Matt Swalley, Co-Founder and Chief Business Officer at Omneky, an AI-powered ad platform, sat down with Mike to discuss the possibilities of AI in advertising and how businesses can maximise the benefits of AI-generated content in their campaigns.

He also shares why testing is integral to campaign success and why human input is essential when working with AI-generated content.

Listen to the podcast now via the links below:

About Omneky

Omneky is an AI-powered platform that uses state-of-the-art deep learning to create and personalise creative content across customer touchpoints. Machine learning algorithms analyse designs and messaging and these insights are used to generate the content most likely to drive sales.

About Matt Swalley:

Matt Swalley is Co-Founder and Chief Business Officer of Omneky. Matt brings 13 years of strategic leadership experience and has an undergraduate degree from the Kelley School of Business at Indiana University, and an MBA from Warrington College of Business at the University of Florida.

Time Stamps

[00:46.01] – Matt discusses his career and why he moved from a corporate to a start-up role.

[06:34.08] – What is Omneky? How does it help its customers?

[13:49.09] –Matt discusses the importance of testing ads and campaigns.

[15:22.2] – Matt explains why human involvement is a must in AI-generated content.

[18:02.00] – Matt shares some use cases of Omneky.

[23:23.02] – Matt offers her marketing top tip.


“The best part about AI is people’s jobs are not necessarily being eliminated. They’re being changed. People can think much quicker on concepts and stuff.” Matt Swalley, Co-Founder and Chief Business Officer at Omneky.

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Transcript: Interview with Matt Swalley – Omneky

Speakers: Mike Maynard, Matt Swalley

Mike: Thanks for listening to marketing B2B Tech, the podcast from Napier, where you can find out what really works in B2B marketing today.

Welcome to marketing B2B technology, the podcast from Napier. Today I’m joined by Max Swalley. Matt is the Co-Founder and Chief Business Officer of Omneky. Welcome to the podcast, Matt.

Matt: Hi, Mike, thank you so much for having me really excited to be here.

Mike: It’s great to have you on. I’m really interested in about your career. And in particular, you know, you’ve recently jumped from a very corporate background into a startup. So tell me how you got to AT and T and then why you decided to change and co founder, I’m lucky.

Matt: Yes. Sounds great, Mike. So I spent 13 years at large corporation, at&t and I did a lot of different roles. And what’s one of the best opportunities of working for you know, as a fortune 10 company for many of those years with 250,000 employees is, you get the opportunity to a lot of different things. over the 13 years, I did probably 15 different jobs and lived in eight different markets, some of the biggest markets in the US. So Dallas, Atlanta, Southern California, where I lead sales teams, and the earliest days I was carrying a bag is what they called it, where you’re picking up the phone and calling you know, 50 customers a day setting up primarily new lead generation through calls and emails. And that kind of will go into my discussion later about how digital needs to be the base today. But I learned a lot about meeting with 1000s of customers learning how to ask questions, selling is all asking questions. And then I took that on and expanded it into leading teams in Southern California across like the biggest territory. And then I took on some leadership roles in mobility applications. So selling software for at&t, like GPS tracking about a bunch of their software services. And I made this decision, I want to get to headquarters because all decisions are made in headquarters. So that was one of my biggest transitions was moving to the headquarters in Dallas, Texas, and get into be around the leaders I led a sales organisation in Dallas initially and then became a chief of staff for the global business officer who ran all the multinational relationships for 18 T communications. And it was a really, really great big picture moment where I was getting to see big, big p&l hiring in every region of the world. We had customers in London in the UK, Japan, every single region. So learning a tonne about multinational companies and how you know how to sell. And then I got my MBA during that. And this was like my second career defining moment there was I made a decision, I want to get into corporate strategy. So I got into corporate strategy day PNP spent two years doing financial analysis, go to market strategy Board of Directors materials, and learning how to work with big datasets and tell stories for senior executives and the board of directors. And during that time, I got really excited about technology and growth stage companies, especially in artificial intelligence. And that’s where I met Hikari singe the CEO of Omneky who is the best visionary I’ve ever seen. He was years ahead, knowing general AI was going to get to where it is today and joined him on that journey. At a early early stage startup at the time, had raised a little bit of seed money, right when I joined, but we primarily bootstrapped and almost profitable in the early days, where Hikari was running most of the different operations from sales to engineering, and I joined as the business leader about two years ago from today.

Mike: Awesome, congratulations. I’m really trying to dig a bit deeper way to this this jump I mean, you’re AT and T you at the headquarters, you say presumably in a well paid secure job. I mean, I think a lot of listeners will be interested now. How do you find that courage to jump to something that appears so incredibly risky?

Matt: Yeah, so I always had kind of entrepreneurship in my heart. So like the earlier my job before 18 T, I spent at a small business where I ran an entire territory for a small uniform company in Chicago. But I always had this like business development opportunity where I love going out and making things happen myself, the hardest thing about working for a large corporation, you learn how to execute very well. And you get to sell established products most of the time and you have greenspace customers where you already have the relationships. But a lot of times you’re not able to go figure out how to go to market, how to go sell a product, how to grow a business. And then the second biggest thing is is when you look at revenue and future projections, I really want to join a growth stage company where we can make a huge impact and we’re a seed stage company with a goal to be, you know, an initial public offering in the next couple years. Some of the other industries are declining industry He’s in, when you’re in that situation, every decision is made an operational efficiencies instead of figuring out how to, you know, grow that next business unit 200 million or a billion dollars in revenue. And that’s where I like, I love startups, because every day you’re prioritising on what’s most important that will make an impact to help grow this business and, you know, develop our team and find customers that fit our value prop.

