← Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast
Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast
How AI search is reshaping visibility: from rankings to mentions
00:44:08
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- [00:00]
Podcast Host (Intro/Outro)
The Voices of Search Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast, I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iheareverything.com welcome to the Voices of Search Podcast. A member of the I Hear Everything Podcast network, ready to expedite your company's organic growth efforts. Sit back, relax and get ready for your daily dose of search engine optimization wisdom. Here's today's host of the Voices of Search podcast, Jordan Cooney.
- [00:43]
Jordan Cooney
AI search is fundamentally changing the rules of discovery, making traditional metrics obsolete the landscape of digital discovery is undergoing a radical AI driven transformation. The sophisticated AI models powering generative search are rewriting the rules, fundamentally rendering click centric metrics obsolete. Consider this 93% of intersections in AI mode result in zero clicks. This isn't just a slight shift, It's a complete transformation. 58% of Google's own searches are now zero click. Google's AI overviews are taking the place of traditional search journeys and increasingly answering the questions without traffic. In this landscape where rankings and traffic no longer tell the full story, how do you measure success? I'm Jordan Cooney and joining me to tackle these critical questions is Thomas Payham, CEO and co founder of Otterly AI. His platform helps SEO and marketing teams monitor brands visibility and content citations across AI platforms like ChatGPT, Perplexity and Gemini. Thomas will explain why traditional SEO metrics are failing, how to measure what truly matters when visibility decouples from traffic, and why a bootstrap approach is proving to be a smart strategy for building a category defining product in today's overhyped market. Thomas, welcome to the Voice of the Search podcast.
- [02:12]
Thomas Payham
Hi Jordan, thanks so much for the invite. I'm super excited to be here today.
- [02:16]
Jordan Cooney
Likewise. Likewise. This is such a busy, busy and noisy category right now. This whole tracking, monitoring, understanding what's happening in AI, visibility, awareness, even the workflows and the production flows are just like constantly being brought up in the news and there's new vendors coming out left and right. You know, you spent, you know, almost a decade in other SaaS and marketing teams before building Otterly. And I just want to, I want to understand like you know, how does that experience in the past exits help you as you're shaping this new company?
- [02:52]
Thomas Payham
Yeah, it's quite the crazy times I guess right now. But I mean, quite frankly, I mean we started Otto EI about a year and a half, two years Ago, Right. And to me it's fascinating how fast paced the whole AI search market has been in the last two years. But I mean to your point, right, looking back at the last decades in marketing, I've been in marketing since 16, 17 years and to be very honest, Jordan, I didn't really intend to start my own startup in the first place in that market category. Right. This was not really my intention in the first place. The whole point, I guess that led me start Otterly EI as an AI search monitoring solution in the first place was my last role at a company called StoryBlock. I led a 30 people marketing team there, spent lots of money on Google over the years. We are the company basically is a B2B SaaS product. Right? So Google still is and was a few years ago the main acquisition channel for us from an inbound motion, right. So I think it was sometime after the release of ChatGPT I started tinkering around with that thought, well, what is actually going on on ChatGPT on these new AI bots, right? And the long story short is I didn't find a solution two years ago, which ultimately made me build prototype some early versions of what would later turn into utterly AI. And I mean, fast forward to today. We've onboarded over 20,000 users to our platform as a fully remote, fully bootstrapped company. And as mentioned, right, I didn't intend to start Otto AI, but after some early traction I was like, well, the challenge is too big to not go after this, right? And then help other marketing teams and conquer and understand and optimize for what I guess is now known as the iSearch, right? So I guess you can say it kind of happened, my journey with Otterly kind of happened. But I'm also super excited that it happened and how far we've already come as an industry and as a space. But I mean the platforms are basically evolving daily, weekly, right? And obviously the market has been accelerating quite a bit as well in the assert space. I do understand every marketer who's like, well this is really hard for me to grasp at this point, right? But I think besides all the hype, right, And I'm sure we're going to touch on a few fundamentals. Sticking with the marketing fundamentals will always help you, right? And it will also help you navigate this AI search revolution at the end
- [05:35]
Jordan Cooney
of the now there's this huge gap, right? Like, I mean there's this massive gap between what marketers know, how we understand what's happening in ChatGPT perplexity Gemini and then the ability for these tools to provide like real, genuine insights. How do you see Otterly closing that gap? Why is it that you guys are doing something that, that is different or more helpful in the market? And why do you see your approach being unique in this, what is seemingly a unsatiable growth of LLM visibility trackers that pop up left and right.
