B (4:30)

An E commerce company, without a doubt, right? People's buying habits have completely changed. Let's just think about ourselves in a consumer experience, right? I walk into Best Buy, I check it on Amazon, I just make sure my price is right. It's a continuous process. But given that this is SEO, I wanted to stick this in, right? You're spending money on ads. SEO. A lot of work as a business to get people to come to your website. My job picks up from there. You've got people on your website, but are you actually making money off of them? Right? So conversion is huge. Shopping cart conversion is huge. But I like to say, look, if you're not finding, you're not selling. And a lot of what we use AI for is to make sure that the products, the services, the things, things that you want to sell actually appear for your clients when they're searching for something and they want something. Because in B2B, if they can't find it in their mind, you don't have it. Whether you do or not, they are onto your competitor and moving right along. And that's a huge benefit financially.

A (5:48)

Well, I, I can tell you, like, product page, SEO is incredibly important. A lot of people are just using the manufacturer, depending on what you're selling. Right. Like, we can talk about a lot of different use cases, but, you know, I look for, okay, I don't know, whatever it is, if I'm doing this, I want it to actually say that it does that in the product description to make sure I'm buying the right thing. And if it doesn't have it, even though I think it does and something else says it and it's a little bit more, even though it might even be like, very, very similar, I, I'm going to err on the side of like, okay, this says this component or whatever it is fits with that. And, and, and that falls in right with what you're saying of, well, if you're doing marketing, you got to be able to differentiate. And that product needs, when people are searching for it, to rise to the top, to be one of the choices in the selection process. You also open up the can of worms of, you know, UX and the customer journey on page, which is probably arguably the most important thing that needs to happen, which is where SEO. Right. You said SEO drops off. CRO kind of picks up, or there's a big overlap there. But when clients are typically looking for SEO or CRO, they're really saying the same thing. I want, I want a customer. I want you to put a customer together with a bow on it, and I want you to deliver that to me. And I don't care what multimodal you're doing. Like, give me new customers is essentially what I'm asking for from most people that are looking for these services, without a doubt.

B (7:27)

And a point you just made is really important. Right. You said, I wanted to say what I want it to do, or it describes exactly what I want to do. And there are a few points that are really important to that. The first is in search. Giving only one perfect answer is not as good as giving a few answers. One, exactly what they're looking for, but two or three that are similar. Right. Or that are bought with. Right. Amazon is great at this. Amazon is a great, great a lot of stuff, but it actually has a higher satisfaction score to give them one perfect and then three options. And I like them stacked on the side that are, one is cheaper, one is, you know, a different brand, one is something that always gets bought with it. Those things actually spark investigation where people will buy Will one, at a better rate, buy something and two, it raises your shopping cart value.

A (8:40)

Yeah. I mean, the cognitive load is really something that people try to cram too much information in there. Even Amazon again, Amazon's going to test it. They'll figure it out. They just move to like, here's all the choices of everything you bought, you know, and so if I'm buying a piece of technology, it's like, do you want bananas too? And I'm like, like it's too much. Right. And, and I just click next and I actually don't like the current experience. They'll figure it out through testing. But to your point, when you give me three recommendations that are tied into what I'm buying and this is bought with that and it's something I can consider, I usually will click on that. I'll usually look at that. And it's not too much to process. Right. And on the website, a lot of what we're working on right now on a separate project is, okay, what is that customer journey? What are the steps that they're going through to help make combined decision? And what happens on most sites and why the bounce rate so high is you have these massive menus, okay, that give it so many options that you don't know where you're taking them. Like if you're trying to get them to buy something, all these other things are just taking them away from that. And many times they're going to get distracted, they're going to leave the website, they're never going to come back. And that's why you have a horrible.

B (10:02)

Bounce rate while you're right. And then let me come back to, because I know you want to, you want to talk about some of the technical and AI things we do. Right. So one of the things you also said is does it say it? Does it?

A (10:18)

Yes.

B (10:18)

Well, that is dang important. You're right. And we have some tools that we utilize to make sure it gets said. Right. And it's. And it's more it and B2B is catching up. But it's not there yet, right? It. It isn't, but it has to be. The expectation of people is that there's no difference between if I want to buy something personally or for business. Now one of the ways that we do that is we use AI and some private LLMs that are industry specific. Right. To enrich the product information. Right. And we actually can do that in two ways. Right. One is just what are the descriptions, what are the things that tie together? What are the matching Products. What are those descriptions, what material and partner. It gets large amounts of data, but it has to say what you're looking for. The second thing we use it for is voice with AI today in for example, one of the products we might use is called the Product Information management system or B2B. Right. Is we can not only take a sliver of product description and make it useful to marketing and SEO, but we can also change the voice. I can take that same thing and tell it to describe this to a 5 year old, describe this to a buying agent, describe this to an engineer and describe this to call it the general public, which might be good for SEO or whatever or a fifth one. Right. Generating specific keywords. We can, we can use the Persona driven side and the description side to create some inquiries, incredibly rich data.

