Episode 83 - Ken Burke

Erik Martinez: Welcome to this episode of the Digital Velocity Podcast. I'm Erik Martinez, and today I'm thrilled to have Ken Burke, founder and CEO of Microcasting on the show to talk about integrating AI shopping agents into your e-commerce website. Ken, welcome to the show.

Ken Burke: Erik, always good to be with you and I'm super excited about today and talking about AI, one of my favorite topics.

Erik Martinez: Yeah it's a fun topic and it changes every single day.

Ken Burke: My God, yes.

Erik Martinez: I think I had you on a little over a year ago and we were talking about something very different.

Ken Burke: Very different. Yeah. Just in the year where AI has come and it's just amazing. You know, that even just in the last month, it's like, oh, we can now do [00:01:00] this, or this. Even chat GPT has gotten so intelligent about what it's done, and literally it's been within the last two or three weeks that it's gotten this intelligent.

So it's crazy.

Erik Martinez: Yeah. Yeah it's really fascinating to see what's going on and I'm excited to talk about your product and your service, because I think what you have stumbled upon.

Ken Burke: Oh completely. It's been a stumble.

Erik Martinez: A year ago we weren't even talking about this and all of a sudden like, "Hey, I started a new company."

So, Ken tell us a little bit about why you started Microcasting.

Ken Burke: Yeah Microcasting's been around for about three, three and a half years. And as with any good company, we were a kind of a customer success platform initially and had some really good success in that. But about a year and a half ago, we started integrating AI into the customer success area and we're like - wait a minute. This is direct application to what we know and my entire team and myself have been in e-commerce for over 25 years. I'm dating myself, but I started my first company in e-commerce in 1995, which was [00:02:00] the beginning of e-commerce version one.

I actually think we're on to kind of a whole different revolution of e-commerce using an agentic process. Where we actually see e-commerce as being all done through the agent and interacting with the agent. So search goes away and navigation goes away, and product presentation all just becomes integrated into one.

Checkout and cart literally just occur as you're talking to the agent and we just introduced voice control. So you literally just talk to the agent and tell 'em exactly what you want and you're done. Kinda like Alexa, but maybe more visual and what more people are used to.

If you think about the interactions with Alexa we're first generation and now can we apply this to the front end e-commerce experience and really take what has been going on for the last 20 or 25 years, literally what you and I created years ago together. L-shaped navigation, facet navigation, search on the top, products in the middle. It's still the exact same interface. It's [00:03:00] boring.

So e-commerce has become very boring, very standardized. Can it be revolutionized? Can it be upgraded to where now people are interacting with it in a whole different way? And I think it can.

Erik Martinez: Well, before we dive into all of that goodness. Let's step back for a second and I totally agree. We've been doing e-commerce a long time. There've been evolutions to page layouts and things, and you can see a lot of that in the manifestations of what Amazon or Wayfair, some of the big marketplaces are doing. And you know, like anything, they go too far and then they kind of bring it back and then they go too far again.

But I think what's really interesting about this moment in time is you used the word agentic, and I think we probably need to describe what that is. So I'm gonna give you my version and then you tell me what your version is.

I was sitting down with a friend of a few months ago, and we were talking about AI and where it's headed and I'm like, I have this question. "What happens to the website when you have AI [00:04:00] agents working together?" So basically the concept of an AI agent is an application that's going out and doing something on your behalf.

So shopping. The other day I had to buy oil and an oil filter to do an oil change in my car. I can choose from, easily two dozen stores within 25 miles of my home to buy oil and an oil filter. Well, I go to same basic one, and I place my order and I go pick it up and it's good, right? But I do all that work.

Whereas in an agentic world, I say, Hey Alexa, go get me this type of oil with this type of oil filter for this car. I probably don't even need to be that specific because it probably knows this car requires this type of oil filter, and it goes and finds me the best pricing, returns that back to me and says, here's your best three options. Which one do you want to go with? Do you want that delivered? Yes. And boom, it comes home. And I never touch the website ever.

Ken Burke: Yep. I think you just [00:05:00] define kind of the next generation of e-commerce and how people will interact with it. Whether it be a device like Alexa or whether it be a phone or a desktop, right? Can it all come together in that ease about, I know what you want and I can go and kind of shop for you.

What I find in what we're doing is taking the agent AI approach is we're really curating. When you get a search result, you get a hundred products, 200 products, a thousand products, and what we're doing is we're returning five things or six things that you want because we're being very specific and then we're basically guiding you through that process. So it's a much more sane approach to getting exactly what you want very quickly. And that's part of what the agent process is

Erik Martinez: That's a stepping stone, right? What you guys are doing is the stepping stone that's leading to what I just described. So just to make sure that the audience is clear, what Ken's company is doing is basically replacing search and your chat bot at the same time.

