AI Reveals Competitor Content Strategies in Minutes with Chris Long

Speaker A: Now one of the questions is how much do we teach? How much do we let people lean on the automations versus having them learn the non automated workflow, doing it manually, becoming somewhat familiar with that for the automation. So it's something we haven't even completely figured out but also something we're thinking about. Whereas if we don't want the team to be weak and 100% reliant on automation, when you make someone master a skill first and then use the automation to augment that afterward.

Speaker B: Yeah, yeah, super interesting. All right, uh, Chris, welcome to the show.

Speaker A: Appreciate you having me so much Aidan, great to be on.

Speaker B: So Chris, you've been in SEO for a long time. It's SEO, aeo, geo, whatever the latest flavor is. But this is your thing. So I thought who better than to ask the question how has AI impacted what you do?

Speaker A: I'm um. So I mean AI is impacting search in so many different ways. I think there's probably two primary different really models that you look at it. One is certainly on the operational side. Right. Um, is that basically so many tasks that you know, might have required someone to do a 30 minutes, an hour, whatever, whether it's creating a content brief, performing research. A lot of like the actual strategy, even some of the strategy work that we're seeing now is like their AI enables for a lot of automation around that. Right. Where especially now, uh, we built like a lot of like automation tools around briefing page refreshing, internal linking, all of that. That. So there was a layer of automation that's coming in in the day to day operations really ever since a lot of these AI models come out have come out. So that's been one of the big ways. The second way is, is also just the amount of AI that people now see like in the Google search results and you know, other people using like AI to discover products. Right. A CMO report came out where they said most B2B CMOs are now actually starting their search, uh, on an LLM and they're actually using Google search. 73% of them are actually using Google Search as a verification layer, not a discovery layer.

Speaker B: So that's interesting.

Speaker A: Yeah, especially, and especially in the B2B space we're seeing this huge shift in terms of like how people are starting their journeys, how they're evaluating especially if they're a buyer of a product. Right.

Speaker B: You know, it's super interesting. I agree with you just on that notion when I think about how I use LLM search. So I'll do my research in LLM and But even if I know the name of the company, so say that I figured out I want to talk to Nective, I will then go to Google and then search for next of even if it's just to find your URL. Right. Like so that's super interesting.

Speaker A: In that same report they also said like that's a primary way a lot of like C suite are using it. They're, they're looking for a company, they're finding the company and then they'll use Google as one of the verification layers is trying to find red flags for that company. So Google almost serves as a reputation management source.

Speaker B: You know what else is interesting just on that front, you know OpenAI had their uh, browser, their you know, Comet competitor AI browser and that was the thing that got me to stop using it. I thought it was really, really cool. But I just needed that navigational. I just need to get to a place very, very quickly that I could do in Google Chrome. And so I did switch back but I don't know, maybe they fixed that since haven't been back to that browser for a while.

Speaker A: Well, and it's coming, those, those actions are full on coming, coming to Google Yesterday they just released webmcp which basically is saying like it's, it's basically like structured data but for websites they basically can say hey, you need to mark up your website using these APIs. So like when we add agent features, the agents know where to go to click a form, like submit to, like you know, create a reservation, whatever. Like they're actually asking sites to technically mark that up.

Speaker B: Chris, say more about that. I think that's super interesting for everybody to understand. And so they built this thing called WebMCP because their view is they want to set the Rails so Chrome and maybe other browsers can do a lot more. So based on that, what do you envision that they will do in the browser?

Speaker A: Probably, probably as much as they possibly can. Right. In terms, I think that, I mean they are envisioning a world where someone says hey, I am looking for toothpicks or whatever, I'm looking for new running shoes. I need you to go out, evaluate all the options and then once you find me the best options I will point to go and actually you purchase them on my behalf. So they want their browser to be able to do everything from look at a product, navigate a category page, potentially add it to shopping carts and then they actually have UCP which allows you to like uh, completely check out. So they want so form fills, add to carts, these key Actions, right, Like image views that we will be taking as users, they want their agents to be able to take those actions. The problem they're saying is right now, just based on the HTML layer, the agents are okay at doing that, but not great. But adding the WebMCP will make their agents much more precise in terms of how they're able to actually interface with your site. So it's a very interesting conversation, optimizing for agents as opposed to users, which I think we're honestly heading more into.

Speaker B: So super interesting. So basically the view is that Google will make everybody get in line and if you have an add to cart or whatever else, you're going to all do it the same way or at least put the metadata and so that the agents can understand. So it's just like a common language. Just like HTML is a uh, is a common language and so so the agents can not make mistakes. So it's basically setting the rails for agents. We're not going to have this feeling, we're not going to browse websites anymore. I don't know what's going to happen. What is your view on that?

Speaker A: I mean there's a lot of different views and like, especially in the SEO industry it's been so, hey, optimized for the user and I, that is still definitely a good practice. I think optimizing for the agents is still undervalued and how important that is. It's like uh, I've heard other CMOs talk about like kind of like treating agents as a VIP customer. I very much agree with that. Where agents are going to be a significant user of your site. For many people probably the primary user of their experience with the web will be done through an agent, not, not necessarily them browsing the web themselves. And I think we're already seeing a shift like that.