A (12:23)

So to, to kind of unpack this a little bit more. A lot of clients that, that listen or listeners are B2B companies and I do a lot of things in B2B selling ERP system. Right. So ERP system is, is what everybody's familiar with on maybe inventory management, product management, whatever. PIM sits on top of that. And it has kind of some machine learning components which were used before LLMs with like you had to clean the data up, you had to label the data and then you could use these LLMs to get multiple product descriptions to extend the category or the definition around it and it could speak to more types of people. And so if you just have the ERP system, you're going to get really basic data, you're going to get just really basic labels and you want to expand that reach and you want to expand understanding of how people are searching and what they're looking for. And you add that AI or intelligence layer to that and now there's more chances to get a sale because you're answering the question better. And it also is understanding more about what you're looking for and who it's trying to reach and it gives you a better chance to surface the right products for them.

B (13:55)

Absolutely. And you know, what I do never sounds as good as the stuff you do, Matt. I mean you get all passionate and I'm sitting here in the background doing all the data work and trying to put this stuff together. But you're exactly right. You know, we've been doing this for a few years, several number of years, right. Where it started out as machine learning, the grandfather of AI. Right. But being able to, going through. And we started with cleansing data, ordering data, creating more data and some structures it has now Moved into exactly what you've described, right. We have full on AI models and we use both public models, right, so that it's understandable they're well used. But we also have created private models and they're important for a couple of reasons. One, a number of B2B companies have you know, data they'd rather not have out publicly. Right. We have a company right now in common, right, that's in pharmaceutical manufacturing and they have, you know, secrets that they don't want out there. So we've created a LLM specifically around their chemistry, around the things that they do and we can search it and serve up information without revealing the secrets yet be able to pull in all of the information you're talking about and do all the things that we do to give someone the right answer. Because that's actually, you know what's great is it's just like today how many people, you know, I actually just want an answer from Google. I don't want five websites to go look at and what has happened and you talk about this Matt, right? I want an answer. Just give me the freaking. Ah, that's the answer I'm looking for. Beautiful. Move on. I don't need to go visit your website.

A (15:57)

And so how for everyone listening how what Rob and I does kind of matches is I'm focused on the public facing view of surfacing in those public facing LLMs. Rob's maybe taken some of those public surfacing or public facing LLMs, been able to put it on a separate server, MPC server, a data lake, building a data mark, labeling the data and then you can recall that information that's private and then it serves up inside a portal on the back end. So it's taking the, the front facing marketing piece and now operationalizing it from an E commerce piece. And then there's an even greater piece of an expansion of the business leverage or the, the AI applied leverage that you can get to apply it to other pieces in the business. We're just talking about specifically the product catalog or you know, informational search of a proprietary library or proprietary database. And it's fine tuned from a, you know, a chatbot standpoint to give you the answer. And again that next expansion for the like VPS innovation that are listening you can apply that to all your data governance to be able to recall data, to get trends. And how this affects what we're doing on this shared project is you can see the trends of what people are buying, how often the time they need to refill and buy more and you can suggest these things to them to, to help them stay on top and to pull forward maybe some of that demand as well as to just help make their life easier to keep stuff in stock, which becomes really, really helpful from a projection standpoint, from a data usage standpoint, from a customer standpoint. These things are kind of keeping you out of the ditch. So there's all these advantages right around purchasing orders and to B2B companies that are listening to be able to implement this on a supply chain side. That's what we're getting a lot of interest in, Rob, is a lot of supply chain logistic companies are seeing the use for like AI layer to help project a lot of these coordination and delivery schedules and fallout rates and say oil and gas. And so it's just incredible what it's able to do.

B (18:31)

It is, but I'm going to back it down a tier because B2B is behind. Right. So you know what, if you're a medium sized company and you're selling through multiple channels, you're selling to some distributors, you may be selling through Amazon or whatever. Right.

A (18:49)

Your Shopify store, TikTok store and your Shopify store and.

B (18:56)

Right, yeah. One of the key problems to solve for these companies is inventory.