Ken Burke: Yep.

Erik Martinez: And you know, we have a lot of [00:06:00] data that says that people hate retail chatbots.

Ken Burke: Yes

Erik Martinez: With good reason because they're very bad. They return horrible results. So, Ken, tell us a little bit about the Microcasting experience when you guys are interlacing your technology into the onsite search experience.

Ken Burke: Yeah. Absolutely. So we actually like to use the word augmented and it really resonates with the retailers that we're talking to. Which is we augment search, we augment chat because chat still has a function in the world. And so whatever chat engineer you're using, whatever systems you're using to do live chat or what have you, we need to augment that.

But we are the front end essentially. That brokers that relationship and that brokers even the search relationships we'll talk about as well. I would say we also replaced one other thing, which is navigation. Not completely, but we augment navigation. So those are the triad of things that we are augmenting.

First thing that you're gonna do is obviously you're gonna go in and you're gonna have an experience. And first question that a lot of people ask is, " Do I replace my chat bot area?" You know - the floating footer. [00:07:00] "Do I replace that with you guys?"

What we found in every case that people start somewhere else. So far all have gone and replaced our agent with their chat bot and let us broker whether or not somebody needs to go to live chat. They can always opt into live chat, right? Or if somebody needs to be redirected to something else on the site or somebody just needs to have an experience during off hours or what have you. That they can have a shopping experience and be fulfilled with that. And that's the natural progression of things. Number one.

Second migration I call it the crawl-rock-run strategy. So the crawl would be, I'm just gonna put a little button somewhere on the site, maybe on the PDP page, and if somebody clicks on it they can open up a window and they can have a experience with an AI engine. So that's kind of bearing it a bit. And we started with some customers there.

Then we went to the walk strategy where it's on every page. It's actually replacing chat, the floating footer, and that experience is carried through the entire shopping experience.

Then I say the run strategy, which people are just [00:08:00] beginning with, right? This is very early, is doing augmented search. We're not replacing their search engine, they type in their search. And what we do is what Google does. We come up and we give you our AI version because they may have asked a question, they may have typed in keywords that didn't make sense to the search engine, but will make sense to us. So we're giving them our results. And then the results for the normal search will appear below that.

And you can do it side by side, top and bottom or what have you. That's kind of the more run strategy that we're seeing. I think that the next strategy after that is where we replace cart and checkout. So we're already starting to experiment with cart where you can add to cart within the agentic process.

The next step that we want to carry it over to is actually the checkout process. That's where I think we then go full circle.

Erik Martinez: But at this point, you know, the distinction between the vision I painted, which you're completely off the website, all of this is still on the website at this point?

Ken Burke: It is, yeah.

Erik Martinez: But it's fascinating that people are starting with their chatbots [00:09:00] and it may be just a mix of the companies that you're working with versus some of the companies I'm working with.

Cause most of the companies I'm working with don't necessarily have that chat bot.

Ken Burke: If they don't, then it's an easier pathway for us to get to That spot.

Erik Martinez: That augmented spot.

Ken Burke: It's more natural. But if it's already being taken up, the first question they ask is, "Well, I like" - they don't like a chat bot, but they like the live agent chat interaction when it's needed. They don't want a customer to go without an experience so we have to do something with it.

And when I first started this probably nine, 10 months ago, we were really worried. We're like, "Well, that's the spot we want. What are we gonna do?" They can't have two buttons there. That wouldn't make any sense. And of course our first set of customers said, "Why don't you do this?" And so we basically just programmed around it.

So the AI engine knows - based on topics and themes, it knows whether or not the discussion is going more to a live agent versus that. And quite frankly, it's not a lot of coding to do this. We just train the agent to know what a customer normally would ask for and we direct them accordingly.

Erik Martinez: So you guys have integrated this [00:10:00] now at least half a dozen times at last count. It might be more now since the last time I talked to Christie.

What do you see in terms of buyer behavior interacting with AI? What types of questions are they asking? Are they engaging longer? Because I know I've done the demos of just a simple crawl and you guys plugging some stuff in and I'm like - whoa, this is maybe not a perfect experience but it was dramatically better than any of the standard onsite search or navigational experiences I've ever had. So, and for the audience sake, we're not here to, well, Ken is, but I'm not here to Microcasting.

But what we do want you guys to understand is like there's some really fundamental shifts happening in the way this type of technology is getting deployed and how the buyer, your buyer, interacts with it. So can you share some of the data that you have [00:11:00] gleaned so far from the implementations you have about buyer behavior, what they find interesting, improvements in conversion rate or engagement rate?

What are you guys seeing?