Speaker B: So this is interesting right, because uh, I, I don't know. Are you monitoring traffic to the websites that uh, you know, you're advising or controlling? What percentage of traffic do you see are coming from agents today?

Speaker A: So you'll be able to see agents maybe from like the log files of your sites. We do monitor the traffic especially like LLM referrals. It's very few though. Right. So from, from traffic, from LLMs is almost, is nothing. I think it's, you know, I think they're sending, they have 12% of the elements, have 12% of the market share of Google but send 1% of the clicks of that agents you would probably more be able to see from your actual log file data. So that's if you wanted to see that, you could then go and say, hey, chat, GPT user bot, like how many times is it going to my site? Right? Then you would actually get an idea of like how agents are interacting. That's not going to be in your traffic data. You'd actually have to get like your basically server access logs in order to, to figure that out.

Speaker B: Very interesting. So yeah, it's, it's not quite there. And actually we have a, we have an interesting workflow at our company where you, every time, uh, one of our sales team has a sales call, you know, they ask the customer how did you hear about fellow? And then, and then the content of that gets posted to a Slack channel that we have. And so I monitor because I want to know how people find out. And the interesting thing is if we look at the click data of what percentage of people come through the LLMs, it's super low. I don't know if it's like 4%, 3%, it's something very low. But when you look at the conversational data, the number of people that reference ChatGPT or something else is like 30 to 40%. So people are definitely using it, but you're not able to track it through clicks. So this is just a, I don't know how to think about it. Maybe people will end up underappreciating how big it actually is. Uh, at least from you know, someone thinking, you know, is this important? Should, should we care about this? Do you find people do care or like, do they understand the gravity of uh, this as a channel?

Speaker A: Absolutely. Especially in the space we're in, especially in the world because we're generally working with like B2B, Series B and beyond that people are going all in. In fact in that same study, basically they asked CMOs what their biggest like new investment channel was. Then there was kind of two interesting insights. They went from 0% investment from AO/GEO in 2025 to 36% of them said they were going to invest in that channel in 2026. It was actually the second biggest investment channel right under AI and automation tooling. So CMOs, especially in B2B, care about it a lot. It's also interesting from another standpoint of like they view it for right or for wrong. They view it as a separate investment than SEO. SEO is not the. Some of them even described it as shifting traditional SEO budgets to aogo. I have different opinions on that. But it's interesting they're considering a completely different investment category to your point from Earlier, I think actually we know attribution is a black box. The way you're doing it's probably one of the best because like, one of the only ways you can even get, get actual attribution is like self select. Hey, how did you hear about us gong data? Um, like self attribution, that's actually one of the best ways we're finding to properly attribute that for clients.

Speaker B: It's a crazy world. So obviously there's a lot to talk about in terms how people are finding products and the impact of LLMs and product discovery. But the other interesting thing is, I mean you spent a bunch of years at Go Fish Digital, which is a larger SEO or marketing agency, right? So how many people work there?

Speaker A: When we were about, roughly, uh, roughly like 80 to 100 people were there in the SEO division of Go Fish Digital when I was there.

Speaker B: Okay, cool. And so now, and this is such an interesting thing, so, uh, you left Go Fish Digital. Now you have your, your own company focused on AEO and SEO and it's called Nective. And so you're building this thing from scratch. And this is one of the most interesting times ever to be able to build something from scratch. And it sounds like what you were saying earlier is that you're just building a lot of workflow, so you're not defaulting to let me hire someone to do that because that's, you know, how things used to be. It sounds like you're first asking, can I build a tool that will do that thing 100%?

Speaker A: And like I'm lucky enough to have a very technical co founder, my co founder, Jason Melman, he's a full stack developer. Like he came in even before we started. He came in with a site called seoworkflows.com that's basically content engineering workflows that he had built from the past two or three years. So we're coming in with that technology stack already. So yeah, we're coming and we're oftentimes, especially for redundant tools, we're looking at like, hey, how do we build that? Right? Like, how do we build something that briefs? How do we build something that like looks at a search, like looks at a particular Google search result, uh, goes through the top 10 pages, right? Gives us competitive insights, intel or something to create the brief, whatever. We're looking at that first. But so we can, like really, so we can help be more efficient and help our team. But yeah, it's, it's an interesting time because we have the capabilities to build those tools. So like Oftentimes our first thought is how do we build instead of how do we hire?

Speaker B: It's very interesting because again when you, when you really master a field and you really understand that like you said, you, you have these workflows, right? If you're going to go diagnose a company and their, and their AEO or SEO strategy, you know, you probably have your, you know, three to five things that you do right away. The, you know, the signals that you look at and eventually you hire people and then you try to teach them to do the same things and so they can now repeat it. You're the expert, uh, the firm is based on your knowledge and then you bring people and teach them. But now it seems like your first action is well, let me teach the agents, let me actually get my common workflows to be done by these agents and these tools that we're building. And then yes, if we hire people then they can just use those things that we've built. And so yeah, uh, it's very interesting. And again I think because you guys have started now in this moment in time, you're probably better positioned to build something than if you started this, uh, even just two years ago.

