[00:00:00] Speaker A: Hello, I'm Jeremy Rivera, your unscripted SEO podcast host. I'm here with Jason Bernard of Kalicube, and I am really looking forward to this interview because I have so many questions about entities and Google entities and LLMs and the subjective nature of truth. So who may not be as familiar with you as I am. Could you give them an introduction to a little bit of your history? And I always do this focus on what you've done or where you've been that makes you a source of truth for your industry. [00:00:32] Speaker B: Right. Okay. My industry is search engine optimization or generative engine optimization or AI assistive engine optimization, whichever one you want to call it. I'm calling it AI assistive engine optimization because we're optimizing today for AI assistive engines like ChatGPT, Perplexity, Google, AI mode, Microsoft Copilot. Why am I an expert? Why can I claim to be an expert? Because I started in 1998, the year Google was incorporated with a website for children and grew it to 1 billion page views. In 2007, 60 million children visited the website. In the year 2007, a billion page views. We signed deals with huge companies like Tata in India and Samsung and Disney and ITV Studios. It was a huge success because of the success on the web and we were competing with the BBC and pbs. And a lot of that was down to my ability to, let's say, manipulate Google, get to the top of the results for all the different keywords at the time, but also market my platform as a brand. So the brands were up to 10, which was the company, and I was CEO and founder of up to 10 Limited and Buwa and Koala, who were the characters that my wife and I created. And so it was a mixture of smart brand focused marketing packaged for Google, and we got a billion page views in 2007. So from that perspective, up to 2007, I think, yeah, okay, this guy's obviously understood. In 2012, I pivoted my career and realized that I could change the way that Google perceived my personal brand. It saw me as a cartoon blue dog, and I wanted it to see me as an entrepreneur and digital marketer. So I figured out how to change its perception. So instead of saying, Jason Barnard's a cartoon blue dog, it said, Jason Barnard is a respected entrepreneur and digital marketer. And now at Kalicube, I built the company to offer that service to entrepreneurs around the world who want to make sure that Google and now AI are saying exactly what they want about them and make sure that Google and AI like ChatGPT, prioritize them above the competition within their niche. [00:02:43] Speaker A: I love that intro. And it leads us on a couple of paths. First, I'll just say that it's. Since you came from 1998, I'm floating this concept out of. Let's forget the acronyms. The problem isn't like SEO is dead or it's G or SEO is geo. It's actually our label as experts. And you came about in the age where a person of your talents was known as a webmaster. So I'm going to try to bring Webmaster back as an actual title because it's a much more fitting description of what it is that we're doing. We're integrating the available signals to whether that's through email, organic search, creating entities, connecting to other websites, through our site and through our business to change how we're perceived and hopefully drive traffic based off of that perception. So let's talk about how when you wanted to, when you made that change from a blue color cartoon dog, what became some of the pillar pieces of research or processes that you experimented with to uncover how it was that Google understood entities. And obviously this was the time, you know, that was around when Bill Slosky was doing a lot of research on, you know, patents coming out from Google. So if you could give us some of your research pieces or your case studies that helped you formulate an actual process and perhaps some of your understanding of how Google goes about creating entities. [00:04:28] Speaker B: That's a lovely question. Well, I didn't have the pleasure of meeting bill until 2018, and then we became very good friends. I love the guy. And we hung out. It was lovely. And he's such a smart chap. But back in 2012, it was very much about manipulating very simplistic algorithms with keywords and links. But the difference that I found was that it wasn't just my website. It was my entire digital footprint that I needed to manipulate. Because when you search for somebody's name or a company name, it fills the results Even back in 2012 with Facebook review sites, articles about you, your social media profiles. So whereas SEO would at that time have been focusing purely on the website, I was focusing on the digital footprint already. And that was a huge difference. So I was bringing my SEO skills to a wider range of sites. And then I realized, well, actually, this digital footprint is the foundation of everything that I am online. It drives traffic directly from Facebook, from LinkedIn, from YouTube, from articles about me, articles I write on Search Engine Land. But I can also use that to Change the results about me so that when somebody has seen me because I've been standing where they're looking on YouTube or on LinkedIn and they search my name, I look like a superstar. And that was in 2012, so I wasn't really looking at entities. And then 2015 with Hummingbird and From Strings to Things, I thought, oh wow, I've hit the jackpot and I created Kalicube. [00:05:56] Speaker A: Yeah, you definitely hitting on 2012 from that perspective. I think at most there was kind of in 2010ish, a rudimentary concept of, you know, reputation