Ken Burke: Yeah, absolutely. Well, the first and most interesting thing when we look at the individual conversations, and we shared them with our customer and a couple of reactions that I've gotten, just first off the cuff is, "Wow, my best call center agent, or product expert, could not answer this question as detailed and as good as the AI engine did."

Because no individual call center might know some of the nuances of the data that we have access to. Literally, I mean, we have access to every PDF, every product description, every customer review possibly social media and other types of feedback that are all being put into the model. It's not possible for even the best agent to have that much information.

So one of the reactions we've gotten is, wow, that was an eight interaction. We count things as interactions, and I'll talk more about that in just a moment. That's a conversation. So eight interactions and the customer - we've [00:12:00] seen this as well, they say thank you a lot. I always find that as interesting because - do, they think they're really talking to a human? I think they get so into the conversation that, at the end of the day, you've really helped me. Thank you so much. Now maybe they know that's going in a backend database and somebody's reading it, but they're interacting with an AI agent.

Second thing that we see is it's a bit addictive. I think that's what you experience, because what we're doing is when the customer first interacts with this, we then provide them with some result. Let's say that on one of our sites they sell apparel and they type in, "Hey, I'm going to a music festival this week. What would be appropriate for Coachella?" Okay.

The AI engine knows that it understands what Coachella is. It understands what is in inventory. It understands the product descriptions and can give the the customer the recommendations. But then it engages them in a two-way conversation, which is what we call, they're called refinements in the technical world. There are basically AI driven facets, if you want to think about them.

But it's not 200 facets, it's four or three. It might be size, might be color, might be [00:13:00] thematic, like Comfy Fit is one of 'em that I recently remember seeing on this interaction. And they click on Comfy Fit. So it can be very touchy feely. These are facets that are not predefined. In fact, we don't want predefined facets. We want the AI to come up with 'em. So sometimes I call 'em facets - the real name for it is refinements.

Customer clicks on one, two, or three, and then the conversation continues. Here's what I find myself doing, and then I see it in the data. Then they click again. These interactions, I'm almost having a bit of a challenge in that they're interacting so much or continuing to interact that well - they gotta buy at some point. So we're actually thinking of maybe putting in a limit to where we then present them with an add to cart a lot sooner. We don't just let them go forever with these interactions because they're so engaging.

What we're seeing is conversations with six, seven, and eight interactions. So give you an average. It's about three right now. Where some people just do one, but on average it's three. But I've seen a lot of conversations that are 5, 6, 7, 8. That means you have a really engaged customer.

Now, you asked about [00:14:00] conversion and other things. We have to be a little bit careful about that 'cause I don't wanna take credit for something that's not totally ours. Here's the deal. When somebody's going and having an interaction with our AI agent, they're already an engaged customer.

They're already kind of an involved customer. They're probably on the higher end of that. So they are absolutely, unequivocally more likely to convert. It just is. So is it my wonderful AI agentic approach to commerce, or is it the fact that I already have a very involved customer that would've probably converted anyway.

That's the part I don't know. Are we seeing conversion up? Absolutely. I mean, I can throw out numbers, you know, 20, 25, 30%. Yes, we are seeing conversions up of the people that interact with the agent. But I do wanna put that caveat because I think it's important.

Erik Martinez: So have you guys done any kind of AB testing?

Ken Burke: We do have a customer right now doing an AB test as well, and we're looking at the data. It's still early, and I do want to caution everybody that it's early. What I do know is that when people actually use our engine, we then track conversion in Google Analytics as an example, and we can see that conversion.

What you really want to be [00:15:00] able to see is AB testing of, again, people that use it versus people that didn't use it. The early results are that we are seeing a tick up in it, but I think it's still too early to say. You know, as we kind of work through the technology, but I wouldn't say it's dramatic because remember, the pool of people that are actually using it is still small.

So if I've got a hundred thousand users, we might have a thousand actually using the agent. Right?

Erik Martinez: So that's, it's still a lot.

Ken Burke: It's still a lot. But it's a, that's the caveat that I wanted to put out here. I know the data. I have the data and I've seen it, but. It's still a small pool. We're in the very beginning stages of this, and so I think over the next year where Target has now put it on, not our engine, but they put their own engine on Amazon has Rufuss.

As you get the customer trained to use this more often and it gets more prominent positioning. Integrating it within search - you get higher usage when it actually is just part of the search experience and that's really the beginning stages of getting into search.

Erik Martinez: Do you find [00:16:00] that being able to put it in search as an example to get that usage up accelerates the learning of the AI engine behind it?

Ken Burke: Usage is what accelerates the learning overall. And it accelerates the learning from two perspectives. One is we have a pretty robust reporting system that informs product managers and merchandisers and other things that are actually educating them on what people are asking and talking about.