Speaker A: It's an interesting time to build. But one of the interesting things that me and my co founder were just talking about yesterday, I was like, yes, we have the tools and yes we have this build first approach. One of the things I think we're still thinking through is do we still. It's like we'd like people to know how to do it without the automation so they can, you know, be complete experts on a process, right? Not having to do it without the automations, but knowing the process, right? Knowing how to break it down to clients, knowing how to do it in case something breaks to do it themselves. Now one of the questions is, is like how much do we teach? How much do we let people lean on the automations versus you know, having them learn the non automated workflow, uh, doing it manually, uh, you know, becoming somewhat familiar with that before the automation. So it's something we haven't even completely figured out but like also something we like. You know, we're thinking about where it's like we don't want the team to be weak and 100% reliant on automation. When do you met? When you make someone master a skill first and then use the automation to augment that afterward. It's also I think an interesting question for us and probably a lot of other businesses too.

Speaker B: Super interesting. So I guess I Guess maybe we can jump into the demo. So what are we going to see today?

Speaker A: So we're gonna see, yeah, a few different things. Uh, the first one I'm gonna show you is basically how to use the Ahrefs MCP. Ahrefs is a data platform for SEOs. It has a lot of good data around like traffic links, content strategies. It's got all this data in one place. We're gonna be able to tap into the MCP to basically use conversational language to get the data instead of having to manually do it ourselves. And that's kind of one of the powers of like MCPS is a, kind of unlocks that power. So this is the AHREFS platform. This would be the data platform where it's like you can see like uh, you know, normally with an SEO doing a task, you go in and there's all these different reports and you get a lot of good stuff in here. Backlinks, organic traffic, top pages, competitive reports. But uh, the brilliant part of an MCP is we can basically have AI unlock all this data for us and use conversation to do that. And that is unlocked via what's called an mcp. Ahrefs have one and it's actually incredibly simple to set up. AHREFS haves one where you could go into.

Speaker B: And Chris, do you find that the MCP that AHREFS has, is it like super comprehensive and it can do all the things. I'm just curious from your perspective, has it changed your behavior in that you don't log into AHREFS as much or do you still for some things and not for other things?

Speaker A: That's a great question. So I def, I use uh, this especially for doing like more comprehensive strategies. If I need, I will log in if I need a quick data point, maybe a single unified report. I'm actually less inclined to log in if I need a lot of data at once or I need to do multi competitor comparisons. That's where it becomes a lot more powerful. And it, this MCP basically gives you access to most of the reporting within ahrefs. So it's not limited where it's like, oh, you get a couple reports, you get most of the SEO data you need like via this mcp.

Speaker B: Okay, very good.

Speaker A: And this is. So this would be the help documentation and like I, I prefer Claude is kind of like my go to. I think it's the best. It's. And it's, I think it's the best at data analysis and something I also talk to a lot of people about is like if you're trying to evaluate someone who's good with AI, it's like they're kind of picky about the AI they use for different tasks. Like I use chat GPD for a lot of like knowledge based tasks, but then for like data insights, MCB connections. I much prefer Claw because it's um, it just, it's a little better at that. You get a lot better visuals, it's faster. So that's, that's the connection I'll use today. And setting it up is actually very, very simple. You'll go ahead and start a chat right? And then what you will do is you'll go in and then you actually go into kind of your settings and then what you will do is you go into your connectors and then I already have mine configured but you'll go in, you'll go into browse connectors and you'll add a custom one. And then what you'll do is basically you'll go in and you will just copy paste this, whatever is in the uh, URL that's in the AHREFSMCP directly into here and then or into your server URL and then you'll name it, right? So name it ahrefsmcp and then you'll add it. So I've already connected mine so you don't have to do that. And then once you go to like an individual conversation then you'll be able to actually go in and start using it. So here you'll be able to go and say okay, I wanna go to my individual connectors. You'll go in, make sure AHREFS is connected and you want to say hey, I'm Docusign, who are my top search competitors? You can say use the AHREFS MCP and then it will actually go and then connect via the MCP in order to start to collect that data for you. And I don't like kind of browse through a lot of times you're like ask for permissions and all of that. And then you can actually see like here is starting to actually go and request make those requests to what's called the organic competitors report. And now I'm starting to pull in data directly ah, into Claude via the mcp.

