please um reach out. Yeah, and then two, is like those get rewarded by LLMs because LLMs have been trained on human knowledge, and so authenticity gets rewarded. So that same hard work that you're doing. Yeah, exactly. So that same hard work you were doing on SEO, now you get to kind of have more fun with it and talk authentically about your product.

SPEAKER_03

Um so and if I'm listening to this and I want to send somebody to go and just out of curiosity, like what are we showing up as in the search term? What role in my company should I say? Hey, take this link, go sign up for this and tell me tell me what you find out. Who is that role?

SPEAKER_01

Uh I would say uh if the the the ones that get the best out of that is is the um is the head of marketing because the head of marketing sees the whole picture. Um and you know, one one thing that we that gets pulled up a lot is is um you can imagine so many of the things that's like, you know, what's the you know, what's the best, um, you know, what's the best fertilizer for my lawn, right? Is is that like you're gonna get a whole bunch of home and garden articles, New York Times articles, like so you know, they're gonna they see those people see the whole picture like, oh my gosh, this is a great PR target list. Like this is the tool that helps me justify the PR budget that I wanted, in addition to me giving me the leverage to to um wrangle the dev team, right? Is like that's the that's the other thing, is that what Reach does, and as a tech guy, um, you know, I did build it from a tech perspective. Um, I'm more tech than marketer um at some point, at some times, um, is that like it's a wonderful unifying process if your marketing team and your tech team, you know, um are yeah, you know, it's just like the dev guys love it because they they they get tasked to do so many changes on the website and they don't know if it's gonna make a difference. All of a sudden they understand this stuff and they know they're making a difference. Um so yeah, if you're whoever's high enough on the marketing chain to be able to tell the dev guys what to do, that's that seems to be the magic um junction point. Awesome.

SPEAKER_03

Hey, so we'll actually have the link to um reach.cranktank.net. It'll be in the show notes. Pass this on to your marketing team. Um, but Cole, thanks again. I'm glad you guys reached out. This has been a fantastic episode. And um, for those listening, look, if you're getting something out of the podcast, help a brother out. Like let other people know that you're finding value in the conversations, you're learning things, um, and you're better understanding how to think about using AI at work, right? For your team, for your uh for you personally, and that sort of thing. We'd love it if you just uh help us get the word out, leave a review, uh, forward a link. So with that, everybody, we will um be back next week with uh actually we've got an amazing episode coming up for you next week, another one. Uh I'm looking forward to bringing that to you. But again, Cole, thank you so much. Cole from cranktank.net was our guest today. And um, everybody, we'll go out and use AI. Awesome. Thanks for having me, Chris. It was a great conversation. Thanks, Cole. Thanks for tuning in to Using AI at Work. Don't forget to subscribe for more conversations about how to use AI at work. And a special thank you to our sponsor, Chief AI Officer, for empowering businesses with AI education and training. Visit their website for a free AI readiness assessment and AI strategy guide to help you get started using AI at work. That's www.chiefaiofficer.com. Follow us on Twitter at the handle UsingAI at work and visit www.usingai at work.com for free resources to help you harness AI in your role.