management in, in the SEO industry. I was in the the around the real estate niche and I know that there were some Realtors who were calling in to our support line asking there's really bad stuff about me. You know, some deals have gone south. Can you help me get rid of these articles that are showing up on page one? But you're right, it did change with Strings to things Hummingbird. I think there are a couple other additions past that that still factor it. But I think the appearance of the Knowledge Panel as a regular SERP feature really cemented entity optimization as something that entered a lot of people's minds. But I'm going to throw a challenge onto that of we were always guessing that click behavior was was a factor and now we have the lawsuits to finally prove that we were being gaslighted by Google all through 2010-2020 about whether or not click behavior had any impact. Absolutely does. But in the fact of following along how brands are searched organically and click behavior, how do you see those two things being connected? I see a direct correlation between the increase in brand branded search being a positive signal about your entity. Would you agree with that assessment and how does that play into your general strategy? [00:07:34] Speaker B: Absolutely. Increased brand searches is definitely a powerful signal to Google. As you said, Google were gaslighting. In fact, you have to remember that people like John Mueller and Gary Elish and Danny Sullivan are actually just there as public relations people to try to keep the SEO community from cheating too much. So they are going to deny a lot of stuff because they don't want people gaming the system more than they currently are. And I think the SEO community gets caught up in Google is telling the truth and Google is telling the truth that it needs to tell. And we can go into what truth is later on. Because what I noticed with Gary and with John and with Danny is that they say things that if you read it exactly what they said, they don't say exactly what the SEO Community thinks they're saying. So they would say, for example, I mean, in this case, potentially clicks don't change rankings directly. And it's the word directly that gets them out. It's their get out clause. So you'll find when you listen to them, there's always that little thing. And then what then happens is, of course John Ludo was complaining about it at one point to me, not nastily, he was just saying, the problem is it all gets taken out of context. So that word directly gets removed, then repeated, and the truth becomes something else. Whereas the fact is he said directly. And I think that's a very important part of kind of the relationship between Google and the SEO community. Then I did a series of interviews with the team leads at Bing, Fabrice Canel, Nathan Chalmers, Federic debut, and they have nothing to lose. So they shared a lot of the secrets that Google weren't sharing. And then when I published the articles, people said, but that's Bing and not Google. And he's saying, well, it's the same technology, the same audience, the same aim. They are not reinventing the wheel. So they're both doing more or less the same thing. And one really famous or really famous for me in my little mind is that I talked about the whole page algorithm that Nathan Chalmers explained to me at Bing. And it's the overriding algorithm that reorganizes the serp. So even if you have a place on that serp, theoretically, according to the Darwinistic theory that you can read up on Search Engine Journal, the whole page algorithm is building what it believes to be the best result for the user as opposed to the best result from the algorithms. And after three or four years, three or four years later, Gary Ilish said, oh yeah, we've got that. And it's called the Magic mixer. And at that point you kind of say, well, okay, I knew it and I was sharing it, but people didn't believe me. And it was only four years later when Gary Ilish admitted to it, that all of a sudden the whole page algorithm that they call the Magic Mixture Mixer becomes a thing. And I think you've got to remember that they've got to protect what they've built. Bing, don't chatgpt, don't the pretenders to the throne have got every interest to help us. [00:10:23] Speaker A: That is true. And that really came to mind. I saw Fabrice present, I think it was either at Pubcon or SEOmoz at a conference where he was introducing this, the new Promethean change system that would allow their, their, their search results to connect to their chat. And I knew then that they were going to be the index of GPT, they were going to be the index of the unaligned non Google AI systems because it was transformative. Certainly, you know, is the first tip off of that. Now there are indications that maybe there's a backdoor, a secondary system where chat GBT or others are able to access Google rankings in some way or Google index in some way. Whether that's just brute force crawling and they're building their own, own systems behind it. But certainly being as interestingly back in the game, you know, what is old is new, you know, so we again have a bit more of a competitive playing field when it comes to the digital marketing field with the entry of chat GPT gathering so much focus. But it's in my opinion, I think how LLMs process entities is as new within Google as it is when within Bing. So from your understanding, what is the implication of machine learning, LLM tools, understanding of entities versus the pathways or process that you reverse engineered with Google and what are the differences