Speaker B: Hey everyone, just a quick pause on today's episode to tell you about my day job. In addition to this new way, I'm um, the CEO of a company called Fellow AI and Fellow is an AI meeting assistant. It joins all your meetings, it summarizes them, tracks the action items and the decision and does that better than any other tool that you've seen. We've spent a ton of time making sure that the meeting notes and summaries and action items that come out of Fellow are the most accurate, the most precise. It beats any human. You have to try it. But in addition to that, what makes Fellow different is that it is the first AI notetaker built from the ground up with security and privacy in mind. This means that you can use it for all your meetings. Not just the customer facing ones, but also the sensitive ones. Things like one on ones and executive team meetings and those QBRs and everything in between. It's got really good judgment. So for example, if you start a meeting and you're talking about some social stuff that you don't really want on the record, that's going to get emailed to everyone afterwards. Velo just knows it just doesn't include those things. Or say you have something that you talked about and later on you're realize, oh man, that shouldn't have been there. Makes it really easy. You can go back to the meeting, select that part, delete it, and then it's gone from the record. It connects to all of the other tools you use in the organization, whether that's Slack or Asana or HubSpot or Salesforce or Linear or Jira or Confluence. Whatever it is, Fellow integrates with all those things. I think the best part is that Fellow also acts as an AI Chief of staff because it sits on all the meetings and the conference conversations that you have access to. You can ask it really cool questions such as what are the biggest opportunities in my company? What are the bottlenecks in engineering? And Fellow just pieces together information, sees trends, and it can answer those sorts of questions. It can even do things like hey, based on all of the one on ones that I've had with this particular person, can you create them a performance review and it can do things like that too. And the sky's really what I really wanted you to do is have the opportunity to try out Fellow. Check it out and we're making a special offer available to all our listeners. So just go to Fellow AI this new way to try Fellow. There's a discount code in there for you if you decide to continue with it. Either way, I would love for you to try it and let me know what you think. And with that said, let's go back to the episode. It's interesting and I see that you're using this is February 13, 2026, when we're recording This I see you're using opus, uh 4.6. Is that now your go to in terms of model?

Speaker A: Yes. For M for data analysis. M8 like for data analysis this like Google Analytics. The AHREFS MCP is certainly. I've tested different models. The ChatGPT interface and um. Well I think we're on uh, 5.1, 5.2 now with ChatGPT and just slower. I don't find the data quality as accurate. And as I'll kind of like demonstrate like clog and give you some like really nice visualizations like directly in platform like visualizations where if I fine tune them enough like I feel comfortable sharing them in a client presentation or a pitch to or uh like talking to the C suite about like data we found. So Claude is definitely the preferred because it just, it just its responsiveness is much faster, the data quality is better and you get like that visual like all in one. Nice in one place.

Speaker B: Amazing. So it looks like it got the results.

Speaker A: Yep. So here it actually will actually go and say here it's like the top search competitors, right. And like here it's like oh, you know, Adobe Panda, Dropbox, Google. So here it's actually saying it'll give us just some basic information. I actually went ahead and ran this ahead of time just to get. Just because Claude can take a little bit right. To um. But I was able to do kind of like multiple different reports. One of the most powerful parts of MCPS isn't just like hey, find this data point for me. Like at that point you might as well just log into the platform itself and find the information. Where I feel like it gets really powerful is when you start giving it multiple competitors multiple data points that it needs to bring and blend together or it has to do some data analysis that you don't want to do like in Excel or something. So this is one of my favorite ones. Right. So I might say hey, or DocuSign. Right. I'm working on their organic strategy. I'm going to give you the biggest competitors. Like they've come to me, they've told me this is who we care about. Right. I'm going to give you four different competitors. I want you to go to the AHREFS MCP and then use that top Pages report to prioritize it by traffic and figure out like what their or acquisition strategies are. It's like a higher level concept. Right. Like I'm basically saying I want you to go to four different sites and break down what their content strategies are and then um, it Might take two to three minutes for it. But, like, you can see it gets back like a pretty comprehensive report where, like, it comes back and tells me, here's all the competitors you analyze. Here's like the category leaders like Panda Doc. They're doing like how to content. Oh, they're doing a template library. That's a good content strategy if you're DocuSign. Right? Okay, sign now. Here's their strategy. They're not doing how to Content, they're doing programmatic approach. Right. Um, they're doing comparison pages. And then I can get like a specific breakdown of each and every single competitor. I didn't have to go like right through hrefs, like one by one and plug them into like the URL. Instead, it literally gave me this full, complete debrief directly in the platform.

Speaker B: This is super interesting. And does this use, does this use the mcp or is it just figuring this out by just going and browsing the sites?

Speaker A: No, it's using, it's using the mcp. So, like you'll actually go and see. You can actually go and see in the results. Like, you'll actually be able to see like, okay, here's the site explorer for, you know, this competitor. Like here you can see here it did like sign. Now here it did open sign, Right. I don't know if it labels it up here, but now it's like, it's probably doing like Panda Doc. This is all directly via the mcp. It's not using, it's not going on the sites. Although you might even be able to like actually hit.

Speaker B: How would it do the content? That's the part that I'm trying to figure out. So without actually visiting this. So maybe it gets the URLs, like the top URLs to visit so that it knows which ones to go to. But how's it able to know the, the content strategy without visiting it?