- [06:18]
Thomas Payham
Yeah. I mean, all goes back, right, to our foundation. And the foundation is we want to deliver a best in class solution for marketing teams out there. Right. We are marketers ourselves. I worked in marketing for many, many years, so did my co founders. And when we set out and when we built Ottil AI, it was clear for us that at the end of the day we want to provide the best solution that would help us get the job done as marketers. So what is the job that we need to get done as brands and as marketers in this space? It is about optimizing our brands to be better found on ChatGPT and the other search engines. Right. How do we do that? We need to go through a couple of steps. One, we need to research and ideate on the topics we want to track and optimize for in the first place. This is already a big limitation and challenge for many marketing teams out there that historically we've been all tracking Google keywords. We might have content plans and topic clusters, but since consumers use those platforms fundamentally different, we rather now think about prompts. Right. And how we show up for those different prompts. So understanding and ideating what those prompts actually should be in the first place is something we help as a product, as a tool. Right. I think we were one of the first ones who introduced an AI prompt research tool. And we constantly make it better. Right. To hold the hands of our marketers and give them a tool where they can ideate, find and categorize and organize the respective search prompts they want to track in the first place in the different markets, in the different product categories, in the different languages and whatnot. So that's really step one of the user journey. Step two. It's about analytics, right? Yes. There are many visibility trackers out there. All of them have some sort of maybe API based approach or front end approach. But I think at the end of the day, what's super important is data quality. Right. And we've invested a lot of time, money and energy in optimizing the data accuracy and quality. I keep saying we want to be the best in class, providing you with the most objective and most neutral insights on how you perform, for example, on ChatGPT. Right. Because at the end of the day, only if you can trust the data as a marketing team, you can then start optimizing. Right. So on the analytics side of things, I think we've done a great tech job at that. And at the end of the day, we want to make it easy for marketing teams to understand how do I show up right now as a brand on ChatGPT, on Google search and so on and so forth, and how do I benchmark against my competitors there? Right. Against their product lines and whatnot. But at the same time, I mean, we all want to understand where ChatGPT and others are pulling in the sources from. So analyzing the citations, diving deeper on the website sources and whatnot, and providing easy ways where you can already see how you also perform as a website compared to your competitor. Websites is kind of the second key area we've been super, super laser focused on.
- [09:27]
Jordan Cooney
I want to highlight one of the things here that you mentioned, and I'm kind of curious, just very briefly, give us a little bit of indication as to why it's so important for us to have a clear category for the technology that's being built here, and that this category is distinct from the traditional SEO tools that have existed for many years, maybe Semrush, Ahrefs and others. But give me your perspective on why this is a distinct category and how this distinct category is different from the traditional SEO tools.