and what are the similarities? [00:12:16] Speaker B: Well, an LLM is designed to have a conversation, so I call it the algorithmic trinity. All of these engines are built on the same three technologies. LLM chatbots, knowledge graphs and search results. That's how they function. So they have the LLM that allows it to have a conversation. They have the search results for up to date information or niche information they don't already have in the training data. And they have knowledge graphs for fact checking. Now that immediately takes you to the point of saying, okay, we've got three different technologies all coming together in different mixes in different platforms. Google have a huge knowledge graph and it's much more important to them than it is to ChatGPT, who may or may not have one, but I would bet my bottom dollar they do have one. It just isn't very good yet. Bing certainly have a knowledge graph and it's huge and apparently it's incredibly good, but they don't let anybody look inside it. But the point is whether it's an LLM chatbot training data, whether it's a knowledge graph or whether it's search results, they all use the web as the data source. So at the end of the day you're feeding all three of the algorithmic trinity from the same data source, which is the web. Which part of the web do you control your own digital footprint? We come Back to Kalicube 2015 when I started, which I love. [00:13:24] Speaker A: Okay, okay. So you're saying, you know, with these three technologies, the other two feed out of the one trough. And since you can control the one trough, which is your personal data stream, then that's where your focus lies. Because the other two are. You can't directly control them. They are secondary systems in and of themselves. That does make sense. [00:13:53] Speaker B: Then you come to the point, is by controlling your digital footprint and your relationship to your competitors and your relationship to your audience, and that's what you need to look at, is my audience, me, my competitor, who am I? And what is my relationship with my competitors and with my audience? And how can I communicate that to all three of the algorithmic trinity? And as you rightly say, the search results are going to be relatively reactive. A week, maybe a knowledge graph is going to take three months. An LLM training data is going to take you a year. That's the way it works today. And if you look at the world from that perspective, you're using the same data source to feed all three of the algorithmic trinity with different time lapses before the effect is felt. [00:14:34] Speaker A: So when you're thinking about optimizing an entity for a client, is there a differentiation between what people consider to be social media sites versus forums versus directories versus news outlets? Is there a utility in distinction between those, or are they all kind of the same class for you? [00:15:00] Speaker B: It actually depends on the industry. In the legal industry, the legal directories have huge power, so you have to look at which sources the algorithms trust, and that's dependent on the industry. Wikipedia apart, Wikidata apart, it's all industry dependent. So IMDb is very powerful for movies, music brands is very powerful for music. Spotify is very powerful for music and for podcasts, but not for business. Crunchbase is powerful for business. So you need to look at the relevancy of the platform to your industry and you need to think niche. Now, what we found at Kalicube is that an incredibly powerful domain for a specific entity is not going to be the same even across an industry. And I can give you an example is that I created my website and it now has huge power over one of our clients, Jonathan Kronstadt, because I've integrated him into my peer group and I've made that relationship with my peer group on my website. And Google and ChatGPT and perplexity all extract information about him from my website. And I don't know Jonathan Kronstadt that well. We worked with him, he's a client of ours. But that relevancy and the Authority that my website has on this specific person who comes from Kajabi and not directly from my industry is incredibly important. So you can't take it as read that a website you haven't heard of has no authority. [00:16:29] Speaker A: I think that ties into a concept. I had a long discussion with Darth Na Darth Darth autocrat on Twitter in DMs about the potential of what signal was actually behind the scenes for the medic update around 2019 where we had an ecosystem of sites where chiropractors were outranking Medline mostly because they actually hired Gantt writers and qualified, super qualified journalistic writing and they had 20,000 word essays on turmeric whereas WebMD had a sentence and overnight we saw that flip across the industry and we were, we posited some theories and he proposed that the concept of distance from seed as a portion of the trust rank factor, meaning that there are seed sites out there and the distance from seed could be could have been that key, key relevant signal or that authority signal that you could flip overnight and switch up basically solve the problem. Because as good as Josh Axe might be as a chiropractor and have a team of writers, he's not getting a, a link from the Mayo Institute. WebMD is for their single sentence. And so you have the disappearance of a 20,000 word, well researched article, fully cited everything that they said eeat written by an expert. But no, the site was had had a link from a trust more trusted, less distance from those seed sites. Do you see a reflection of that seed