By the way, let's not overlook that. That's also part of the learning. And then the agent itself, it's basically the more it gets used, the more it learns. That's the formula.

Erik Martinez: And you know what, a thought just popped in my head as you were talking about, it's helping the merchandisers and the purchasers. A couple episodes ago, I had a conversation with a gentleman named Joe Hudicka. And Joe works on the logistics side of the business, and we were talking about how to connect your e-commerce right through your supply chain and what you just described provides some of those capabilities.

Maybe not there today, but definitely the [00:17:00] ability to make that happen tomorrow. So, as we're talking about this - a question keeps coming up in the back of my head. If you are the buyer of this technology. I'm sitting here and I'm putting my CMO or VP of E-commerce hat on, and I'm looking at your technology versus, what's being deployed on Amazon and stuff. What are the critical decision factors?

What is the best way for me to get my head around what you guys are trying to do and how to leverage the technology the best for my company? What's your recommendation in terms, you know, we can deploy the thing everywhere on the site, right? And at this point you've got some use case data to show people.

But, if I'm having that conversation with you, "Ken, I'm like, Hey, look, I'm a very technology forward person. I'm like - I'm in." Versus the person who's like, "Eh, you [00:18:00] know, I see all these shiny tech tools and I've spent lots and lots of money on tech over the years that, yeah, doesn't always quite achieve its promise."

What do you say to that person that's on the fence. How do I characterize this in a way to say to somebody, you know what? Here's an easy way to start". Because I think at the end of the day, one of the biggest hurdles with tech is, you know, everybody's got a free trial, right? I just signed up for a free trial on like three or four SEO tools. I should never do that because I can barely get to the one.

Ken Burke: Right, right. Let alone three or four. You're ambitious.

Erik Martinez: So. If that's the challenge, how do we get over that? How are you guys solving that problem to show the value of what you're doing? Because I think it's imperative. That we kinda try some of these things.

Ken Burke: Yeah. I go back to the crawl, walk, run strategy again for anyone, and I would say that if you're a little bit skittish about this, but you want to have the [00:19:00] customers to start to experience it - just so you can get data. That your sole purpose is to get data. Maybe it's to ultimately increase conversion or abandoned carts or what have you.

But you just want to serve the customer a bit better. Maybe that you start by putting it in one place. So you basically put a button on your PDP page as an example, and it's integrated into the interface. "Hey, if you need some help, click here. Our AI agent will help you."

And so it's fairly discreet. You're not impacting the customer experience. You're not forcing it in their face. You're also not incurring the cost because the cost of trying this - the number one cost variable in all of this is the actual calls to the AI engine, what we call interaction, which is how we charge. So if you're just trying it out, it doesn't have to cost a lot.

And if you're on Shopify, for us anyway, the integration's at five minutes and it literally is five minutes. I swear to God. I did it two days ago. And it was click on a link, install it, and the product feeds were feeding right into our engine automatically.

So that makes the implementation and then to turn it on, you click a button and then it turns it on. And [00:20:00] yeah, there's some configurations on the back end, but your vendor - us - are gonna make it look good and make it look right with a lot of configurations to make it look just exactly as you want it to.

I would say the first strategy is - Hey, if you're really unsure of this, keep the interactions down. Just put it on the PDP page. In a strategic spot on the PDP page. Number two - if you're feeling a little bit more aggressive and that you want to get it out to all your users, then make it a floating footer and you can always AB test that and turn it on and off.

I have customers doing that right now, so that might control that. But what you wanna get is the data. You wanna get the data so that you can read what your customers are doing, seeing if it's actually helping them. And you're gonna get thumbs up, thumbs down data as well, because they are giving thumbs up and thumbs down.

Thank good, mostly thumbs up, but we do get some thumbs down. And you know what that tells me? We have a deficit in product data. So that means they're asking questions and you don't have the product data in your data feed or on your website or anywhere to be had. And that's a big mistake, but I've caught it time and time again.

When I go back and I look at a thumbs [00:21:00] down, nine times outta 10, it's because we have inaccurate data or lack of data, I should say not inaccurate, but lack of data. Maybe one times outta 10, you have some disgruntled person that would probably be angry at any response that they get. Right.

And usually it's something like, "This was in your ad, but it's not on the website." Well, that wasn't on your website before. So the other kind of thing that I've gotten is something around more of a customer service related thing that they're angry about that they might not have gotten a response on.

But you need to know that because you need to know what your customers are thinking. And this is the first real tool outside of maybe looking at your search results, which a lot of people don't do, unfortunately that you can actually read the conversations that your customers are having with your AI agent.

Erik Martinez: I've looked at a lot of internal search results and there is some good data there, but it's not as robust as you think it is because in the traditional measurement tools you get to see that hey, the executed a search, they got X number of results, and then they jump off.