- [09:59]
Thomas Payham
Yeah, I mean, it is a distinct category in my mind, because it's a distinct channel. Right. Those AI search engines fundamentally work differently for us as consumers. And also the optimization techniques are, I mean, are SEO influenced, but it's not only about SEO. So it is a dedicated category because we're looking at those dedicated channels as new emerging channels. I'd like to keep comparing it to social media. Right. Many, many years ago, social media emerged as a dedicated category and we would see social media monitoring, analytics, optimization tools emerging there as well. And it's the same thing with AI search. Right. AI search as a whole is a new category, and each platform in itself, ChatGPT, Cloud, Gemin, they all have different mechanics that will also make us optimize on a channel by channel basis. So that's one, I think the second factor to your SEO tool comparison, I think SEO tools per se obviously have historically been pretty much focused towards organic performance on Google. And historically those SEO tools most often, quite frankly, have lived in the silo. Right. I personally worked in many marketing teams where we would rely on many of those great SEO tools out there, but, but most often the data was not directly connected to our business critical martech infrastructure, let's say. Right. And I'm personally hoping that we don't go into the same, I'm not sure if it's a mistake, but into the same direction that AI search tools will live in their own silo. Because at the end of the day, I believe it requires an overall go to market play, meaning we also need to connect the systems. And this is also one of the reasons why we as a vendor, as a tool vendor, are actively working on technology partnerships and integrations. Because I truly believe we as marketers can do a better job if all of our systems are better connected with each other. Right. So I think at the end of the day, yes, it is a market category dedicated because of those dedicated channels. But I'm hoping that we would also build out integrations and connectivity towards SEO tools, towards content platforms, CRM platforms and whatnot, to basically give our marketers more and more context there. Right, Absolutely.
- [12:23]
Jordan Cooney
And I mean, one of the really defining moments in this category that's being built. Right. Because this category is just in its infancy. We're like in the first couple of years of AI knowledge, let's just call it, and AI insights in how these platforms are going to help inform marketers to do their jobs. But you know, Otterly grew super fast. You guys reached over 17,000 users. And I think one of the more notable pieces is that Gartner recognized you all as a leader, an industry leader and an innovator in this new forming category. What made that possible? How did you guys get to that level of both recognition but also distinction in the market to capture that many new users?
- [13:11]
Thomas Payham
Yeah. Again, product focus. We're product geeks, Right. And we're product geeks who are our biggest critics ourselves. Right. So I think day in and day out, we try to make the products better. We try to make the products better for our marketing users and audiences. And as practitioners of our own, of our own product, we use it daily, we use it regularly. And we also are obsessed with all the different use cases on how our customers have been using it since right the beginning. And I think that customer use case obsession helped us grow so quickly with our setup. And I mean, the recognitions I think speak for themselves. Right. If people are enjoying and getting value from the system, they will recommend the system to other colleagues, to other people in their network. And I guess that's how we ultimately also caught the intention from Gartner. And others. Right. And yeah, I guess in that sense there's no secret sauce on how we earned that recognition in itself rather than being obsessed over the product and making the product better. Really?
- [14:23]
Jordan Cooney
Absolutely. And you mentioned some of those product features earlier as you were sharing some of the insights as to where we're going. I'm curious, Thomas, how you see this evolving because the landscape seems to be shifting super fast. And you brought up one of these, which is how other brands or communities are mentioning sites and then how that creates this credible set of data that LLMs use to cite or source specific brands in responses. And so that's become one of the key defining data sets that brands are looking for, which is like where, where is my brand being mentioned? How is that produced through our PR strategies or social community strategies? And in summary, I'm curious, what are some of the defining product features that you foresee in this category and why are those going to be so important for marketers?
- [15:19]
Thomas Payham
Yeah, I mean product defining features and in that category, obviously the first one is, is end to end tracking. Right. And what do I mean by that? Right now we're still in an infancy where most marketing teams do not track end to end performance. Meaning how do I Show up on ChatGPT as a brand to all the way towards someone making a purchase decision on my platform, on my website. Right. So I think the end to end tracking is super hard still today, but it's something that's solvable and will be solved by, by vendors in that space. So we need a system that tracks end to end. How do I show up as a brand ultimately? How do bots engage on my websites, how do agents engage on my website, engage with my content? I think that's a whole new analytics layer that we as a community, we as an industry haven't really unlocked. I can tell you from our own example that as of today, we see, when I look back at the last 14 days, we see about 15% of our total traffic already being coming from agents, AI agents. Right. Be it agents acting on behalf of my user or chatgpt search bot. Right. Doing its own research and building up their own index. So I think we need to unlock that as an industry as well. Right. And then last but not least, how do we tie that back to our CRM data? How do we tie that back to our revenue data? Right. And I think that's, that's a big challenge, but it's something we're going to see emerging in the next 12 months, I believe, from an end to End tracking perspective. So that's one. Obviously the second factor is optimization. Right. So what do we need to do? What, what are the actions, what are the tactics, what are the playbooks we can do, be it on page tech or off page, in order to improve, in order to have more brand mentions, better brand mentions, but on ChatGPT and ultimately drive more business impact. So I think that's the second big pillar that's going to be quite industry defining and it's going to be quite interesting.