concept or is that really the foundation of what you're saying is like industry like. Perhaps that's why we see industries niched and gathered is because we have trust flowing from certain sites within an industry which tend to then create the ecosystem. [00:18:27] Speaker B: Yeah, I mean we had data of where knowledge comes from in Google, in Google knowledge panels in particular. And there are four different sources. There are Google knowledge verticals like Google Maps, there is Wikipedia and other highly trusted sources and then there is second generation that is the ones one step away from that seed set. So what we managed to identify was the seed set and then the one step away from the seed set and what you ended up with and this must have been 2021 or 2020 when we started seeing it was a lot of resources that just don't make sense that you simply wouldn't trust by looking at it. And that was the time when Google said okay, the knowledge graph has got its seed sources and we've stuck to it religiously for the last, whatever it is, six, seven years now, we're going to let it go. And it started pulling up different sites and that's when my site became the authority for the TV series me and my wife made. Up until that point, my website didn't have any authority on that. It was Wikipedia, Wikidata, IMDb and fandom. And then all of a sudden the knowledge panel started to contain for all the characters we created, started to cite my website and information I fed from my website. For example, they are cartoon characters. They started off as fictional characters and I moved them to cartoon characters and my website was demonstrably the motor behind that. And that happened around 2020. I think it was 2020. I can't remember the exact date. And that was it. Moving away from the seed set where my website, even though it's not got a high domain authority, it has a very high entity authority for very specific entities that are related to me. And that's hugely powerful. And it's even more so today. [00:20:19] Speaker A: Let's talk about the the impact of ChatGPT's seeming reliance on citations from press sources, journalists, the concept of subjective truth, and how SEOs have been a little bit remiss in separating themselves from the previous generation of PR people. [00:20:42] Speaker B: Right. Well, the question of truth. We were talking just before the show about claim frame and proof and this immediately gets us into this philosophical discussion is I claim that I was born in 1966 and that's pretty easy to prove. I claim that I'm a world leading expert in generative engine optimization, or world leading expert in AI assistive engine optimization as I call it. That's much more difficult to prove because it's subjective. But I can make the claim on this show, framing it away to say, well, because I'm an expert in answer engine optimization, therefore I am an expert in AI assistive engine optimization. Generative engine optimization is for me the precursor to AI assistive engine optimization, which is the next step. Therefore I'm an expert in generative engine optimization. That's a framing. And then to prove it, I get people like you to say, I agree Jason, you are an expert and it becomes truth. Is it fact? No, but it's truth. [00:21:36] Speaker A: Okay, so I say Jason Barnard is an expert in geo in AI SEO. And I add that to show notes of this show, going to write an article on it on SEO Arcade, going to give you an article that you can post to your site as well. So there will be three concurring sources with my my statement of that fact. So now those, those words exist in multiple places online. And so if a query comes into an LLM tool and it has access to an index and those pages are indexable, the fact that those four concurrent occurrences of that statement now lead to a claim becoming now a nearly provable truth. Right. [00:22:34] Speaker B: Yeah, yeah. And kind of. It may sound like cheating, but if you think about human behavior, that's exactly how it all works. Anyway, is somebody downstairs from me says that's the best boulangerie, that's the best bakers. I believe them. Somebody else says it, I believe them. So you end up with the truth that this is the best bakers in this town in the south of France where I live, because people repeat it and if you get reviews, it's people repeating that this is the best bakery in France sommier in the south of France. And truth becomes reality or truth becomes truth or fact due to people repeating it. And what you realize after a while is that people sometimes just repeat what they've heard and they don't actually have an opinion. And the more that happens, the more it becomes proven and hardened down into the truth of humanity, even though a lot of the people who are saying it have absolutely no idea what they're talking about. [00:23:25] Speaker A: So what I think is interesting is that, you know, this is something that Rand Fishkin came up with. The concept of unlinked citations. 