A (19:01)

Yes.

B (19:02)

How do I know how much inventory I need to sell on Amazon versus my Shopify versus what if I have more than one warehouse? So what they wind up doing is actually a very old fashioned solution. They put in safety stock, which is extremely important. And if I allocate safety stock incorrectly to one channel and the other channel sells out, I've got a bunch of stocks stranded over here that I could have sold. Right. So using AI and using, you know, good connectivity, good data, it can actually manage all the channels at one time. And we do that in pim. And the reason we do that is we're able to work directly with the erp, apply some AI, look at the channels, manage and even be predictive in the selling. Now Amazon can be helpful with that, but I know a lot of customers that are doing safety stock across all of their channels and you don't need to. And it's expensive.

A (20:05)

Well, one of the things that you and I were talking about before this call to kind of build on that concept was, you know, if you're a supplier, right. If you're a supplier, you're typically, you know, you're, you're either repackaging or reselling other people's stuff or if you're buying something and you're configuring something or Whatever. That ERP system's not going to do a really good job of recognizing all these different product orders and POs and you know, product labels. And if you're trying to resell that as your own product, right. You're, you're, you're, you're, you're, you have a markup or you're, you're arbitraging what's going on and you're buying that thing from a bunch of different sources. Okay. They're going to have their own PO numbers and product label numbers. And you got to be able to unify that to your point on the product supply side and then present your own product label number. You can't do that really well. It's a very manual process with the ERP system and a lot of people are band aiding and jerry rigging that up. And I just wanted to flesh that out a little bit more because that's where the PIM and the dam come in is you can run all those APIs and into that AI layer, it can figure it out and tell you what's at where, what store, what it is. And it streamlines that product so you can have just in time delivery where you're not carrying all that overhead. And I think that that's super powerful because I know that there's people listening right now that they're using those ERPs and they're like, there's got to be a better way to do this. And they're trying to, you know, band aid up a bunch of different solutions.

B (21:55)

Sure. Well, ERP was of course primarily set up as a financial system. Right. And it's really good at will handle your finances, it's designed to plan your resources. But in the end, right. And you threw a lot of information out there, Matt. But in the end, right, what are we trying to do? We're trying to sell product and that may come in many flavors. It could come from multiple vendors. You may even have a white label product that you do of your own. You may have the opportunity if you're a distributor, you probably sell multiple brands that do the same thing. Relating all of that is hard. It's a lot of data. PIM can make that so much easier. You can sit there and do it by hand in an ERP and start matching stuff up. Or you can ingest it, connect it and use AI to begin to put all these things together and then deliver it to your AI driven search. It, it becomes a whole lot easier and it, it gives you a lot of features that people have not been able to do before. I'll give you an example. From one plumbing client. We were able to take all of that information, create all the relationships between Delta, Kohler, whatever the brands were their own white label brand and off brand and a lot of data. And in the end we were able to surface one exactly what the custom. If you put In Kohler valve 1, 2, 3, you will get a Kohler valve 1, 2, three. But you will also get their white label exact product that matches it, which they make more money off of. It's a cheaper product, but we're maximizing their profit. And then we'll give you some other options. This data is truly valuable.

A (23:53)

Okay, so I want to break one thing apart and dig in a little bit more of what, what you just said. So, okay, so we have like our website and you know there's an ecosystem associated with that. We have it connected to an ERP system. Now we're talking about a PIM or a DAM or a hybrid of that on pulling in data and API. Is what you're talking about now adding a AI search layer on top of that or is that still part of PIM and Dan, and like what are the differences between plugging something like that in to give you even more granular search, to give people the absolute right answer of what they're looking for? Because that's some more horsepower.

B (24:37)

It is. And it actually requires both.

A (24:41)

Okay. I just wanted to make sure.

B (24:43)

We may get to one as we begin to be able to use more and more unstructured data to do these things. But we have to just like any LLM, right, we have to have the descriptors in there for the AI to find what's common. Right. If all I do is put in screw and nail. Right. They're not going to be able to connect it as hardware. So you know, it doesn't, it doesn't always work that way. Now what we do is we take all of that data, we do some structure inside of the pim and a PIM is the product. The DAM is Media Digital Assets. That's where that comes from. And what we're able to do is enhance that data inside of the pim, give it all the terms that the AI will need to search and look for. And then when we serve that up, the AI driven search is able to just go to town. I've got your materials, your size, your product, your everything that goes into that has been enriched to allow the full search capabilities across everything. So it's two steps right now.