You only see kind of, back to your earlier point, you only see the actual [00:22:00] aerial component of it where they take an action and you see, oh, well, every time they take an action - their value goes up.

Right?

But we're not insurance companies, we're in the business of selling products and the business is selling products is like we need more people to go through the funnel.

Ken Burke: Yep.

Erik Martinez: To get to a transaction. What are the biggest data gaps that you're seeing in the implementations that you're working on?

Ken Burke: Yeah, in terms of lack of information on the PDP page or on the product page, that's the biggest problem that I see for sure. And I would say marry this to other tools that are out there that will actually help you enhance your PDP page. Or the product data that you have. There's a lot of AI tools out there and I've seen some of them that will absolutely help. They'll auto generate information for you that extends out, how to information and other types of things as well.

Remember, I wanna make sure that everybody understands cause we didn't cover this - how this AI stuff actually works. We have the option to go out and use a large language model. We're not using that and we're not doing that. We can tell the [00:23:00] agent to go out and get external information, but you as an e-commerce person do not want external information coming into your website at all.

You wanna control a hundred percent. So what we're doing instead. We're only using the content that you give us. So the data gap that we see hands down is the information usage questions about the product. That's not nearly the level of depth that customers are actually wanting.

That's what we see as the problem. So we need to augment that, but we're only gonna use what you give us or what you point us to. Not the universe at large, because you'd be getting competitor data that would be coming back and you do not want that.

Erik Martinez: Yeah, I mean, it'd be like marrying Nordstrom with Victoria's Secret

Ken Burke: Yeah, technically you could, but you don't want to. It doesn't work.

Erik Martinez: That's, yeah. There's gonna be maybe some small overlap there, maybe bigger than we think, but it's not gonna work very well for you. So since you're using people's data.

That means you're installing the tool and you are having to collect data for a period of time. What is that [00:24:00] data collection period look like before you start getting effective results?

Ken Burke: Actually it's immediate. So the indexing occurs within four hours of the single day. We are gonna have digested a hundred percent of the content that you're giving us.

Now, does it get smarter and smarter as it goes along? And do we get smarter and smarter? Absolutely no question. But it literally takes four hours. From the time we turn on like a Shopify feed to the indexing in our system to full operation. Yes - it's that quick. It is because the actual language model that we're using to communicate with has been established already. So that's what we're leveraging.

And again, I'm gonna throw out some technical terms. It could be open AI, it could be Gemini, it could be Claude or Anthropic Claude or Anthropic Claude Haiku. There's all these different versions. I just looked at our list today and we have about seven different engines integrated already. The LLM models, right? That are back there, that interpret the data.

All we're doing, if you think there's magic to this, there isn't really. We are doing what we call rag. [00:25:00] Basically all it is, is a very complicated search on your data to get the closest results possible. Then we send it out to the AI agent. That AI agent then makes sense of it and brings it back. That's where the training and other things come in.

So I guess I could just say that it's not horribly complicated in which to do. It's all the tech around it that is required. The integration with Shopify, how the window looks, how the interactions work, all the features. Give you an example. We just introduced a new feature where when you go onto a product detail page. The first thing we do is if somebody clicks on the button, we render three questions specifically about that product in our box as our suggested prompts.

And we do that on every page, every product detail page that is absolutely helping cue the customer. Cause they would rather read a question than have to think of one themselves. They might have one themselves. It might be like, "Oh, I wanna know a little bit more about this." And then they get the answer right away.

That's technology that's leveraging all of this infrastructure and we just keep coming out with more and more stuff, and others are as well. But I did wanna highlight that. The [00:26:00] actual underlying AI technology is kind of commoditized at this point. I know it sounds strange, but it's commoditized.

I can use one of 20 engines LLMs out of the box. I have seven integrated, but I can turn one on in about two hours, right? That's not where the tech is. It's all the nuances around your data and around how we go about this and how we interact with the customer.

You and I are both merchants at heart. You are much more than I am, right? Because I've never been a merchant itself. You have been because I've worked with you in that capacity.

What we want to do is to influence the experience a customer has at every step. And if we can influence it by being one step ahead of the customer, or 10 steps we're gonna be in better shape to be able to anticipate exactly what that customer's gonna want, the moment in time they're gonna want it, and personalize it to that individual customer.

Bingo. It sounds like an old story of personalization. This is kind of personalization coming back in a very sophisticated way.

Erik Martinez: Yeah. And it's gonna evolve towards that vision that we painted at the very beginning of this, right? Where the website is [00:27:00] not the place you're interacting. You're interacting on your phone with a voice assistant talking about whatever product it is that you're interested in buying.

