The Future of BizTech Podcast

Ep. 63: Using AI to Grow Sales with Customized Ads – Matt Swalley, Co-Founder & CBO of Omneky

Learn more about Omneky at:
Find Matt Swalley on LinkedIn here:

JC: Welcome, everyone to another episode of The Future of Biz Tech, I’m your host, JC Granger. And I have another fantastic guest on the show today. And listen, if you end up loving this episode, show your love and appreciation for the podcast, wherever you’re listening to it, be sure to give it that five-star review preferably with some nice comments, because that is how other techies like you and I find cool podcasts like this. And today I have the absolute pleasure of interviewing Matt Swalley, who’s the Co-Founder and Chief Business Officer of Omneky, Matt, tell the audience a bit about yourself and what is it that you guys do?

Matt: First of all, JC, we say thank you so much for having me today. Love your show, and say hi to the audience out there. So I’m the Chief Business Officer of Omneky and the Co-Founder we are an artificial intelligence-powered marketing platform that uses real-time performance data across Meta, Google, Tik Tok, LinkedIn, Twitter, uses computer vision to help quantify what’s leading to performance. And then we use the latest generative AI tools plus what we’re building in-house to make really quick, efficient and more effective digital advertising campaigns and creatives. And a little bit about me is I have a different path than most, I spent 13 years at a Fortune 10 company 250,000 people working at AT&T. So yeah, and then transition to an early-stage startup. It’s hyper-growth. But I got to I got lots of iterations of leading teams like leading seven different teams over a period of a couple of years moving all around the country and meeting with 1000s of customers. And then one big career-defining moment that carries the Omneky was I set a goal to get into corporate strategy after I got my MBA, and I got some really big picture, go to market deep data analysis, where I was digging in data for weeks and then telling the story. And then as joining the most exciting generative AI companies advertising Omneky, that’s what we do we tell stories with data. So it was a perfect fit and love, love the ride.

JC: That’s awesome. That’s very technical background. And it is I mean, coming from a Fortune 10 company. I mean, literally, that doesn’t get much higher than that. Right? Also, I’d like to say I love your fashion style. I think I just noticed that we’re basically wearing the same thing here. So good for you. Imagine, for people listening, you can’t see it, but we’re matching and it was not planned. So tell me what motivated you to start. Well, did you you’re a co-founder. So you did start the company with someone else? What motivated you to leave? I mean, obviously a great career in is about as high corporate as you can get. Right. You know, what was that defining moment? What pain point did you say? Dammit, we got to fix this or you know, what, what was it that led you to co-found the company?

Matt: Yeah, so our founder Hikari Senju is a Harvard computer science grad. He founded it back in like the late 2010s. And he had this idea way ahead of time that data and analytics would be the key to using artificial intelligence and generative AI. It wasn’t yet at the point of this today, where it’s at this Cambrian explosion where it’s getting better every day. And you can actually create things with it. But he had the vision. And he founded it. And I was actually employee number three. So at the time, Hikari who was running, all of the engineering, all of the sales, was the most driven person I’ve ever met, he brought me in as the business leader of the company as employee number three, taking over all revenue-generating activities. So that was the entry point. And how I got decided to join was, I was doing corporate strategy and looking into all these emerging companies. It was the bull market after COVID 2020 and 2021 when the markets on fire. And I was looking at all these emerging startups and reading a book called Clayton Christensen’s innovators dilemma. Are you familiar with it?

JC: I’ve heard it, but I have not read it.

Matt: Basically, it’s it talks about how large companies get disrupted by these small companies, because they can’t place big bets, because they often are billion-dollar revenue streams. And it just really excited me to join a tech company. And I met Hikari, who I knew would help lead us to, like Initial Public Offering as our goal. And that book, though, opened my eyes and was like, I want to join a company like that, that is going to disrupt the incumbents and be that publicly traded company in the next 5 to 10 years.