A (25:55)

Yeah. So let's just. I. There's a lot of people out there, right. And I just. The term information's the new oil. Right. Has been talked about for a long time and you had to do, you had to have a data analyst team. You had to spend months like to slow down like the data labeling like you're building like there's a ton of people listening that have data marts and they have tons of data and they haven't done anything with it. I would love to hear from you. What are some different use cases if they start to implement PIM dam some AI driven search on. Let's just open up the minds of what are some of the things that they could do with this data. I'd love you to just rattle off a few high value use cases where you could make more money doing these sort of things. You can leverage it.

B (26:48)

Yeah. When you've got data buried across wherever it is, Right. Being able to relate data and serve data are the two beginnings of better revenue and total cost of ownership. Right. And the way you can do that is by beginning to tie that information to what's actually happening on the website. You can serve it and you know and actually test out what appetite is there for this product. Data and information and products. You can use it to make your products more enticing, more descriptive, provide more information to different Personas and buyer groups. And then let's not forget, right. Once we've invested in all this data, Long tail marketing and long tail find is really, really important, Right. Why does your website care if you know so many clients, right. They have the top 20% of their volume on the website. Not a hundred percent. Eighty percent is buried in catalogs or a salesperson's mind. So what happens? Salesperson retires and a lot of guys are beginning to retire in in these manufacturing and distribution businesses and you've lost it. The E commerce and search does not care. Put all million up and the one time that somebody buys it, you are way way ahead. It also helps in your search. So in the end just from a few ideas, right. You're getting more people to your website, you're getting more sales off your website and then you're also going to be able to create more data to understand your customer better. What's the customer journey on these kinds of things? Did we miss something that suddenly turns out to be extremely important right now in engineering or in, in a buyer's group, the only way you can find out this data is let's expose it and run some reports. Let's find out. There's so many opportunities that, that you can do with it and I'll give you a real life example. Right. So we had a tubing company, right? Very, very boring industry, right. They might say and yet it's critical, right? They sell a lot of tubes. They, they're all different sizes, right. And what they realized is there was a us that by just putting up a few things they don't normally. One, their CAD drawings. CAD drawings are typically filed away somewhere. Putting up their CAD drawings is a true blueprint of what is going on. The real information. And then secondly using AI to make their detailed product PDF sheets just readable. Traffic to the website went up 12%. 12. Just, just making all this exposed, right? Went up 12% and the buying went up 3% 3% pure revenue. More clients, more revenue. Nicely just exposing the data which the. It does not care, it does not care how many things I stuff in it. It doesn't care how many calls you make from was you know a one time effort create a process and now I'm making more money.

A (30:28)

You know this is the hard thing because AI can be applied to almost every aspect of the business to help improve it in some way. If we drill down to well AI learnings and we're talking about like CRO conversion rate optimization like understanding that customer journey because the buyer behaviors changed and people want more of that proof. You, you started, I started thinking about eat, expertise, authority, trust and experience. That's what you were doing is you were proving that out more. So people said oh this is what I'm going to get. This is how it's going to do. It's explained. The LLMs understand it, the people understand it. It's a win win because that process is happening. A lot of people are, are like I'm going to save all that until I get them on the phone. But now they're missing the deal because they're not even in the top three choices or whatever the selection is because they're already out of the running because someone's deselected and unraised their hand from using them. And so I mean you look at these bounce rates, you look at these click through rates, they're minuscule. You, you gotta get that number up. And when they get to your website you got to understand what content are they missing. Where did they get stuck? Do they get card abandonment? Right. That's a huge, huge issue. Why do they put it in there? What, what's going on with that? I would love to hear a little Bit more about how you look at conversion rate optimization, heat mapping, and how you're starting to make some of those decisions. Because yeah, SEO gets them there. There's a conversation that has to happen. And really, you know, 50% of that informational content is no longer on the website. So you gotta drill down on middle of the funnel and bottom the funnel content. Because if someone's came to your website, right. They gone past the AI overviews or the LLMs have recommended them or whatever it is, now you're on your website if you don't get some kind of information. And we got, you know, we got all the pixels going away, right. And so you gotta capture their information and you've got to get them to the next step and, and you gotta push them through that funnel. And the only way you're gonna be able to do that is with data. And that's the big differentiator today that you can, you can still analyze is once they come to your website like, you know, they're, they're in your territory, right?

B (32:53)

Absolutely. And it can be a little more difficult in the B2B space. So there are, there are a few things that, that we do. Right. One, don't just provide your, your telephone number. That's the way to interact with you. It sounds funny, but there are tons of clients we start with where call my sales people and we'll get going. Well, most people don't want to talk to your salesperson until they're 100 ready.