Which is really kind of mind blowing because we have to rethink as marketers and merchandisers and creative people. How that's gonna look in the next three years, five years.

Ken Burke: So I would say it's coming faster than anyone thinks. Again, we're at the beginning or what I'll call early into this process, but everybody is talking about it and what's great about what we do - it's very visual. So in five minutes. When I show somebody their data in our engine they get it instantly and then it starts to unfold.

But I think you're absolutely right about the vision in that you're gonna basically just say, "Hey, I wanna buy something from X company." And that's gonna be the interaction that you're gonna kind of bypass, a website or a mobile experience, and you're just gonna be saying what you want and the system.

So it's [00:28:00] kind of like everybody will have their own Amazon, if you will, with all the sophisticated tools and all the things that Amazon has and all the infrastructure. Cause I can just talk into my Alexa, but instead of buying from Amazon, whether it's Alexa or something else, I can buy from the actual retailer and quote unquote cut out the middleman.

Erik Martinez: Yeah, no, totally true. Let's just take this one step further to something that we probably all do very frequently, which is drive in our cars. We wanna order takeout because we're on the way from here to there and we don't want to go to the grocery store or whatever.

Ken Burke: Yeah.

Erik Martinez: And basically, what you're saying is this type of technology is going to lead to, "Hey, Siri or Alexa" or whatever the agent is on your car and - " I want to place an order for this type of food, from this location in 20 minutes."

Ken Burke: But think about that from buying a dress to anything else. Or to I'm headed to Home Depot and I need some deck, repair kits or whatever. I was working on my deck this weekend. So I went to Home Depot five times, right?

Erik Martinez: Ah! It drives [00:29:00] me crazy!

Ken Burke: Yeah, exactly. Yeah. I'm always forgetting something. But you're always looking for the right thing at the right time, and so on and so forth. So you just wanna tell 'em the situation. Just like you're talking to somebody maybe at Home Depot, but there isn't anybody to talk to at Home Depot, ever.

But when I need something I go to chat GPT over Google almost all the time now. I've installed the app on my phone, and I think a lot of people are like this as well. I kind of bypassing the search. I'm just going to chat GPT.

Well, what's next? Chat GPT just actually announced, and I don't know if your listeners know this or not but they have full e-commerce. They are presenting product. It's like Google shopping for chat GPT, but it's not influenced.

So remember back in the day when Google Shopping first came out? Well, they say it's not

Erik Martinez: It's influenced. You and I were around when Google started doing this.

Ken Burke: True

Erik Martinez: And it was influenced.

Ken Burke: Well, it was

Erik Martinez: Well, it was mildly influenced

Ken Burke: Now it's majorly influenced. I get it. When it first came out. I don't know - I can't speak for them. But at the very beginning though, and I think that's where Chat GPT is according to their announcement, is I've actually [00:30:00] interacted with it. They partnered with Visa to, I guess, enable transactions in some way. I haven't actually bought anything from it yet.

But if they're doing this now, I think they see two things. One is e-commerce. It's a huge market for them. Cause this is one of the first real apps outside of the actual chat engine that is integrated. Go to Chat GPT and try to look up something. I encourage your users to do that. You will very likely get a product display over on the right hand side of the screen.

Erik Martinez: Yeah, it was very interesting. I was listening to the artificial intelligence podcast with Paul Roetzer and Mike Kaput and they were talking about some very interesting positionings with the large language models between Google and Gemini and where they're headed, and Apple and Anthropic, and Open AI and Meta. And it was very interesting because of all those companies who has the most data?

Oh, and Amazon, of course we can't lump out Amazon. Amazon and Google have the most data right. Apple has a great amount of [00:31:00] data and they were saying it's kind of terrible how awful Apple is at artificial intelligence at the moment

Ken Burke: it's kind of scary. They're a little behind.

Erik Martinez: Yeah, I've got a iPhone 16 with Apple Intelligence and I can promise you it's not that much more intelligent than not having Apple intelligence on it.

it's really not a great experience. What's really fascinating is open AI has a partnership with Microsoft and they probably could get some data there, but they don't own their own data source.

Ken Burke: Yeah. No. They have to search the web like everybody else. Right.

Erik Martinez: Anthropic doesn't own their own data source, but Anthropic is interesting. It seems like they're positioning themselves really to be the leader in the agentic side of the business. So it's just really kind of fascinating and while all of you listening to this maybe going, "Okay, Well what does that mean to me?" What it means to you is you're not prepared, nor is our society prepared for what we're talking about today.

And [00:32:00] what Ken's company's doing is kind of starting to bridge the gap between the now and the future. And if you are an e-commerce retailer or you're any kind of retailer - you were just talking Ken about Home Depot and how there's nobody in Home Depot. Well, shoot.