2013 2011ish even you know, going back there of like, hey, there's value in the mentions. And I don't, Yes, I think at that time it was true there was value in the mentions. But because we lived in a Google centric economy, the fact that links were, were the true, were 10 times weightier or 10 times more effective at providing that same signal. Most SEOs would either poo poo or just outright ignore the concept of okay, well if I get their name mentioned, their brand mentioned this facted somewhere. Unless you were, unless your client came to you and said, hey, I need to be, I can't get a Wicca Wikipedia page. And then you have to jump through the hoop of oh well, you don't have any actually journalistic mentions of your business confirming these facts. You know, I was given that challenge in like 2015 of like hey, we're our Wikipedia page. Can't get past and like okay, well you have interviews with your, your CEO but never actually said anything about your business. You never said how many people were there. You never said how when you were founded. You never said that in the interviewer never confirmed any of those facts, so we can't use that interview. So I just find it fascinating that, you know, this concept, some of these concepts have existed, but now we're not in the golden age of Google dominance SEO focus, and it's opening up the playing field, which then reveals the fact that it's been this way all along. [00:25:20] Speaker B: Yeah, well, there's a couple of things I would say there. Number One is whoever 10 years ago was saying I don't care about mentions should be kicking themselves today. Because in this claim frame prove system, I see a lot of people talking about answer engine optimization and I thought, okay, if you search for who is an expert in Answer Android optimization in January of this year, I didn't even appear on the list, but I started a series on SEMrush called SEO is AEO Answer Engine Optimization 15 part series. I did a podcast webinar, sorry, with Trustpilot article on Search Engine Watch in 2018. Lots of mentions, but not very many links. So I could actually then explain to the AI, to the LLMs, and to the search results. I started this in 2018 and I can prove it. And here's the proof. And all of those mentions suddenly come in very useful because now if you ask any of these machines who are the world's experts in answer engine optimization? Six months down the line, Jason Barnab, he coined the term, and that's the power of this work that we were doing 10 years ago that didn't seem worthwhile. And the second point there is you talk about Wikipedia and there's an obsession with Wikipedia and it's come back. It was kind of disappearing because Google wasn't paying so much or isn't paying so much attention to it anymore. And all of a sudden everyone's saying, oh, the LLMs are using Wikipedia all the time. You have to think about scale. Wikipedia has 6 million articles. Google's Knowledge Graph has 54 billion entities. The scale is 10,000 times bigger. Google doesn't need Wikipedia, doesn't care about Wikipedia above and beyond. It's a seed source. And if you get added to Wikipedia, it definitely helps you get. But LLMs are way beyond that as well in terms of the amount of data they've got. And if you look at, and here's something I was looking a couple of weeks ago is you look at an entity in the knowledge graph. It's a thing. And little by little, you can reinforce the presence of that entity in the knowledge graph and its place in the knowledge graph relative to other entities and its relationship to other entities. But if you think of an LLM, the equivalent is a parameter. In an LLM, I'm a parameter. And if I reinforce that parameter, it's the same effect as reinforcing an entity in the knowledge graph. And I can reinforce my place within the LLM relative to other parameters around me, such as skill sets, other people, other companies. So you can actually look at both an LLM and a knowledge graph in a very similar way. If you accept that a parameter and an entity are essentially the same thing. [00:27:48] Speaker A: Does that mean that potentially, you know, a marketing team faced with a challenge of a disruptive technology, is almost looking at a. An adjustment to the knowledge graph understanding of that old technology and the relationship to that new technology? [00:28:12] Speaker B: Yes. [00:28:12] Speaker A: And the job is to put articles out there to craft the semantic connections from old A to new B. Yeah. [00:28:23] Speaker B: And that's a really well put, if I may say so, Jeremy, because it doesn't know what it doesn't know. And like with the knowledge graph, it can't understand something if you don't relate it to something it already understands. Now, in a knowledge graph, it's a question of understanding. With an LLM, it's a question of having that parameter to hook the new new parameter onto. If the other parameter, if there are no parameters to hook onto, it can't include it in any meaningful way in its data set, it won't be accessible. So for a knowledge graph and an LLM, I would build the same way as you say. You say, well, this is the old world, this is the new world, and this is how they connect, and this is why we are important in that connection. And then you become part of that connection. [00:29:02] Speaker A: I think that's a transformative way to view the, the transitional effect of this new technology, because I've been kind of seeking, kind of seeking a newer framework to approach my SEO work with, you know, with, you know, taking on the webmaster idea of like, okay, if I'm looking at these connections, looking at my role, and I'm not narrowly focused anymore, you know, the golden age of Google is gone. You need to look broader than that. I think that it's a very useful mindset to consider that the LL&LLMs is learning and you can influence that learning process. [00:29:45] Speaker B: Yeah. [00:29:46] Speaker A: Do you. [00:29:47] Speaker B: With an LLM, the. I. Sorry, go ahead. [00:29:50] Speaker A: No, let's. Let's go down that. Because I have a little bit of a tangent and a challenge from another expert that I'd like your take on. [00:29:59] Speaker B: Go ahead. No, no, no. The thing is, I agree, it's