- [17:28]
Jordan Cooney
I love it. One of my follow up questions on this is as you think about where marketers are going and how you've built this business, you've done this purely as a bootstrapped organization.
- [17:44]
Thomas Payham
Right.
- [17:44]
Jordan Cooney
And so there's a lot of other players. I'm not, I'm not, I'm not trying to, you know, you know, discredit any of these other players, but there's a lot of other players that are, that are tracking and trying to inform marketers around AI visibility and many of them are doing it with very, very deep pockets, many of them are doing it with, you know, heavy investment and they're splintering that product focus. And that's why I'm asking this question off of the understanding of how you're looking at the future of product and the evolution of AI tracking software. Because that product vision I think largely dictates the ability for any organization to be successful. And what we see with a lot of these other AI tracking platforms is they splinter from monitoring, tracking performance to work, work management, work product and then, and then even beyond that now there's even some platforms that are trying to now get into the whole reporting layer and tracking layer. So there's even now deeper use cases as heavy, heavy investment gets poured into this category. You, Thomas, have built a company fully bootstrapped. It means that you have to have some level of focus and dedication as you likely don't have the same resources. But correct me if I'm wrong on that assumption, how are you doing this, how are you winning and what is the focus to win considering you're a bootstrapped organization?
- [19:13]
Thomas Payham
Yeah, I think focus is already the trigger word. Right. So yes, we don't have those deep pockets compared to some VC backed startups. For sure it's a bad focus. Right. And asking ourselves Daily Weekly, where's the biggest pressure on our customer side on our marketing teams we work with that we can help them with. Right. And I'm not a big believer in building out what I would call monolithic marketing suits. Right. I think some of those VC backed companies are going down that road building out all of that. As you mentioned pointed out, I don't believe in that because I believe marketing teams already have a sheer amount of tools and platforms they use. I rather want to build an ecosystem, right. I rather want to build connections and integrations with all of those systems. And for sure this also requires focus and resources. But I believe in a future where we are a best in class, end to end observability platform, funneling the insights in the right systems that our teams need them in, be it a content management system, be it a PR system, be it a community system, right. We want to funnel those insights back into those systems. The whole workflow topics comes with that. But we're definitely not going into whole monolithic. Let's build out a suite that does all of that. Marketers don't need yet another content tool where they generate content. They already have plenty. They don't need yet another PR more
- [20:48]
Jordan Cooney
so now that we have LLMs so you can just create your own quickly.
- [20:53]
Thomas Payham
Exactly. The yeah, you probably don't see us going into like let's here's a content platform where you can manage and organize all of your AI generated content to rank better. We are rather building out those integrations and connections and providing the insights into those where needed. That's our approach. But you know, I don't think there's a right or wrong here. Right. I mean obviously we see startups and companies have a different play game than us, right? And all come with pros and cons. And I think for us, I mean we had considered VC in the first place but for us it just felt more natural. And for us as founders really and with our personal goals and ambitions to stay independent, to stay lean, I think also thanks to AI there are lots of potential ways to also outperform the bigger companies and the bigger, the bigger teams. Our investment goes towards product, our ecosystem and also to our knowledge. Right. I think the knowledge we have built up and the knowledge we will build up will also win in that market as a best in class observability platform for AI.