Speaker A: And that's. So it's basically pulling. It's basically pulling from data that's available, like, right in ahrefs, right? So if I went back to this and I said, hey, let's go to PandaDoc.

Speaker B: Right?

Speaker A: So it's basically the AI almost kind of what we were talking about earlier. We go, okay, I'm going to go plug in pandadoc now I'm going to go to their top pages report and then I'm going to look at all of their, their top pages, their top queries, and there it's kind of like. And then through that, it's parsing Together their acquisition strategies. Right. So it's saying, oh, here's a free business plan template. Okay. Templates are part of their strategy. Oh, here's their like, here's like a how to make a signature word. They're doing like the how to content. So it's looking at this report, piecing together this information and then saying like, okay, here's Panda doc strategy but then replicating that on every single competitor I fed it, but with a basically a one shot prompt.

Speaker B: Okay, super interesting. And the, and then how is it able to figure out if someone's SEO strategy is programmatic?

Speaker A: So it's probably parsing, it's probably parsing that together basically via probably via its almost own internal knowledge of like how some of these like strategies run. So like it's probably saying like, hey, I'm seeing a lot of templates, keywords, because it's template. Because it's kind of this like formatted approach. It's a programmatic play. Right. So like these models are actually pretty good right. At knowing like what kind of SEO strategies are which. So it's good, it's good at understanding what's a local search strategy, what's a programmatic strategy, what's a commerce based strategy. So the fact it's probably reading those keywords and saying like, okay, he's talking about SEO. I'm seeing a lot of like templates to me that indicates some type of like programmatic strategy where they built like a core common template and then just kind of replicated that for different themes. Right. So that's one of the ways it knows it's in inferring that based on its knowledge of what it's finding and then probably its knowledge of like how SEO strategies work.

Speaker B: That makes sense. Yeah. I mean, super impressive. It's um, you don't, I mean Ahrefs I would say is like pretty easy to use. But uh, I mean for a lot of tools that, that aren't, I mean this is like the best way to get to use something. But I love this because this is not something that I could have done in Ahrefs without, you know, much SEO knowledge. Right. To say what is a competitor's strategy, I would have to look at the keywords like you showed and then look at the patterns and then really try and glean what that might be. Whereas the model is now helping us do this. So it goes beyond just, oh, it has access to the thing, it has access to the data and then it can think on top of it and then give you insights Based on like what someone who knew about SEO might say. So I think that part is, is super powerful for sure.

Speaker A: Yeah. And it's like a lot of times, it's like, uh, a lot of times the most value is like, hey, what seats individual competitor strategy? And then like also, what's that one snippet you wouldn't have found like otherwise, right? Like maybe if I had looked at the top 10 pages of each competitor, I would have found like these three. Right. But maybe just a little bit deeper down across some of these, like I wouldn't have found that they're targeting competitors. Right. So it's like sometimes it's that surfacing like that one to two, like key strategy pieces that you say, oh, I like might not. Like, uh, if I only review this for an hour, I might not have caught that. Like, I might have caught like, you know, 75% of this, but it was able to do it faster and more comprehensively. The other part that I really like about it is like, um, it can create like these visualizations and aggregate the data in a way that like saves me a ton of time. Like, like a big thing in SEO is like you want to take all your keywords and then like theme them and like write like, okay, we want to group all the templates keywords together and the docusign, uh, keywords or the E signature keywords together. You can have it do that for you. Like here I basically asked it to like rate me a keyword universe. So like I basically said like, hey, go in and like create a universe, theme those together. Right. And cluster them together. It did that. Created these different like keyword clusters based on the information I gave it. And then like, there's one of the reasons I like Claude was um, you know, actually you can actually get like pretty nice visualizations at the end of this. And like things like I said, I'm more comfortable sharing with like C suite level people. I might refine this one a little bit. But like based on that clustering now I've kind of, you know, in 30 minutes time not only found the keywords I needed, but figured out what are the themes, who's winning in each one and then visualize that in a way that I can really more form a better comprehensive strategy. So like, it's nice for the multi competitor piece and it's also really nice for like, hey, go and like AG go and like analyze this large data set and then aggregate all that information for me in a really quick way.

Speaker B: This is, uh, yes, it's super cool. So what is the, uh, what is the other MCP that you use?

Speaker A: So the other MCP is, uh, basically Google Analytics mcp. And Google, the Google Analytics MCP is big for really a couple reasons. Right. Um, one, for a lot of what we just talked about, where it's like you can blend kind of conversational data on top of conversation data on top of, you know, LLMs, right. But another reason is not know how much you're using it. But people, people hate Google Analytics 4.

Speaker B: Oh my God, I never learned how to use it. It's just what a disaster this GA4 is. You know, it's just like you spent years learning an interface and then they just changed absolutely everything and it's impossible, so hard to configure. I think like that's the other thing that people throw up their hands in the air and so people still don't like it.