They could put a device in every aisle on every bay and give that same capability that you're talking about to every customer in a store where they can just ask the question and say, " Hey, we've got three products and you can find them in this aisle, and for your specific application, buy this one."

Ken Burke: Absolutely right. Absolutely. Yeah, I wonder if and when that's going to happen. It's such a bad shopping experience. I mean, they're almost discouraging you not to go into the retail store.

Let me give you a quick example. I went to Target this weekend and half the products that I wanted to buy were locked up and this is in suburban San Francisco. This is not a bad neighborhood. And I literally was like, "Well, why am I even here?" And I went home and I just said, I'm gonna buy it on Amazon. And that's what I did.

It was just so frustrating because I'm gonna hit a button and wait, you know, there were [00:33:00] probably six or seven aisles of things in this particular area that were all locked up. And then I couldn't find what I was looking for. Even if I could get through the case, I'm like, screw it. This is, I don't even know why I came here and I left.

Erik Martinez: Yeah, yeah totally agree

Ken Burke: They're discouraging the experience and CVS and everybody else is - they're all following suit. And you wonder why the in-store retail is dying. I don't want to say that it's dying, but I can tell you I don't know why people go.

Erik Martinez: Well, it's interesting .That you say that because we have some data that says there's about a third of the people out there who would rather have a retail shopping experience. Because they still trust it more do digital.

Ken Burke: But it becomes harder and harder to engage.

Erik Martinez: It is becoming harder

Ken Burke: It's harder and harder just to buy. I mean, what they closed down all the Macy's in the Bay. Almost all I can't find a Macy's now in the Bay Area. I'm sure there is one or two open. It was making it hard to buy from wherever you used to buy from.

They don't exist anymore. So that's another problem. It's just access. And I get it the world is changing in all of that. I agree. But I do think that retailers are making it very hard to buy things.

Erik Martinez: So what [00:34:00] Ken's also saying is that those of you in the e-commerce space are doing fine. You're great. you're well positioned to compete against the marketplaces by deploying these types of technologies. For those people who really want an authentic brand experience, because let's be honest, buying on Amazon isn't about price anymore it's about convenience.

Ken Burke: Absolutely.

Erik Martinez: And if the small and mid-size retailer, e-commerce retailer can make it more convenient. Suddenly that big advantage that Amazon has goes away as long as you can still fulfill in a reasonable amount of time.

Ken Burke: Yeah, I mentioned that earlier and I think that's a really important point. Can we, through some of this technology, bring down the barriers so that everybody can have the Amazon experience, or more of the Amazon experience, and I think you can as well.

Erik Martinez: Yeah. So, we've covered a little bit about Ken's technology at Microcasting, which I think, try it, talk to his team, experiment, have him do a demo. The demo is really pretty impressive I gotta tell you. I've done a couple of them now and I am really [00:35:00] impressed with the initial results, and that's without any beautification of the page. Just the simple results and going, "Holy smokes, I wish I could have done that."

Here's the other thing, you know, Ken was talking earlier about helping merchandisers and stuff. This can help your customer service operation. Think about the types of questions that in product training, which I know a lot of you do. It's still hard to convey all the information in your CRM or ERP or whatever order management solution you have to your customer service team to explain what the product is.

But now if they get a call, and for those people who still want to talk to another human being, which is hugely important, that human being can now leverage these types of resources to pull the data up and help answer that question much more effectively.

Ken Burke: You did a better job than me of explaining the phenomena that happens every time we put this thing in. Is that customer service VP or success manager or whatever - calls us or [00:36:00] gets a hold of it and says, "I want this for my customer service team." Inevitably, every time it happens, and I gotta tell you, the customer service teams forget the front end people.

We get such rave reviews, and it's not just us, but the fact that they have this tool. Now, what you just said, they've never had access to this data before in this way.

Erik Martinez: Not in this way. No not at all. So look, you know, Ken's company is just one of number of companies that are pioneering these types of technologies. Our recommendation is start looking at them.

And if you don't know where to go, start reading some blogs. Start getting into the AI world. Yeah, there is a lot of smoke and mirrors about AI technology and stuff, but find examples of people really solving very specific problems. Not just subject lines for your email, but really solving human-oriented problems that your customers are experiencing.

If you can find a solution that's similar to what Ken's pitching. And again, I've seen the demo it's pretty cool. I've seen some of their live sites. It's pretty cool. Is it perfect? No, nothing's perfect, but they're [00:37:00] getting better.

These tools are going to be the future of your e-commerce business. And it is time that we all spent a little bit of trying to get familiar with some of these. So that was our goal today,

Ken, before we wrap up this conversation, and thank you so much for coming in and sharing a little bit about what you're doing with Microcasting and pontificating about the future of e-commerce and AI. Is there any last thought that you'd like to leave the listening audience with?