JC: That’s awesome. But so let’s do this. You give a very technical explanation of what the company does. And beginning now let’s do more layman’s terms. So give an example of what it’s like, because I watched some videos on your website. So I have a good understanding. But for people listening here, give an example of who would use your system and what it would do for them in just real terms.

Matt: Sure. So we have multiple ideal customer profiles. So I’ll give you I’ll give you two major ones here. One is we partner with growth-stage startups where we’re partnering with the CEO or founder and we’re a direct plugin to their marketing team. And so what we do is, let’s just say let’s talk about meta and Google they own historically 60% of the digital advertising market. But it’s slightly declining right now, we would plug into those channels, we would look at historical advertising data in real-time. So you can look at, you can plug in through API integrations, and pull in data for why people are clicking, or buying things, lower funnel conversions. And then we have our own computer vision there that automatically tags things like color, length of the video, and text in the different dynamic sections of the ad. And with that, you can run regression and start to pull out insights into what are commonalities for different audiences that should be used in the next set of ads.

JC: So basically, it’s a massive split testing platform. And in one way, I’m sure it does other things, but I’m a marketer. Right? So I look at it from the point of view, like you’re saying that I can, I can, I can run some ads, and then based on their performance, your AI can actually pick out the why, and not just the what?

Matt: That’s exactly right.

JC: That’s impressive. Can it also analyze other ads? So let’s say, you know, does it have a competitor analysis? Can I see, can I analyze other successful campaigns of other companies, and then figure out why those work and play off of that

Matt: We cannot analyze, we can only analyze the data that we have access to. So the customer data that we have pulled in directly from the platform. Now we can make more macro views into verticals and everything. We can’t share data. But we can definitely look at verticals and performance and make assumptions that can be used for customers.

JC: So for example, if I start off with three different versions of an ad, and then I plug your software into it, how many more versions can your software create for me based off just before I’ve even run the ads?

Matt: We can. So first we need that historical data to get data. But what we use is the latest generative AI tools plus, plus our own proprietary technology. And we look at the data. And we can generate tons and tons of ads for multivariate testing. We’re talking anywhere from at the minimum 30 a month to hundreds for our largest customers. And they’re a combination of.

JC: Compounding as more data comes in. Right? That’s right. 

Matt: Yeah. And depends on how big the advertising budget is. And like, one of the biggest things in the future is micro-segmentation, or being able to really do targeted campaigns more personalized. So what you do is you can be really agile with the data and target different segments of your customers instead of more general very quick. And what we’ve got the time value down or the time we can launch a campaign is down to like, like three business days right now where we can have an initial onboarding, connect with the data, and then turn around a first set of ad creative for a company with either little to no brand assets are quite a few brand assets in three days. And then they’re fully launched within a week. So where can that’s like one of our major key KPIs is lowering that time as we build on the key.

JC: Very cool. Okay, so now let’s talk platforms, what platforms does your system work on right now?

Matt: Right now we have integrations with Meta, which includes Instagram, Google, which includes YouTube, TikTok, LinkedIn, Twitter, Reddit. And then we’re building out connected television and some of the other mediums like gaming, which is going to be an emerging vertical.

JC: Cool. Cool. All right. I have a question about LinkedIn, because I’m a b2b guy. Yeah. So LinkedIn has mostly I don’t know this, I’ve decided to get the audience per second. LinkedIn has regular ads, like you see on anything else, right. You can do those, but they also have inbox like in mail style, like, ads, where it goes, it sends a message right into the inbox. Does your system yet? And if not, when? does it deal with that? Where it can take let’s say, I write a sales message and I use the paid version to drop it into inboxes? Can your system right now create different versions based on the feedback have it in that in that kind of text? Because it’s longer? It’s much more text than it would be for like a small ad. Do you guys work within the paid version of the messaging?

Matt: We have not expanded the messaging yet. And that’s something I’ll definitely definitely

JC: Feature request right now. Like, I’ll use it tomorrow if you do, because we love those. We love the direct pay that so features requests? You heard it here on the podcast,.. Okay.