- [22:06]
Podcast Host (Intro/Outro)
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- [23:34]
Jordan Cooney
I love it. I mean I think that this is a distinction in the marketplace, right. This is one of the noisiest categories and I, and I even find it funny, you know, we're recording here off of the, the backdrop of OpenAI and ChatGPT announcing ads. And, and just this past week they also announced how they're going to measure ads, which is going to be on an impression basis, which is, which is how the kind of the Internet originally started when it came to selling ads. It started with a cpm. Now the one terrifying thing, and I know for our European audiences this might not sound like a very important Data point, but ChatGPT's CPM, essentially the effective rate that they're charging Advertisers is around $60, which is the same CPM of running a Super bowl ad. So you just have to understand the context of this cost. And, and one of the questions I have for you here is, you know, the reality is that the old metrics we've been using are not working. We're moving into this whole new paradigm shift of how we're measuring our performance inside of these models and these response engines. How are you thinking about measurement? What are the key differentiations between traditional search and now, you know, AI discovery? Give us some insights into how you're seeing the transition of the leading and lagging metrics that marketers need to use.
- [25:09]
Thomas Payham
Yeah, I mean, to your point around cpm. Right. I mean I don't necessarily would say it's impression, but it's, it's brand visibility. Right. I think that the main KPI we most of our teams we work with, look at us, is brand visibility. How visible are we as a brand on these different AI models and engines? I think that's the main one we all want to influence at this point. As a second layer to that, I believe it's three buckets right now. It is AI crawler engagement on our own websites. How many of those AI bots end up on our websites or I guess what might also change in the future, Our content and how they engage with our content there. How do people engage with our content? Coming as a referral from the different AI search engines. And then there's a big indirect impact, right? People most often, especially in B2B where user journeys are much more complex. I mean they end up maybe on the third or second step on our website or some sort of web property of ours, right? So I can give you many examples where, I mean as a user myself of these systems. I've been doing some early on research on for example my next vacation trips, right? Going to Italy. Let me ask ChatGPT for the best family friendly hotels in a certain region. I don't click on those links directly, but I'll eventually come back to a Google search. I come back through a direct search. I think that indirect impact right now is something where we have to rely on self reported attribution and similar efforts. But that's, that's on the second layer, right? So the second layer, bot traffic, human referral traffic, indirect traffic coming from branded and organic searches and ultimately it all, all leads to the North Star. How can we, how can we influence our brand, our brand visibility? So if I'm on hotel in Italy, I want to show up with certain characteristics and I guess facts when, when people do their vacation planning. So I think to your point, right, the big shift, and this is why I'm also a big believer this is not just SEO because SEO teams historically have been optimized more for performance over brand. We now see this big shift towards brand, which one makes it exciting for brand marketing teams and brand in general. But two also basically means we need to cut down those team silos and all work together towards the same goal, right? No matter if it's SEO teams or, or brand slash PR teams. That's kind of, that's kind of why I'm not. It's not SEO is not that for sure not. But it's also not, right? This is also not SEO per se.
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Jordan Cooney
And do you believe that with this transformation of ChatGPT moving into the ads world, there's going to be a higher degree of integrity behind the insights we are able to gather about what's happening with consumers inside of these AI responses.
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Thomas Payham
Yeah, I mean, it's going to be interesting, right? I mean, we're pretty early on with the whole ad announcement from OpenAI, so I'll be super curious to see what exactly OpenAI releases in terms of data and insights. I believe there has to be something like, I mean, obviously we all enjoy the ad managers from Google and the insights would get there. So I believe there is more data coming directly from OpenAI. There has to be. But at least to my knowledge, OpenAI hasn't revealed a whole lot on how that's going to look like. But for sure, the more insights we'll get directly from OpenAI, the better it will be for us as marketers in general. But yeah, let's see how the next couple of weeks look like with the rollout of the whole advertisement program.