A (33:21)

Yes.

B (33:22)

Not a good strategy. So what, what, what do we do? First of all, we want to be able to utilize some, some methods. Right? That in. And, and they're consumer methods, right? We, we learned them and we know these from, from websites we interact with all the time. How would you like to. Why don't you just save a few favorite parts so that you can come back and look at it later? No problem. Give me your email address and I'll save them for you. Right. These are standard things. But you know what, why don't you join our loyalty program and I'll give you points toward everything you buy and if you give me my, your email and phone number right now, I'll stuff you with a 100 points just for signing up. Right. And as you go. So that's on the very early side.

A (34:11)

Quizzes and calculators. I love quizzes and tagliners and engaging them to. But, but we got to have your email to be able to give you the answer, right?

B (34:21)

You do, right. So you know, what's your Address. I'll, I'll calculate out your. Your shipping address. Do you want. You know we use gated content, right? Yeah, I have really valuable content. Just give me your email address. Everything you can do to get something from the client is really important, but not every client does. So what happens now? Let's say you do have a shopping cart. You know that it is the most effective way for reordering. You know that it's the, you know the way sometimes people want to try out a small buy before they go call your, your salespeople and give you a big purchase order. They just want to order one, not a thousand or a million, Right? Just one. Let me buy one. Let me see what it looks like. That happens all the time. So what happens? You get into the shopping cart and then they stop. It's not high on their priority list. It's very high on your priority list. Right. So what do you try to do? First of all? Right, we're trying to get their information up front. Hey, create a shopping cart. Okay, to create a shopping cart. Let's create a quick account. Where am I sending it? What's your name? What's the company? Right, it. And we create all that. You've got it sitting here in your shopping cart. And now I've stopped. Well, what. Here's two things that, that surprised me now. Yeah, you send emails. Of course you do. Hey, you stopped something in the shopping cart. What I was very surprised by is we encountered a marketing company and they convert that and they send automatic postcards.

A (36:07)

I love that. I was like, just direct. Ship it. Yeah, just a direct.

B (36:12)

Here's a postcard. And by the way, I'll give you 10%, 5%, 20%. They actually look at what's in the cart. Can I ship them a 10% coupon?

A (36:23)

And that's, that's so that the drop shipping to set something like that up. I actually had a conversation with a client about that last week is on. Let's just put a tag in the CRM if you want to drop. Ship a postcard to them that looks handwritten and you can have a couple different options. You could even put, you know, like a, a tier up from that. Send them cookies, whatever. And, and the conversion rate's going to be so much higher because you're building reciprocity and you're hitting them offline because there's so much noise online. People get distracted, you know, and oftentimes.

B (36:57)

Well, sometimes they don't use the right email address. I don't know why, but sometimes they don't. Right. So there, there are methods around it, particularly on like gated content. If you're selling information as your product, right. Can you can insist on a good email because that's how you're sending access to the information. But if it's a low value, you know, sign up to get something, you know, often, you know, we'll see, you know, junk12345gmail.com as the thing and therefore is that really working? Whereas in the shopping cart, if they want it, they will give you the right address.

A (37:41)

Absolutely. Yeah. I think, I think adding the text automation to that, like, I mean, I'm starting to get a ton of spam text, but I still need to delete them and clean out my text messages.

B (37:52)

Absolutely.

A (37:53)

But text has a whatever, 98.9 or 99.8% open rate still. Email people are just death by email at this point. Like, we're having to set up Rob with a lot of our clients, Slack chats, because they're not getting our emails because they're overloaded with emails. They're working on whatever they want to work on. So here's a specific form of communication to talk to. Like, I mean, emails getting tougher and tougher. I mean, now you can use AI to of course, clean out your emails and, you know, sort by the different categories you're using it for. But email, email's tough these days. It's not always the most reliable. But if they get it in the mail. Right. They're going to pick it up and see it. So I love that example. That's a great example.

B (38:40)

Yeah. Everyone looks at their mail, even the junk mail, you still look at it. Is it junk?

A (38:47)

Yeah, you gotta, you gotta, you gotta define it, you gotta categorize it.

B (38:49)

Yeah, you gotta define what is it. Right. I, I think your point about email is, is spot on. Right. And that is, it's so full, it's so completely overused. I mean, I watch my, my, the number, the red number grow and then sometimes I just go through, okay, anything older than this, gone. Right?