Matt: That’s great, yeah.

JC: I mean, so um, what type of it’s funny I was usually asked what type of marketing early doing but obviously you’re probably using paid ads in your own system. Why not turn the turn the guns in but let’s say outside of that, obviously, using your own system to promote yourself. What are types of marketing? Are you guys doing? You’re doing PR, you’re on a podcast, so that one’s checked off. Okay. What else are you doing to get the word out? And how long have you guys been around?

Matt: We, our first revenue month was in March 2020. So we’ve been around since then,

JC: That was a great time to start a business, wasn’t it? What happened in March of 2020? I can’t remember I think my mind has blocked out the trauma.

Matt: The world is shut down, the market circuit breaker was pulled multiple times in a day at one point around that

JC: You picked a hell of a time. But hey, here you are, though you made it.

Matt: Yeah, we do really well, with a number of different ways for generating business one is in, they all complement each other. That’s what’s so exciting about marketing, right? They’re all a different complementary strategies. And then you can target and retarget at different areas of the funnel. But digital ads is really our main major business development. And then we have a team that sends out targeted emails, and then the goal is to set up a demo or we retarget. Those, those people, once they visit our website, or landing page or social page with our ads is the second one. And then we get tons of word-of-mouth referrals from current customers, and then building out partnerships in an agency arm as well. So those are our major channels.

JC: You’ve got it down that I mean, that’s you definitely we’re using all the angles, which is good. Let me ask you a question for your, your optimal client, I’m sure you can take on a broad range of industries and company sizes. But let’s talk optimally speaking. What size of budgets monthly budget, do you find that is kind of the minimum where you see the most effectiveness of your system playing into just so the listeners have an idea of like, who they should refer this to? Or should they’re referring it to mom and pops, you only spend 500 bucks a month? Or should they be only referring it to enterprise level that are spending 50,000 a month? Like where is that sweet spot? That you advise that like, Listen, this systems really going to help you more? If your budgets at least x?

Matt: Our sweet spot is between $10,000 in ad spend to Oh, half a million to a million dollars is our sweet spot, but 10,000 and up essentially per month? Yeah, yeah, our smallest customers that are testing and learning concepts, you need to get enough data, you need to spend about $3,000 a month in ad spend. So that’s just from learning from data, testing your value prop product, we can help customers find product-market fit with that kind of data, bringing initial customers on, but really, the greater than 10,000 is really the sweet spot.

JC: Perfect. Now, question just about your company as well. Obviously, your your SaaS platform, people go in there. And they use that? Do you have an add-on service by any chance where you guys have offered to manage certain ones that people want to use your system? But then they’re like, listen, can you just do this? Like, do you have an add-on to that?

Matt: We sure do. So with about 50% of our customers, we offer the full management through our customer success team. So we do a campaign strategy, go to market, how we’re going to you know, go after different audiences, then we segment each one with a different type of creative or multiple different types of creative that then we go multivariate test against each one of those types of platforms or mediums.

JC: Awesome. Okay. Well get into the main question, of course, my two-part question do for every episode for anyone who always listens, a future biz tech. So let’s let’s talk about the future. The first question is about the industry. So not you guys in particular, but kind of the industry you’re in? Where do you see these kind of multivariate testing AI-driven marketing platforms in general, going in the next three, five or 10 years? Whether it be from legislation, you know, because a lot of privacy stuff out there too, for targeting? Whether it be culturally, technologically just where do you see the industry going? Is there anything that excites you, or worries you coming up in the future?