that we're feeding these machines, whether it's the LLM, the knowledge graph or the search results, we're feeding them through the web index. And that web index is being sucked up by Google, Bing, ChatGPT, sometimes in real time. And the common crawl and Perplexity have theirs as well. So you're feeding all of these machines, whichever one it is, with exactly the same data source. And if you can organize your data source to be logical, because machines are logical, to be meaningful and to be valuable, and make sure that you're connecting out to the proof that what you're saying is true, or at least supported by people and companies and entities within your industry, then you're onto a winning mindset, at least. [00:30:45] Speaker A: So I'm not sure if you've followed a lot of what Mike King has recently been putting about putting out or, or any of his recent talks, but he talks about the concept of query fan out within Google and using that as a useful framework to adjust content marketing and the content that you put out on your own site. Do you agree with his general approach or does that dovetail with what you're doing or how, how might that be different from your, your systems? [00:31:22] Speaker B: Yeah, well, I talked a couple of years ago about cascading queries. So what he calls fan out, I call cascading queries. And it's Fabrice Canel from Bing who explained that to me two years ago when Copilot was launched. Basically saying what we do is take the first query and find the other queries that make sense around that query to make the final query that allows us to produce the results. So what he's calling fan out, I was calling cascading and it makes total sense. And I wrote an article on search engine Land a few months ago about Micro aeo, micro answer engine optimization, with the idea that if you can optimize for each of those cascading queries and you can become the answer for multiple ones, you will be included in the LLM output in AI mode or Copilot, if that makes sense. [00:32:09] Speaker A: So one interesting side note is that a chunk of the first sites hit by the HCU update were very notably sites that very specifically reverse engineered. What were the people also ask entries for a particular niche. I think it was like a cart, I think it was Naruto and they reverse engineered and they took all of the answers from that were populating there and created their own site that had, it had had their own similar but not very different answers to the same thing. But that programmatic approach got Slapped by hcu. Do you think that that was just a side impact of what HCU and the language learning model behind that system was trying to do? Or is it indicative of a problem that you might run into if your primary content creation system is based exclusively or primarily off of reverse engineering? People also ask for the structure or semantic content that you create for your site. [00:33:25] Speaker B: Yeah, well, I mean, I would argue that reverse engineering Google is a futile task. I mean it's something you'll chase the rest of your life and you'll lose. I would say build your brand, build a decent marketing strategy. Stand where your audience is looking, offer them the right solution in the right format, the right place. Invite them down the funnel on LinkedIn, on YouTube, wherever it might be and package that so the machines can understand it. And it's not just Google, it's Google, it's Perplexity, it's Microsoft, it's ChatGPT. So at Kalicube we have the Kalicube process, which is the digital marketing strategy, brand focused digital marketing strategy. Stand where your audience is looking, offer them the right solution in the right format at the right time where they are looking. Package it so the machines can understand it and the machines will simply replicate what they see. That's what I would do as a strategy. And when you come back to what you just mentioned, which was I'm looking at what the results currently are in Google and I'm simply going to write a better answer that's doomed to failure in the new world. Because LLMs, once they've got the information, they don't need it again. Once they're convinced that the answer is correct, they don't need to come and find the answer again. So you've lost the war. So what you need to do is give a new perspective or a new angle on it. Then they become hungry or additional data. So when you're giving an answer and you're thinking, okay, well I'm answering something that's already been answered, that's pointless. What I need to do is add new data, add a new perspective, or as you said earlier on, take it to a new place, move the discussion forward, forwards, move the world forwards. And then the LLM and the knowledge graph and the search results will always be your friend. [00:34:57] Speaker A: I think, I think that's true. It also is kind of the, the only escape route out of the snake eating its own tail of LLM training material I like that is continuing continuingly more and more, eating more of itself. The only way that changes if, if we as Humans make distinct efforts for information gain because there are only so many plumbers articles that we need to say how to fix a leaky faucet. And that was Google's problem, right? Like every single plumber was writing an article on how to fix a leaky faucet. So there's no information gained to them, but a conversation with a podcast, an interview with a 30 year plumbing expert. That conversation is definitely going to have some information gain, a unique insight, some different ways of looking at how plumbing is attached to other functions