A (39:16)

Yeah.

B (39:17)

So it's tough to, to get through the clutter.

A (39:23)

So let's bring this back and kind of bring it back to, to marketing and close it out. I think a lot of people are hearing, okay, AI is going to affect business. Right. It's going to have a positive impact. Where can I see that impact? How can I apply that? I think we went through a number of steps on how to do that. I think that PIM and dam, if you have an ERP system. You should be really critically looking at that. How can I get AI to apply to different categories? And that could branch out in a lot of different ways. CRO and SEO are connected, okay. I think they're attached at the, at the hip. A lot of times when people want one service or another, they really want the same thing because they want to just open up that funnel and, and tighten that phone and bring that together and unify that data. And so you know, if you're using LLMs to make the website better for a public facing, right. So you got, you got behind the, behind the wall and they set up an account kind of on, on that back end when they log in. But, but a lot of the look and feel is that first time customer interaction, getting them into the right customer journey in the right channel. You got to have that information publicly facing the LLM's got to be able to read it. You got to have a site map, you got to have a organized and logical categorization of your product category. You got to have good descriptions to speak to different people. One of the things we didn't talk about is, you know I like to use like this profile because I did it many times. But these different type of people want that information like you said, given to them, right? Or some people might want to dig more and get that research or some people might want to video or audio or voice hear it, right? I want to just spoon fed to me, right? Some people want to submit email and have you contact them. Some people want to sign up for a calendar, some people want to download a form and talk to somebody. Somebody people want to call a 1, 800 number. And if you're not addressing all these different modalities, you are missing customers, you are missing distribution channels on marketing. You need to be able to splinter this information and be able to push it out multiple ways to bring everything back to your main source hub. And you know something that we probably don't have time to go into too much, but hopefully it tees it up is we need to understand your company as an entity. We need to define that, we need to define your key players of who the authors are. All these things are the information architecture, which is really what you specialize in and kind of how we work together is mapping that out and mapping the site architecture out. And that's how you and I are working together really well on some of these projects because you need different voices at the table, different experts giving different opinions of looking at it differently from design from the back End from the marketing, from you know, how the LLMs are picking it up and it's all well, marketing and positioning and well information architecture. That's what Google's trying to do is understand that's what all these LLMs are trying to do. They're trying to figure out the information, trying to organize it and layer in a way that you can recall that information really easily. We're talking about like information recall is, is really I think the, the big or data recall. There's a whole industry around that and that's what we're talking about whether it's on the website or before the website, on the website or in the website. And I think that that gets underserved sometime and these are complex issues that you need to unify a lot of data. And I think just the execution of companies is they've spent a bunch of money on one or two different things and they just are 85% of the way there and they just need someone rob like you to help connect that data together and then the circuit starts running and it's really, really quite powerful. Or someone like you, you know, and, and I, I just think that this is where things are getting missed. Like they've, they've built the data lakes, they've labeled a lot of the data and it's just sitting there and they're not getting that the, the, the insights they're looking for, they haven't gone the rest of the way. And that last 10 or 15% is the hardest way to do it. And once you do that, that circuit gets completed and now you get all these benefits of the, you know, the AI, machine learning, LLMs, whatever you want to call it.

B (44:21)

I agree. And the thing is, look, we've talked about removing silos forever, right?

A (44:27)

Oh my gosh. Yeah.

B (44:28)

But leaving your information internal and not utilizing it, right is, is another silo. We have to break down the data of the company to the consumer. One of the things you talk about quite a bit is, you know, putting a stake in the future marketing. Right? The LLMs will rule all search. They will, they will be giving an answer, you know, and, and so many companies have developed out so much intellectual property and they have so much that just isn't displayed. Part of this is stick the flag in the ground for the future because what we're doing right now lays the groundwork for years of future success. Because the LLMs are, are looking now. They're looking for, and you know this better than I do, but they're looking for authority. They're looking for depth of content right there that we're no longer looking at high level marketing world. They want you to demonstrate deep knowledge and being able to expose some of the things I talked about, whether it's an engineering drawing to, to PDF information and getting it in such a way that you're properly staking your flag and saying, look, we know tubing better than anyone else. It's important, right? You think it's not and that there's lots of competition, but the people who stake, who get there first and show the depth of competency have a huge, huge advantage.