Speaker A: A lot of people just, they made the shift like a couple years ago. People like still never really fully learned it. Right. So the beautiful part about the analytics MCP is like you can configure it and never have to go Into Google Analytics 4 again for your data, which is just a beautiful thing.

Speaker B: I'm going to set this up today. So by the way, like, this is an interesting thing, Chris. One of the things that I always wonder about GA4 is like, have we even set it up correctly? So for analytics now, we use a whole series of other tools. And so as a result, I think maybe our marketing team used it. But like, personally I use a, you know, I use heap and we have a bunch of other tools that we use. But can it tell you if you configured it right? That's probably one of my first questions.

Speaker A: It probably, it might not be able to give you. I might not trust it for, hey, are we 100% configured? It'll be able to say, hey, I see data in there and this is what the data is. I think if you configured an errant tag or something like that, it might not catch it. I'm definitely not an analytics expert, hence why I like using the M mcp. So maybe someone out there can tell me. But, um, it's going to be able to get the data, analyze the data. I don't know if I would trust to say, hey, it's tagging. Your tags are firing on every page.

Speaker B: You know, this is where the clever prompting would come in. I would say something like, I suspect that we haven't set this up correctly. Uh, what are some suspicious things that you could point to? To validate what I'm thinking 100%.

Speaker A: Right? Or you could even merge it where it's like, hey, here's all the, here's all my site data, right? Like, here's a crawl of my website, right? Here's all the data. Can you go into Google Analytics and confirm that across this data set, we're getting at least a session on every single page to ensure I have tracking set up properly. So you could probably even like merge multiple data sets to get better kind of configurations.

Speaker B: Hey everyone. Hope you're enjoying the episode. One of the common things that we hear is, hey, you all talk about all these different tools, you walk through these demos. Sometimes it's hard for me to follow along. We decided to do recently was take all the things that we talk about, put them in a weekly newsletter, we literally list all the tools, we link to them. And any demo that we walk through, we break it down step by step, put it in this newsletter, so it's super easy for you to follow along. And the other nice thing is that if there's someone on your team that you think could benefit, they're working on that subject area. They could use a little bit of AI injection into their workflow. Workflow. Send them the newsletter, send them that particular episode. We make it super easy to do that. It's free. To sign up, all you have to do is go to this new way dot com, enter your email address and you'll get this weekly email from us. Hope you enjoy it. With that said, let's go back to the episode. Love it. So what kind of things do you do with it?

Speaker A: So basically it's a little more technical to set up. Um, and I'll go ahead and, um, I'll go ahead and actually use clog. I'll go ahead and show you via clog code. Like clog code is actually my preferred, um, kind of choice to use because, um, it's a little more technical. Um, sometimes it requires a little bit of like troubleshooting even to get started. Um, and it's just, it's just fun to ask clog, like to ask Claude code, like questions and have it analyze things so you can, you can do it like anything from like really basic things. Like so, you know, here I went and said, here I went and said, okay, like what's all my traffic? What are my, um, what is my traffic data from the past 30 days, right? And then it's going to go and give me like some really basic insights.

Speaker B: Okay.

Speaker A: Across like the last 30 days. Like here's the traffic data. Like here's different, here's the date. Like here are your engagement metrics, your average session duration. But then what I think is pretty cool is like uh, beyond getting like, you know, really basic insights, you start to ask it like pretty specific questions. You can say like, okay, well great, that's good to know for that traffic data. But like I want to see, you know, we're in a, like, do we get traffic from LLMs to my site? And this is the next digital site, it says yes, you've gotten traffic from LLMs, right? And like here it is, right? Chat GPT. Here's how many sessions, here's how many sessions you got from Gemini Page still small, but it's actually going to give me like pretty nice data on like, hey, are you getting traffic from lms? It's actually saying like you have pretty strong engagement. Um, you actually have pretty strong engagement from that traffic. That's really nice. And then you can start to have a conversation with it and say, oh, well, hey you Notebook LLM. Like that's an interesting one, right? Like someone kind of like, you know, that's generally like a pretty high quality reference. Like let's say I want more articles to get referenced by other people in Notebook LLM. Like, you know, what content got cited there? And here it's, I'm talking about some of the data studies we did, right? Um, some of like the kind of like thoughts we've posted around the changing search results. So it's really cool to have these like kind of just, you can almost just act like it's your analytics analyst, right? And say, hey, get me this data. And I'm uh, just curious about the data in here. Can you kind of tell me more about that? And it will start to give you that information and you can just really have these kind of natural conversations with the MCP in order to give you those insights.

Speaker B: So this is super interesting. One thing I'm going to rewind and ask uh, you about is, so as you're doing this demo, the first demo that you did was also with an MCP used cloud web. And when you went into Google Analytics, you went into cloud code. Why, why the difference? Why couldn't you have done that in the web version?