Matt: Well, it’s a really exciting time, since it just hit this commercialization. It’s crazy, the multiplier effect of all these people learning how to use it, and then telling people, one of the most interesting things I will say, like in the short term, and I’ll give you a long term here, is that everyone, people aren’t going to lose their jobs, they’re gonna have to evolve how they think and how they in how they upskill like, using AI is such a different brain power than the past where you actually have to write something down and think it through or design it on a you know, on a canvas or on a computer. Now you have to understand how to tell the AI what you want it to do. It’s a completely different thought process. So

JC: not as easy as people think to like they’re like, oh, just ask you something. And it’s like, I’ve never asked this isn’t saying go ask that brick wall something like where do I even start? Like I don’t like even know, like, I start with small stuff like have a Chat GPT. I’ll be like, Oh, tell me this. But then I see examples of other people. And they’ve asked it, something’s super complex I never would have thought of it. I’m like, Oh, okay. I didn’t know it could do that. I guess I’ll you know, so we learn on how to even talk to it, just like you’re saying just as much as it’s learning how to give answers.

Matt: Right, right. And then you have to learn how to get really specific on what type of camera lens you want. Do you want a drawing or crazy color picture. There’s all these different things the way you tell it to do to get what you want. So the more you can figure out those different models and different ways to explain something the more successful you have in the near term video is going to be there very soon, in the next year or two. So you’re gonna be able to tell AI to completely put together a video for you. And I can actually see within the next five to 10 Here’s where you can, it’s going to have some sort of neural thing where it can tell what you’re thinking and then start to create it from there, which is mine.

JC: Now we’re gonna, now we’re getting to the scary black mirror stuff here, right? This is Yeah, but it is coming it is it does a thing like, like, you just look at the science, there’s no opinion here I will agree with or not, or if you like it or not, it’s not the issue, it’s going to happen. You know, there’ll be, there’ll be plenty of people, they’ll be more than willing to adopt certain things that other people will not be willing to. But it doesn’t make it any less real. So I just think it’s fascinating to see. And it’s gonna be an exponential curve. I mean, we’re not even be able to keep up pretty soon, too, you know, all the manual stuff for even like space launches. Right? Now, there’s pilots, yeah, there won’t be because eventually AI and computers will be able to take off a jet and fly it in space and come back better than humans can just like how we have, you know, auto driving cars that are coming out. I mean, the technology, the ability is one thing now the social acceptability, that’s a little slower, right? Where do you see, let me ask you that? Where do you see the the dissonance between the technical realities versus the social acceptability? And how much do you think that’ll hold back the industry because at some point, it gets scary people just, they don’t either know what to do with it, or they’re afraid of where it’ll go, you know, just do you see a big lag between our implementation versus our actual ability?

Matt: Well still, you’re still seeing with like, certain open models that are creating things only in certain ways, because it’s learning from out there, what’s already out there. So it’s creating. It’s almost picking out how something should look. And it’s showing it over and over again, instead of giving you a more diverse view of what all the different things are. The second one I think is most interesting that just is happening now is I have two little kids, learning is changing so much, right? Like when we were there, we had to write it on paper, we had to go read a book. I think we’re probably around the same age, you know, like was so exciting for you. And then now that Google search was last they were searching Google now kids are starting to write out everything on chat GPT. So schools are already going back to writing with a pencil and paper again, right now, like..

JC: When we were kids, it’s when those those those new advanced calculators were coming out. Remember what they it was the graphing calculators that came out, and that technology advanced so fast, and then we’re sitting there and like, you know, algebra, or calculus or trigonometry. And they were like, Okay, great. What do we do with this? Because these kids are figuring out how to do the whole equation just by typing it in, and we can’t actually prove that they know what they’re talking about. Right? So for us, it was the graphing calculators. And for kids now, it’s Chat GPT. And there’s this, you know, massive struggle and almost chaotic type of, like, what do we do? Like? How do we like, how do we get them to not like, how do we tell the difference, but you know, it’ll create another industry, now, you’re gonna have an industry, which is already probably going to pop up of someone’s gonna write software in AI that can track other AI so that teachers can tell if it’s plagiarized through AI, rather than just plagiarized from different sources on its own. Right. So like, there is a cat and mouse game with technology, which I think is really, really interesting.