of the house or is part of connected to the value of the home. Those aspects and connections like that human connection, that's information gain. [00:36:06] Speaker B: Yeah, yeah. And I mean the downside to what I've just said and what you've just shared is that every time you give the algorithms the new information, they store it and they don't need it again. So you need to keep moving forwards. But as a human being who has ambition and I believe in learning, perpetual learning throughout life is part and parcel of my DNA is saying, well that suits me fine because I want to keep pushing knowledge forwards, I want to keep adding value, adding additional knowledge to the human race. So for me this is a very positive thing. But it does put a lot of pressure on everybody to keep moving the. [00:36:40] Speaker A: Needle forwards as a kind of wrap it up. If you could give an SOP or a tangible, physical, specific completable task an SEO listening to this can do to start going the callocub cube method, going the information gain route. What would be those practical hand ons, hands on steps to execute or to hand to your SEO manager to do in the next week to start moving things in the right direction? [00:37:12] Speaker B: Well, the very first thing to do is look at your about page on your company website or your personal website if it's a personal brand and make sure it states clearly who you are, what you do, who you serve and why you're important within your industry that it links out to all of the corroborative sources, all your social media profiles, all of the articles that talk about you and they all say the same thing and if possible they link back. So you end up with an infinite cycle of self corroboration that the machine understands. Because if it doesn't understand who you are, it can't attach credibility signals E E A T or I call them neat N E E A T T it can't attach those credibility signals to something it doesn't understand. So that understandability is the foundation. If you don't have that, you're not even in the game, then you can start building eat credibility and knock yourself out. The second thing I would say, so that's the first practical thing. Sort your about page out on your website. The second thing I would say is, oh, and that's called the entity home, by the way, the entity homepage. Google call it the point of reconciliation. You could call it the canonical URL for the entity, but you need to own it. If you don't own it, they're going to attach it to LinkedIn or Instagram. I've seen pop stars whose entity home is Instagram. You don't own it. That's rented space. You don't want that. You need to own that entity home, that point of reconciliation, that entity canonical. That's point number one. But then if you look at your website in the same way, the entity home website actually should reflect your entire digital footprint and then you own your digital footprint. So look at your about page as the entity canonical for just the entity itself, your company, and then look at the website as the representation of that entity and its digital footprint and you're on the right path. [00:38:53] Speaker A: That definitely makes sense. I work with my friend Michael McDougald who switched from personal branding to trying to launch an agency and he was getting nowhere with his right thing. Agency was what he wanted to be, but it just wasn't showing up at all in the serps. Okay, you don't have an about page. Let's, let's fix that. So I'm glad to hear echo of like that Basic Advisor. Maybe if you want Google to know about you, you should tell it about you, you know, and that happened with another, you know, brand I worked with, Save Fry Oil. It just kept showing methods of how to save fry oil. And like we need links, you need entity mentions, you need, you know, be in directories, you know, they had, you know, social media profiles, but they had no anchor text profiles, very few mentions of their brand elsewhere. So I'm and sorting it out, getting the about page added. I love that it's a very tactile, very tactical and within the reach of nearly every SEO. Some SEOs might have to get permission to edit the about page. I once spent four hours in a meeting with seven CEOs to add a single word to the homepage in the H1. But hopefully, you know, not everybody's bound up in that much red tape and companies do love talking about themselves. So if you can frame it as we want to surface your expertise as much as possible, let's let's find other ways to develop your about page and surface everywhere. You're an authority. That resonates so well with CEO 100% yep. [00:40:30] Speaker B: So the Kalicube process. You can actually download the free [email protected] k a l I c u b e.com guide guides and it's all based on understandability. Does the machine understand who you are? What you do? Who you serve? Credibility? Does it believe you to be the most credible solution in market deliverability? Does it have the content from you that allows it to deliver you to the subset of its users? Who your audience? That's the key. The Kalicube process. Understandability. Credibility. Deliverability. And if you can nail that, you're going to win the game that's coming. [00:41:00] Speaker A: Fantastic. Thank you so much for your time. I will be linking the show notes obsessively creating a couple of different barnacle versions of this article to go out there, so anybody that's interested definitely will be getting their fill of versions of this conversation. Thanks so much for the expertise. [00:41:21] Speaker B: Thank you so much, Jeremy. That was delightful.