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Jordan Cooney
I mean, yeah, still very early days here. I think there's also a benchmark threshold of a million dollars of initial spend. I forget. So, so again, this is a very, very, very small population of advertisers. We're still early in, in. In what's happening in, in how these models are going to implement this and how, how they're going to do it in a integrous way. Because a response world is very different than a rankings world. Right? Rankings naturally created space for ads in responses. I think that there's likely to be some real friction into where and why an ad shows up. Now, shifting gears in our conversation, one of the unique things about Otterly in the way you've approached the market is that you guys are integrating much more so than building. And so tell us a little bit about how Otterly integrates with other tools and other partners to scale the utility of the platform.
- [29:59]
Thomas Payham
Yeah, yeah. I mean, great question. I think integrations, very frankly speaking, happened organically, meaning they happened by demand. Right. So when, when we launched, and I think we launched the first product iteration end of 2024, we were actually approached by SEMrush. Right. So SEMrush, big SEO vendor now acquired by Adobe, reached out to us and was like, well, we really like what you guys are building. Shouldn't we talk partnerships? Right. So we had a few conversations with Semrush and ultimately, long story short, in January last year, January 2025, we launched and announced our tech partnership with Semrush. We launched in their app marketplace and ecosystem and since then have been working with Semrush as An SEO tool, right? For us it was a natural fit. I think the same thing happened on the Semrush side, right? It felt like a natural fit for them as well. Because at the end of the day, going back to the point earlier, I don't want to treat AI search as a silo, right? Obviously we all engage in Google, we all use ChatGPT in those systems. We want to make sure that data insights also flow between those systems. So that's one partnership. Actually the very first partnership that happened beginning of 2025. Later last year, we also announced partnerships on the tech side of things with PressRanger as press release distribution service. Because we basically saw the impact of pr, right? And how our customers were seeking for future proof PR solutions that helped them do better PR and Urden Media, right? So again, it happened because our customers needed a tighter play, a tighter integration between the analytics layer that would come from Ottiliei and the PR outreach that would come from a solution like PressRanger. Same thing with content, right? We announced a partnership with storyblok as a modern headless CMS because of that. Right? Because we would realize, like storyblok, that a big impact on performance is coming from on page content and how content governments and also content updates would help to perform better on ChatGPT. So we announced that and we're also actively working on other content partnerships and CMS integrations. There are also certain AI content generation tools out there, like Newsroom AI who are very specialized in the editorial process. They work with lots of publishers and newsrooms. Right? So we will team up because their clients and customers would also need analytics layer and our clients who are in the publishing industry would also need a tool like theirs to get the job done. So as you can hear already from those couple of examples, we always look for tech partnerships where we can provide better value to our marketing team seeking for a fully fledged end to end process. Right? And again, we're not building out everything, but we rather look for partners where we can integrate, where we can team up to help our marketing teams, content teams, do a better job on that.
- [33:17]
Jordan Cooney
Here's where I find this to be super interesting and I think you have a remarkable opportunity in these partnerships because the market, even in 2025, shifted rapidly into these ecosystems and understanding why these ecosystems so heavily influence LLM responses. Reddit is probably the most headlined community platform of 2025. I'm already seeing a lot of noise around Wikipedia for 2026 and how you're cleaning and updating those entries and Then to your point, having these press partners, I look at your partnership strategy and I think to myself, there's a lot of benefit in thinking about the future of AI search as a multi channel influence engineering, that you're influencing all these ecosystems in order to help create clear, actionable, useful responses in these models, in these partnerships. And as you think about Otterly's future, what are marketers? And how should marketers, regardless of their background, SEO or not, be thinking about leveraging the data that you provide inside of these other channel ecosystems? Like pr, like social, like paid?