A (46:07)

That is the unknown secret that I don't think people are aware of that the training data in these LLMs, they've just opened up like the world wide web from their kind of training data that they're built on. And the LLMs are still trying to decide what gets saved in their long term data in the training data sets that they continue to reference. And the more and more that you get recalled and referenced, the harder and harder it is going to be to dislodge you as that authority or that expert in the LLM data set. Because every recall does that. With Google, you know, there's a little bit more play. These LLMs are going to solidify and in 18 months it is going to be extremely hard to do that. And the people that are planting that flag in the ground now and building those libraries and those data sets and becoming the go to recall expert for these things are going to win and people are going to be spending a lot more in the future to just get a piece of that. Because this is, this is the time that people need to like get with it and take action. I just did an article on this kind of like the LLM land grab and I think it is absolutely so true. And in some of the presentations, you know, I mean, just ask, ask any lm, they'll tell you the same thing. Like this is where we're at today and this is a monumental shift on how business is done and where it's going. And I'm seeing the jump rates of usage. To your point, Google was the librarian, okay? And you would go to Google and they would give you 10 blue links. Here's where you go to go research it. Now people just want that answer, Give me that answer and you go do the research, synthesize the data and give it to me. As people start to use that, they don't go backwards, okay? They, they only move forward. And we're seeing, you know, huge amounts of increase in this, and as people get more and more comfortable with this, they're, they're using it more and more often. And, and, and this is the future. It is not a fad. And, and any business that wants to be forward thinking, needs to, needs, needs to start jumping on this. And one of the things you're talking about is that push to becoming an AI first company, which, there's a couple steps to make that jump. Amazon didn't do it overnight. There's a sequence of steps that you have to make and I feel like.

B (48:53)

A lot of, oh, I like that. I, I gotta trademark that, Matt. AI First. An AI first company. I love it. But I, but you're right. And here's the thing that unfortunately people will think right, oh, AI makes it so easy so fast. 15 months from now I can still get on the, in on that 18 month land grab. Unfortunately, the answer is no, you cannot wait the amount of time, right? Part of it is the amount of time you're sitting in the next 18 months. 18 months is a flash. It will go fast. And as you're thinking about 2026, it's better to start earlier than later. If you're going, if you're going to be serious about owning this space, you need to start right away because it takes time to set it up properly, it takes time for it to be ingested properly and it will take time for these LLMs to decide, right, that your data is what they really want to quote in the future.

A (50:03)

And you got to get your IT team on board. You need to get, you got to get it and security are going to be, you know, they, they need to be rowing in the same direction because the bigger your company is, the more time it's going to be taking to get everybody on board with this, to make those changes, to get those approvals. And what you're talking about is you need to be showing up now, okay? Because every time that somebody else shows up, they're getting their moats getting bigger and bigger and bigger and bigger. And if you're at a company that is going to take a quarter or two to get this implemented or approved, you got to start pushing on this now, so, so you even have a shot at this. But the nimble companies where, where every, everybody's on board and is roan in that same direction and understands this and has this education, that's why I'm getting called in for a lot of talks is to, to, to get everybody on board with this, to understand what's happening, to know that we have to take action now. Like the next couple quarters are really, really critical and I, I think that the gaps are going to really widen between the people that get it and do it. I, I have on the opposite end of the spectrum, Rob, like one client that it's kind of pushing uphill. This was about six to nine months ago. They are owned by another company that's owned by another company. So that you got all these approvals going up. They got purchased and their stance is we don't understand AI we want and content creation and SEO. These, these are the marketing sales. Now HR is about to be affected. Like these are the things that had disruption. First they said no content. Like we want a hundred percent, zero AI content. Okay. And they were pushing back content. We were sending them when we actually had a subject matter expert writing it. And where do you think these LLMs, Rob, were trained? Where do you think the information? They were trained on actual humans writing content. So it's very hard to get to 100. Like we were actually having to twist and change the content to get that to cement it. That's where a education at the executive level needs to happen. Because this needs to have champions all the way through. You've got VPs, innovation, you got CROs. But like, everybody's got to be on board with this and understand it because a lot of people are afraid of it and are pushing back or worried about their jobs. I have. We've implemented AI heavily in our company over the last two and a half years. And we just gave people more reach, we gave better productivity. We, we gave people the access to do more things. It actually wasn't limiting and like, hey, we need to get rid of these jobs. It was actually how we can do more, deliver more, deliver better quality work. But it's all about that perception. And if you're thinking AI is going to replace you, it is. If you're at a company and you're worried about that, you need to understand how they are because somebody that, that AI is not going to replace you yet. These agents have a little bit more time before you turn out full agentic AIs. And we've heard some horror stories about that, but somebody leveraging AI and understands how to use these systems will absolutely replace you if you're not understanding it.