Speaker A: That's a great question. So one is my personal reason is it's a little more, it's like a little more technical to set up. Uh, you might even have, you might. The way they set it up in the demo is they generally run it off the command line Right. So that's also. I was just figured, because they're having you run it through command line, clog code is a little bit easier, like I said, uh, just due to like the configuration, because you have to, you basically have to like, you basically have to install different Python libraries, that type of thing, like via command line, even to set it up. Clog code was really valuable to me because if I ran into a hurdle, cloud code would just debug it for me as we kind of went along.

Speaker B: Because it's on. On your computer, uh, versus, yeah, just on the web. So it's interesting. So could you actually call this MCP through the web version after it's set up, or it can only work on the desktop?

Speaker A: I believe that's a good question. I believe you can actually configure it through. You can actually configure it through the desktop app. The way to do that would actually be to set up a connector for your Google Analytics. Push your Google Analytics into BigQuery. And then from there what you can do is you can connect your Claude desktop app to BigQuery and then you can start to ask Claude questions about your Google Analytics, like via the web app, via the desktop app. I've even heard people talk about how, uh, like they'll literally use the Claude mobile voice app and they can like go and ask like Claude mobile, like any question they want about their analytics data and then we'll ping that BigQuery database, get a response back. So really powerful and like, you know, it's almost kind of having an analyst in your pocket for, you know, analytics.

Speaker B: Super interesting. So I see. So if you want to do the web version, you've got to push it into an intermediary source like BigQuery. But if you just want a direct connection, then you're going to use the desktop. So either cloud cowork or cloud code.

Speaker A: And cloud code, like I said, was helpful for debugging where it's like this. This is a little less straightforward to set up than the Ahrefs mcp. So it's helpful for kind of like, hey, this is why it's not connecting. Your oauth isn't set up correctly. Let me go fix that for you. So that's also one of the reasons I value cloud code.

Speaker B: Yeah. So, Chris, if I did something like said, okay, you know, you now have access to our Google Analytics and you have access to Ahrefs. Come up with an SEO strategy for me. How well would it do at that?

Speaker A: Well, um, and that's One of the, I think that's one of the really where it gets really, really interesting with a lot of this MCP usage, right? Like what MCP I think is, can be powerful. I think what's really going to expand marketer skill sets is like when you can blend multiple together, right? Because now you're blending data sources, um, and you're, you're basically running your MCP off two databases, right? It's like here's an example where I said like, hey, go into Google Analytics, look at my landing pages, right? And Google M Analytics mcp. Then what I want you to do is I want you to go and use the Ahrefs mcp, but look at organic traffic to a big competitor site, right? And I just chose a site that I know has a very large SEO presence and then use the Ahrefs MCP to see like what their, you know, estimated organic traffic data is. Now can you kind of give me a strategy for like gaps I should build? And then it's going to go, it's going to like look at the Google Analytics data here at your site href Site Explorer data. And then basically it's saying like, hey, I compared us against a much larger site, right? Um, but it's saying like, hey, here's like your, you know, here are some of your top pages, here's some of their top pages, right? And this basically saying like, hey, you might want to go build a pricing page. They were building a lot of tools, right? They're building like, you know, maybe an AI, like a prompt optimization like tool. They're a fan out query generator. They're also like, it also actually went and dug in and said, hey, here's the service pages they've built, right? They built a small business page, an enterprise page. You need to build those pages. And then if I was being extra curious, I go and say like, okay, like you know, Maybe, maybe the 1 and 2 aren't for me as much, but service pages, that's interesting. Like I could ask it and say dive deeper, give me like 15 different service pages I need to build. Go match that with the Google Analytics MCP to make sure I don't have one on the site. But now it's starting to use those multiple data sources in order to like build me a strategy that I could potentially use.

Speaker B: So this is super interesting and this is for everybody who is thinking about this. Probably heard the term context engineering. So the question is what context do you bring into Claude so that it can then with the right prompt be able to Give you the right answer. And again these things do not have infinite context and it is a, you have to figure out what things you want to bring in. And so that's where some of the, I guess like the art uh, you know, comes into the mix and some experience like doing this enough and learning how to work with it 100% very, very interesting. So thank you for showing uh, this, this stuff. Very, very cool demos. Uh, since we are talking about tools, one thing I did want to ask you is there's a lot of, I mean there's a lot of tools now, you know, a lot of startups that are uh, being built to you know, help focus on aeo. So what would you, what are you seeing out there? Like what are the ones that people are using the most? What are you coming across these days?

Speaker A: Yeah, so with AO specifically I think there's multiple, right. One of the biggest and it's big caveat is an imperfect science. I still think every business needs one is some type of LLM tracker. That is the big one. The big player in the market is of course profound. They probably have one of the better user interfaces out there. A lot of the client partners we talk to are using or in talk to. Profound. Another one is Athena. That's another one that's a, a little bit more data driven, a little bit better at giving people scale. So some type of LLM tracker to understand like hey, if we look at our brand across AI search like are we getting mentioned right, Because a lot more people are asking about that. And yes, it's not a perfect science but if, if your manager is asking how you're showing up in lms, the answer can't be I don't know. So there are these LLM trackers out there that can help you get that data. I think that's a really big one and going to be imperative for a lot of businesses. This is 20, 26 and beyond as well. I think I have a lot of hypotheses around kind of the future of content in our industry. I see organizations hiring less for maybe individual content roles or people creating the content. I actually see the rise of tools like N8N Air Ops, um, some of these like content engineering workflows that can, you know, potentially 10x the output of a single person by you building an entire workflow around, hey, go ingest this data from multiple sources, create me 20 different outlines. I think these kind of like N8N type of content engineering workflows. That's something I'm very, very bullish on moving forward. I, um, think that's going to be key, especially in our industry.