- [34:40]
Thomas Payham
Yeah, I mean, I think the most underlooked factor is entity recognition. Right. And what do I mean by that? The reason why we're building out those integrations and partnerships is also because we've been as marketers, we've been really copy pasting content from one place to another. Right. There is maybe there is a product page on our website and an about page on our website, managed in the CMS at the same thing. Every press release has a certain about us page as well, a certain about us paragraph as well. Right. On the community platforms, obviously it's a bit harder to control how we are being portrayed and how we are basically being described as a product or as a brand. But all of those systems that I also mentioned earlier have product descriptions on us in there, company descriptions in there. And what we've been seeing is if that's not harmonized, if that's not cohesive basically across the Internet, then ChatGPT has a harder time recognizing who we really are and what we really do. So, and that's just one factor. Right? So if we look at that ecosystem, I think for me it's a lot about brand harmonization, brand auditing, and how we as a brand and how our products show up on all of those different places. We had customers who realized that there might have been some negative Reddit comments on some of their products. And historically it wasn't really a big deal because it never showed up on Google too much or elsewhere. But suddenly, for whatever reason, ChatGPT is citing those exact, precise Reddit threats. Right? And this most often sparks, first and foremost, an aha moment. Aha. These are Reddit threats that are getting surfaced. These are places where communities, people talk about us, talk about our competitors. But obviously in the second step, it makes marketers and brands want to optimize. How should we respond to that negative comment? What should we do about it? How can we make sure that there are also more positive comments on our products out there on the Internet? I think because the way those AI systems work in a more answer engine like way, those type of sentiments, those type of content formats are now getting more attention, but it also makes us, I mean I think that's a positive thing. Care more about brand, how we are being perceived as a brand. Right. And what we can do about it.
- [37:14]
Jordan Cooney
Love that. And this is a great segue for us to move into our lightning round. I'm going to ask you five different questions from our episode today and we're just going to quickly give a 30 to 60 second response on each of these to help our listeners learn and gain more insights from today's episode. So my first question. You ready, Thomas?
- [37:36]
Thomas Payham
Yes, I'm ready. Let's do it.
- [37:38]
Jordan Cooney
All right. What's the biggest myth about AI search visibility that enterprise teams need to unlearn.
- [37:48]
Thomas Payham
So I think we need to unlearn that those systems are not influenceable. So I hear a lot that while those systems are, we cannot really influence those LLM large language models and whatnot. That's not true. Most of them use web search type features of various degrees. And I've seen big success. Be it through on page or off page, on page is definitely faster where you can basically get your content cited within ChatGPT in a couple of days. So I think the biggest myth is that it's not influenceable and we can't do anything about it. We can definitely do anything. We can definitely do something about it. I recommend everybody to one, familiarize yourself with those engines, how they work, technically, fundamentally and B, either start your own POCs, your own experiments to learn firsthand, because every industry will provide different insights, will cite different websites, will show you different products and yeah, so it's about getting first hand experience in the first place and not being too focused on that myth, let's say.
- [39:00]
Jordan Cooney
Fair enough. You started up Otterly without any external funding. What's one thing that startup founders should avoid?
- [39:15]
Thomas Payham
I mean one thing to avoid is growing too quickly, hiring too quickly. Right. I think thanks to AI and all
- [39:23]
Jordan Cooney
the
- [39:25]
Thomas Payham
current times we live in, I'm a big believer in doing things that don't scale in the first place. And only once you found product markets fit, you can scale. Right. You can hire a team, you can build out different functions, specialists and experts and do all of that fun part. But do things that don't scale. Right. Is something that, where maybe some founders rather directly jump into hiring, spending, outsourcing without fully figuring out the whole challenge beforehand themselves. Yeah.
- [39:58]
Jordan Cooney
And I got a question, follow up question for you on this one because I think this is an interesting topic. You guys have built your business off of partnerships and off of some really strong product depth. When do you think as an AI founder you should bring on sales or kind of sales executive sales resources into your teams?