B (53:35)

And that's the truth. No doubt about that. And I would, I would take it up one level, Matt. This is a CEO issue. This is strategy, this is vision. This is the future of the company for the next five to 10 years. Right? It and marketing alone are not, not going to drive these decisions. You and I had it. We were at a, at a customer and we were talking to him and I was sitting next to the CEO and he sat there and he said, we have to do this. Right? He got it. He, he, he just was like, I don't have a choice. If I want to be there in the future, I have to do this. And the good news for them, right, is they have, they have information. It has to be put out there. We have to make the land grab. But they're actually in decent shape. But the CEO totally got it and suddenly, guess what? The cfo, the cmo, the, the CRO and the CTO were all like, yeah, we gotta do this.

A (54:43)

Well, that was, that's rare though, that you get all of them in a room and you get everybody on the same page and they understand it. And that's where this executive level advisory really comes in to get them on the same page. I know after that specific presentation you're talking about, we were asked to leave the room. So I had the CFO and the CEO and the head of IT starting to talk. We had all the other executives there and they're like, could y' all please leave and talk about this outside? That's what you have to do. You gotta get everybody on board to push from the top down and the bottom up. So it's a top down approach and a bottom up. And you got to hear what the people in the trenches are hearing. And it can't be disjointed. Because the last thing that I'll say about this is what is happening, the transformation and happening is going to be so fractured. Okay? There's going to be a huge tail on this that businesses are going to operate the same way. Some people are going to implement it in some areas, but the companies that leverage this, that can move forward towards this AI First Company are going to crush other companies. I have, I, I did a podcast a couple podcasts ago. I encourage anybody to go listen to it. It is a driver's ed company, okay? That is a true AI First Company. That they are operating in such an archaic industry that I would put bets on this that this will be the best, biggest driver's ed company in the next three to five years in the country, hands down. I would put quite a bit of money on how they're operating and how they're competing with it. And you should just listen to how they're implemented. I'm going to be doing more interviews with AI first companies. And I would just encourage everyone to go educate yourself on this or reach out. We are going to be doing a webinar on this very soon. We've really focused on LLM visibility and how you can leverage an AI layer in your business. So I would encourage you to check it out. Rob, you're doing a lot of this stuff. You're implementing a lot of these processes. How do people find out more about your work, what you're doing, check you out, find out more about your company?

B (57:02)

Well, thank you. Because I was just writing down some of the stuff you were saying I learned from you. Every time I'm like, I gotta remember that. I gotta follow up. But. But thanks, Matt. So. So, first of all, I am on LinkedIn. It's in slash. Rob Newman. My. My name is up there. It's spelled funny. You can find us@netformic.com us. We're part of a multinational now, which is kind of cool to be a partner in that we handle the entire United States, North America region. You can find me anywhere. Matt is. Because I follow him around and I'm just trying to learn from him. But no, in all seriousness. And it's Rob newmanetformic.com so everybody go.

A (57:55)

Check out what Rob's doing. If you need a DAM or a PIM layer to your ERP system there. There's also a lot of other huge cases we didn't cover. I know that there was a lot to unpack. You can go back and listen to this at like 0.75 or whatever to hear it again. I know I talk fast. I listen to everything at like 1.5 minimum. That's all I can handle. But, you know, there. There's a lot of great value here. Hopefully you got a lot out of it. If you did. Please, please, like share or follow Shaiiko. We used to use the word Shaiko. Please leave us a review on the podcast. A lot of people are leaving us a review on our EWR gnb. I do appreciate that, but leave it on the podcast. If it's about the podcast, you know, if you like what I'm doing, leave me a LinkedIn review. I would appreciate that too. Leave it on me. As an individual, I think entities are really, really important and to separate those out. If you like to hear more, you like to hear this, reach out to me. I'm going to put together a selection of playlists. We are moving into YouTube best SEO podcast. We're everywhere. I know we are on Internet marketing secrets too, but I'm going to fold that back into Best SEO Podcast because I think we need to really get clarity and drill down on this. LLM visibility and going too wide. All those things are a consideration in these frameworks of AI discoverability that I'm putting together so you can check out some of our frameworks. We're going to be launching some.org sites to help educate the public on some of these things because I just think it's so important. Thank you so much for listening. To the end. If you would like to be a guest on our show, we do have a guest option on Best SEO Podcast. We're going to be revamping that site. Until the next time. My name is Matt Bertram. This is the Unknown Secrets or Best SEO Podcast. Bye bye for now.