Speaker B: It's very interesting. Have you any views on Open Claw as it relates to what's going on, like, you know, these NA and workflows? It's very interesting. I was having this conversation just this morning which is, you know, why would you, like, what's the advantage of using something like NAN when you can just, you know, basically ask openclaw and give it like a very descriptive prompt and it can, you know, open up your browser when it needs to, go to a different site, when it needs to, you know, use your desktop when it needs to write code when it needs to, and then just solve all the same things. So it's kind of a tricky and full transparency.

Speaker A: I have not used Open and Claw. I'm on Twitter. I have seen all, I have seen all of the hype and the, um, kind of the messaging around it. To me, it's like I'm probably, I'm AI forward. Maybe I'm not that AI forward. I'm like, used to, like, close to giving up that much control. But I do think it's eye opening to see it's probably one of the first tools that like kind of showcase the world, like what is possible in the future with kind of like a fully autonomous solution. A solution that doesn't even require you to build a workflow. A solution that builds that workflow for you.

Speaker B: It's a crazy, crazy thing. I mean, one fun anecdote that I'll mention, uh, here is the. You know, someone asked openclaw to, uh, book a restaurant reservation. So, uh, it tried to use OpenTable, did not succeed because it was enlisted on OpenTable. So wrote code so that it could build itself a voice component and then it actually called the restaurant and booked it that way. So some crazy stuff happening out there.

Speaker A: That is wild. Whoa. Okay, that is, that's next level.

Speaker B: Yeah, it's, uh, it's kind of like the thing that you would expect a human to do, right? Because you tell a human, hey, book this thing. They would try OpenTable and if it's not there, they would pick up the phone. But you know, a great, you know, someone, for example, for example, with not a lot of persistence might just give up. Oh, it's not on open table. Do you want to try this other restaurant? Uh, someone with more persistence would get up and actually call the place. And that's the thing that I'm finding very interesting. It feels like we're going to this place where there's just that extra persistence, like they will knock down doors to get to the end outcome that the user is wanting. And so when I think about SEO, I now think about a world where, okay, you know, we did a lot of stuff today. We said, okay, like find our competitors, find their strategy. And I just imagine a world where like, you know, can you guys, like at uh, Nectar, for example, build this like AI SEO employee that we can hire and they can just work at our company and it's going to do these things, but then create the content briefs and then update the site and it's just going to be this ongoing thing. Maybe it'll feed into our data sources, like our sales calls and like whatever stuff we have access to, our product, uh, roadmap, you know, even the code so that it knows when we build something new and then just, you know, do, do all of this, this work and then you guys train these employees. Uh, so I don't know, some futuristic stuff, but I actually don't think we're very far from it.

Speaker A: No, I mean especially. And especially with all like the open, open call hype. It's like, it, see, it seems like we're much closer and it's like, I mean, it's interesting to me the range of people experience. I feel like there's people who are either on either side where it's like they use AI for everything or they're like allergic to it and like kind of still afraid. But it's like the change is happening so rapidly, um, that it's, it's truly a little unbelievable.

Speaker B: I think as all this stuff happens, and I'm sure you experience this too, uh, because I know you work with a lot of larger companies as well. It's just, you know, when you're in a serious environment, larger companies, private security, like, this is the stuff that really matters. And again, it's just the stuff that's top of mind. It just becomes even more top of mind as these tools start running around and connecting to whatever. So, uh, it's a brave new world for sure.

Speaker A: Absolutely. I do think they'll get more power the more data sources you can give AI access to. The. It does become more powerful.

Speaker B: Yeah. So, uh, this is awesome, Chris. Thank you so much for doing this. So for people who want to reach out, uh, you're the AEO expert. You have, uh, a new company and building it in an AI native way. How do people find you?

Speaker A: Yeah, easiest way, find me on LinkedIn. Uh, Chris, long dash marketing. I post about SEO, AI search basically five times a week. Thoughts, tricks, tips, whatever agency. Uh, name is Nective Digital. As Nective, you can find us@nectivedigital.com.

Speaker B: all right, Chris, this was amazing. Thanks so much for doing it.

Speaker A: All right, appreciate you having me, Aidan.

Speaker B: Um, and that's it for today. Thank you so much for tuning into this episode of this new wave. If you like the content, be sure to rate, review, and subscribe so you can get notified when we post the next episode. See you next time.