- [40:20]
Thomas Payham
Oh, that's a good question. So I think it depends if you are bootstrapped or PC backed. But I mean obviously we are a product led business, right? So in our case we brought in sales rather late and only after we as founders would be able to sell enterprise deals. Right? I think you need to sell as a founding team yourself first before you bring on board first sales executives, account executives and whatnot. But I mean it obviously depends on are you bootstrapped, are you VC backed or not. But that's how I would approach it, right? Only going back to the Commodore dia, only if you've done it yourself firsthand and you found techniques and you have a belief that it is scalable, then bring in people.
- [41:13]
Jordan Cooney
I love it.
- [41:14]
Thomas Payham
Bring in your sales team. But you need to do the hard part first yourself.
- [41:18]
Jordan Cooney
That's right. That's right. My next question, should brands care more about being linked or mentioned in AI generated responses?
- [41:29]
Thomas Payham
Oh, 100% about. You have to care about getting mentioned, right?
- [41:34]
Jordan Cooney
I can give you contrarian view there. You know all the SEOs out there are screaming right now, Thomas.
- [41:41]
Thomas Payham
Well, I mean let me think about an example, right? I mean if, if I have to choose between getting, getting my website linked and referenced cited versus my brand mentions, I would always opt for brand mentions because there's more business impact there, right? If I, I could optimize if I'm a sports brand, right? Selling running shoes, I could probably optimize my website to be cited and referenced linked for. How does marathon training work or what is a good marathon training plan? By positioning myself as an expert. Having content on site for that topic, does that influence the business in the same manner as getting mentioned as a product when people search for the best running shoes? Probably not, right? So I'll always opt for brand mentions because when there are brand mentions it is getting more eyeballs, it is getting higher attention within those AI answers. Love it.
- [42:46]
Jordan Cooney
What's one signal that AI models pick up on but marketers are rarely optimizing for?
- [42:55]
Thomas Payham
Oh, that's a good one. Wikipedia is still a hard nut to crack for many teams as well. So we saw a big impact. So we didn't have a Wikipedia page ourselves. For example, 12 months ago we launched one, we created one, I think about seven, eight months ago. And we saw some good impact there. So I think marketer is not really utilizing the the visibility that you could get through a Wikipedia presence through a Wikipedia page.
- [43:26]
Jordan Cooney
That's awesome. Yeah. I don't disagree. I think that playing those visibility platforms or ecosystems is really underserved and often misunderstood. Today the whole Reddit piece, I've seen so many just unclear attempts to influence or manage that and there are good ways to do it and then there's many, many wrong ways to do it. Do it. Last question for you here. If your entire SEO dashboard vanished tomorrow, what's the first metric that you would rebuild?
- [44:03]
Thomas Payham
Another good one? I'm inclined to say none. Jordan.
- [44:09]
Jordan Cooney
I love it.
- [44:10]
Thomas Payham
I love it. Yeah, I mean I said right. I'm a business driven marketer and right now I if I'm rebuilding a SEO KPI more metric than it's probably the the impression the impression share I would get on Google. I tend to to to look at also Google More as a brand building exercise, as a brand building channel due to all the changes that we've been experiencing in the Google ecosystem. Right. You mentioned some in the intro. Right. We most businesses saw a decline of organic traffic. I really believe that's not coming back. So if my SEO dashboard vanishes, then I don't want to build back that KPI because I don't think it's worth potentially even going after it in the first place. But I'm still interested in the impressions. The impression share I would get on Google overall and I would rather push for that.
- [45:07]
Jordan Cooney
So yeah, I love it. And that's a great place to wrap up this episode of the Voices Search podcast. Thanks to Thomas Payham, CEO at Otterly, for joining us. If you'd like to contact Thomas, you can find a link to his LinkedIn profile in our show notes or on thevoicesofsearch.com. you can also visit his company website, Otterly AI. If you haven't subscribed yet and want a daily stream of SEO and content marketing knowledge in your podcast feed, hit the subscribe button in your podcast app or on YouTube and we'll be back in your feed every week. Okay, that's all for today, but until next time, remember the answers are always in the data.