Ken Burke: Yeah, I think that the best way to get your arms around this is you kind of dive in a little bit and you dip your toe in the water. And I think with this particular kind of technology, you can dip your toe in the water and doesn't have to cost a lot. Yeah, there's a free trial. We have a one and other people have one that's fine. But it's dipping your toe in the water and just starting to play around with it.

Even if, all you do is put it in your call center. Even if you just started there, you will start to see that this opens up another world just like that first time you used Chat GPT, and you went, "Wow, this is incredible."

And then you started writing with it and it's kind of the same thing. And that's what we're experiencing [00:38:00] now and it's just gonna get better. You're right, we do stumble on occasion. We're not perfect. Although, I will have to say the speed at which we're evolving is ridiculous.

So, you gotta jump in at some time and to get more experience, just knowledge inside your company. I think it's worth doing it just for that reason alone. And I do know it will enhance your overall customer experience. Absolutely. And by the way, you have to do this. This isn't a choice. So you either do it now or a year from now, or two years from now, but you have to do it.

It's kinda like, remember Erik - in the day. Erik and I have known each other for a long time.

Erik Martinez: A very long time.

Ken Burke: And when we did our first e-commerce site together, not everybody was on just catalogers I mean, you were at a catalog company and it was just catalogers that were on there.

Now, can you imagine, can you fathom a retailer not having an e-commerce site? Can you fathom anybody in the direct business, not having an e-commerce site?

Erik Martinez: You could still find them, believe it or not, but it's extremely rare.

Ken Burke: Extremely rare. We are at the beginning of that same cycle when you and I first met with AI, except it's gonna go a lot faster. It's not gonna take 15 years. Cause I lived through [00:39:00] that from 1995 to probably 2010, where we were still putting people on for the first time.

This is gonna be in the next two to three years. This is gonna proliferate through most e-commerce sites. So you just have to decide when you're gonna jump in. Not if it's when.

Erik Martinez: I think that is a debatable point. I think, you know, in the places that I'm following, I agree that the speed of which it's coming is coming that fast, faster, maybe.

I think our ability to absorb. I'll give you a good example. I was talking with a client a couple years ago, and he is like, when do we need to be worried about crypto?

I'm like.

Ken Burke: Yeah.

Erik Martinez: Hey look - crypto is coming and it will be ubiquitous at some point. When that is, we don't know. But one of the reasons it's not ubiquitous right now is because all our existing tech is not compatible.

Ken Burke: Yeah

Erik Martinez: So all that tech still has to be compatible. The thing about AI is that it can be compatible with more tech now than crypto can be in any regard. [00:40:00]

Ken Burke: That's absolutely true

Erik Martinez: So it will come faster. We can debate whether it's three years, five years, 10 years. I'm with Ken. I think it's gonna be sooner than later, but there's still a curve. And for you brands that, "Hey, I don't wanna be on the leading edge of technology." You don't have to be, because there are practical solutions that exist today that are starting to bridge that gap for you. And Microcasting is one of those companies that's doing that.

This is not a sales pitch for them, but this is the type of technology that if you want to evolve your site and your customer experience and win. These are the types of tools that you need to be investigating and we're gonna try to do our best here at Digital Velocity of bringing more of these types of tools to the forefront.

So Ken, thank you so much for your time and your expertise. And I hate to tell you, you said plus 25 years and then you said 95, it's 2025 and just

Ken Burke: No, I know. No. Yeah, no. I was saying that when I was saying the [00:41:00] first 15 years I was forgetting about the rest of it. I wanted to forget about the rest of it.

Erik Martinez: Don't wanna forget that it's been

Ken Burke: It's been since 95, so we're 30 years into it. Right. Oh my God.

Erik Martinez: Thirty years into it, so.

Ken Burke: And I've known you for 25 of those 30

Erik Martinez: And that is about right. That is about right. Well, Ken, thank you again for sharing your knowledge. I really appreciate it. If somebody wants to reach out, what's the best way ?

Ken Burke: Yeah, you can reach out through our website. Actually we have a new website, micro commerce.ai, which has all this great information along with our blog and all of that. And I'm also just ken@microcasting.com or ken@microcommerce.ai. Either one works

Erik Martinez: You can find him on LinkedIn. I can guarantee he's active out there too. Folks, thank you again. This is a second in our series of product showcases, so to speak. I'd love to get some of your feedback on the conversation and if you learn something. We're here trying to help expose you to some new technologies that can help your businesses grow.

So thank you very much for your time. [00:42:00] Y'all have a fantastic day. That's this episode of the Digital Velocity Podcast.