Matt: The other interesting thing, too, is all these technologies are getting built upon these technologies that are getting built today. Like I saw it. I saw this week, someone already built a citing company. So it goes in and it can cite the things that Chat GPT is writing on top of, because a lot of times when you go you go get Chat GPT to write something like, where did this come from? And you can’t track it back. So now they’re building apps on top of that all in real time. And it’s just, it’s moving so fast. And it’s it’s great to be part of it.

JC: Apps on apps on apps. I like it. All right. So let’s talk about your company. Okay, I’d like to know, where’s the future of Omneky going right. And let’s talk about, you know, maybe in the next six months to to a year, and if you got any cool things coming down the pipeline that my audience gets to hear first, you know, we’d like the inside scoop. What do you got? 

Matt: So the other side of our business, we talked about how the data and analytics is an input, you can pull out different value props, images, texts, the things that should be included in the ads. Well, we have a generative capability where we have our own technology plus the open source ones, where we take that data directly feed it into a generative tool, and then it gives you prompts on what to create. So that’s really we’re combining it right so we’re taking the data and moving it right to helping the machine tell us potentially what, what you should make for a customer. So that’s one of our favorites. And then that’s, of course, the copywriting on top of that, in the future. We want to continue to do this of course with video and then for like E commerce, you can instantly take a product and you can put it in different backgrounds for production with a click of a button. That’s one of our favorite use cases for AR right now. You don’t have to go film things all over the place. You can take a product photo, you can go put it in all these different scenarios and then you can go take it to market within hours instead of weeks and a lot more money in the future. Omni key wants to go from just digital ads to landing pages to chat bots and key I’m expanding to improve conversions down the funnel. Because that’s next.

JC: Yeah. And I like because the funnels that have more pieces, just the ads, right. And like a lot of people, myself included, you know, we’ve been forced to Frankenstein’s to certain things, you know, you have an end goal. But once you start putting money into the top of that funnel, it’s got to go different places. So a company can add more things on so they can control that. And it works seamlessly. I mean, even better, right? Like one of my favorite examples is click funnels, for example, right click funnels as a software was way before its time. And it just started adding in so many pieces of the puzzle, so that it made it easy for people to go in there and drop things into the top of it. Whereas yours now with the AI into it, and the ads, if you start adding on that’s even higher in the funnel, and drops in. So that even does better than Click Funnels right, you know, in the future. So I think that’s really cool. Okay, so you had told me, you like to read or you’re a big reader, you’re saying, as a kid and whatnot, what is your favorite book you’ve ever read? It could be anything it doesn’t. We could talk business, it’d be business book, but just more or less like, what book is one of your favorites that you would even recommend to the audience, based on kind of maybe how you got to where you’re going or something that inspired you?

Matt: Sure. So one, I got a couple here. So the first one was innovators dilemma, I already talked about earlier about how you distribute..

JC: I’m gonna add that to my reading list now too.

Matt: How you keep making marginal improvements and eventually it gets good enough for commercialization. And then it hits a tipping point, and it takes out the incumbents. So that’s, that’s a fun one. A second one is 4 Disciplines of Execution, which this is a basic business book that helps you set lead and lag measures. Lag measures are like revenue. It’s like creating a scorecard for your business where you’re figuring out all the activities you have to do to get to those goals. It’s a very strategic approach that simplifies the entire process. And then the last one, which I’m sure you’ve read is Malcolm Gladwell is the tipping point.

JC: Oh, yeah. I’ve read every one of his books. Absolutely. Look, I like outliers, too. Because I liked outliers. a tipping point was a classic. I liked outliers. Also, because it, it helps you understand that just what you see is not necessarily the full picture of the average of like, what’s plausible, it tells you what’s possible. And you know, in so many people, we live in a world of plausible, but we think in a world of possible. And that’s not always a good thing, right? Because it can be don’t get me wrong, right like that the real innovators and creators, they don’t know how to live in plausible they only live in possible. But if everyone does that, a lot of people are gonna be disappointed. Right. So I thought it was interesting how he captured how certain stats, you know, or certain people show you be like, Oh, look at that. But then you start doing the reverse math. You’re like, oh, well, that’s how they got there.

JC: The Canadian hockey league, right? 

JC: Yeah, like the birthday. I was blown away. If you guys if you haven’t read Outliers, you gotta read Outliers, and anything from Malcolm Gladwell will reach a tipping point. First, it’s a good foundational book, and then and then read his other ones I’d recommend

Matt: I love I love outliers. I mean, just the fact that for the audience out there, if you’re a little bit older, and you start a sport, and you’re older than the people in the same team as you, then you have a much greater success of making it farther along and up into the pros. It’s pretty good. 

JC: And you know, and actually, since we’re on a tech podcast, one of the examples he given there was actually Bill Gates, it’s like, well, you know, was was Bill Gates his big genius? Or was he in the right place at the right time and also smart. And so when you break that down, it helps you understand that certain people you may admire are still great, but they are not this insurmountable example that you couldn’t actually produce sometimes it’s just a matter of where you are when you are like what you’re you were born literally right yeah, you know, right time Right place, right situation. And then of course your intelligence has to play into that your motivation and things like that. You have to have them all but I thought that was super fascinating. So yeah, good one good and tipping point. Again, classic, it gives you the whole foundation everything you need to know for that. Let me ask question how can people watching I’m gonna ask you one more personal question Sure. Because you I like to hear I want to see I want to know a little bit about your childhood side here. You know, what is it that you wanted to be when you grew up like when you were a kid and then is this it and if not, how did you get to here from there.

Matt: Great question JC you know, I don’t think you can ever predict what’s going to happen like you look at Steve Jobs say you connect the dots looking back you know, it’s it’s famous. But when I was a kid, my dad was a salesperson, by the way he went to IU, I went to Indiana University, Kelley School of Business, I really looked up to him he’s the most humble follow through person ever like never forget to face and I was like, I want to do what he wants to do. So that’s how I initially got into sales when I when I graduated. And then I think every decade of our lives, your whole everything changes like what you’re going to do next. Right. So like that first 10 years versus the second 10 years. I wanted to get a big strategic mindset get into corporate strategy, start learning how to tell stories with Data and financial outlook and then now as Chief Business Officer, trying to figure out how to put the pieces together to build a billion dollar business. So I can’t say it’s exactly the way I figured it out. But it’s all exciting. And every 10 years, you feel like, you look ahead and you can’t be sure what’s going to happen in 10 years, you can plan for it. But it could be completely different.

JC: Yeah. And Omneky you guys, I think in the pre-show, you mentioned something about a round of funding. Did you guys explain that – did you guys get funded? Are you working on it? Sure. We

Matt: Just closed out a fundraising round in November. So we are hiring through our next stage of growth and bring on some amazing leaders and some of the best engineering and AI scientists across the world right now. So they’re all joining the team, and they’re going to help us build everything we’re talking about, to help our customers grow faster.

JC: Wonderful, wonderful. Congrats, by the way. I mean, that’s, that’s a big deal.

Matt: Thank you.

JC: How can people listening a reach get to the company site? And then be how can they reach out to you personally if they have more higher level bigger deals to propose?

Matt: Sure. So you can reach out to me at Matt at Omni au, or Matt Squale, on LinkedIn. And you could also just go directly to our website and schedule a demo and then put in the notes there that you heard us on The Future of Biztech.

JC: Cool, yeah, let me know if anybody comes out there. I will. Awesome. So for everyone listening out there. Again, if you liked what you heard today, be sure to subscribe to this podcast, give it that five star rating with a little bit of comments on it, so that other techies like us can find it and enjoy hearing all about these new amazing and helpful. b2b software’s like Omneky. Matt, thank you so much for being on the show. I really appreciate it and I look forward to talking to you off here too.

Matt: Thank you so much, JC it’s such a pleasure. Bye bye.

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