Mike: I love that. I think it’s, you know, it’s absolutely true. Most people find growing, that sales number is far more exciting and far more interesting than shrinking that cost number.

Matt: This role a lot of things I learned in the past, how to organise teams, how to I learned a lot of marketing, channel marketing, for example, how to sell with or sell through customers, we’re doing that a lot at arm to keep, they all are mission critical at a startup because a lot of leaders that startups are the most driven individuals, incredibly intelligent, know how to do so many things, but they haven’t worked at large corporations and figured out how to, you know, build that operational cadence and structure into the day. And that’s where you can immediately bring that knowledge from dealing with eight different levels and figuring out how to navigate the political environment and everything and you can, you can really simplify that all and then start building that into startup.

Mike: That’s awesome. I love your enthusiasm around nominee keys. So do you want to talk about what I’m Nikki does, I mean, I got from the website, you’re the omni channel creative orchestration platform, which is a bit of a mouthful, I think it probably needs some explaining.

Matt: Let’s just say AI powered sales. And when I say that is digital advertising has to be the base for all sales. Primarily listeners here are in the B2B field. So in the past, you used to figure out ways to develop business from meeting in person making phone calls and emails, well, what we do is we tell businesses stories in different ways. So you have all these four different major criteria I keep going back to, you have different audiences for your product, and B2B, it could be a different vertical, like retail, you have different products and services. You also have different geographies with like localization, you could be based in the UK or based in, you know, Dallas, Texas. And then finally, you have different platforms. So this could be websites, or social apps, or a number of different things, people’s attention spans keep getting shorter and shorter. So you can go follow your customers to wherever they are on different websites or apps and tell your business’s story. That’s what Omneky does. We tell your story in a lot of different ways, formatted for each platform. And then you can target and retarget those audiences. And lead generation is a major, major one of our focuses, especially for us, because we use digital ads for our own growth.

Mike: That’s interesting. So what you’re doing is you’re kind of taking that story from the customer. And then you’re being able to tell that in emotional, different formats on different platforms, different sizes. Is that really what you’re doing? You’re kind of doing this? It seems almost like repurposing on this massive industrial scale.

Matt: Right? Yeah. So it’s called multivariate testing out there and marketing. And you can learn a lot from the data. So one step back on on McKee is we collect data from a lot of different places. One is third party data from advertising platform. So if you’re advertising and have a couple of weeks or months worth of data, we can analyse like how many people are clicking for each of the different things, clicking or buying or generating a lead, or we care about qualified leads the most, so you can go farther down the funnel. But then you can use this tool called Computer Vision, which has been around for a long time, but it’s getting better and better as well. It can identify different elements of the copy the image, the video, and then across all the people looking at an ad, you can start to like quantify, like what’s resonating? What’s the key headline for the audience, what’s the key video length, what’s and then you you can iterate off of what’s working well. And then with testing also, like, you want to spend about 30% of your advertising on brand new concepts and about 70% on iterating off what’s working, because the platform algorithms for like the major platforms, meta Google, LinkedIn, Twitter, for B2B are, the algorithms are constantly changing. And so you have to feel it with creative and then also targeting is becoming more restricted with GDPR, California Data Protection Act. So now creative is the major lever for distribution. So a lot of these platforms have really smart algorithms that recognise what people like and it will deliver an ad based on what you’ve been looking at in the past. And so the better creative you have that hits their needs, the more effective

Mike: so it’s interesting. So you’re creating these ads, images, text, etc. And you’re looking at two things you’re looking at how really to get preferred in the algorithm, but also what works in terms of what drives drives leads. Is that Is that really what you’re trying to combine?

Matt: That’s right. So it’s a data based approach. And then also testing of new concepts. And one of the beautiful things with AI is like, is advertising still overall is too general, everyone talks about personalization, but there was broadcast before one ad reaching millions, then it was narrowcast, a little bit more narrow. And today you are entering a place where technology allows you to be so agile, it can be more and more personalised, it’s not gonna be exactly personalised yet. But it could fit the audience, the vertical, the, like I mentioned, the platform, the product, they will piece those all together, and then deliver to the right set of small narrow customers that you’re trying to get to. And you have to tell it across images and videos, and you go test what’s working, and then raise budgets on what’s performing well, and continue to iterate off of it.

Mike: So let’s talk a little bit about what it feels like to be a user of Omneky then, I mean, how does someone use the platform? How do they they create content? And then how do they control where it goes? Because it sounds like it can be going in a huge number of different channels.

Matt: Yeah, Mike. So this is some of the exciting things of technology is bringing as well. So when you onboard, we have a platform. So you register on Omneky, and we have within our platform, you upload your brand assets. So the first guardrails, our enterprise has very specific brand guidelines, we stay within those. So you give us your fonts, your logos, your brand guidelines, in any raw assets that you have, you could have 1000s of assets, a lot of these big brands have so many assets. And what’s beautiful to with technology right now is on Nikki’s built a brand large language model that will like categorise and scan all the different assets in the library, and then make it really easy to go pull from them for different ads. So that’s step one. The second is we connect to the advertising platforms for data. And then we have an immediate six month history of what’s been performing well. So we look at that look at the criteria across all your platforms that you’re advertising, Maddow Google, LinkedIn, Twitter, we look at it as a single pane of glass view, figure out what’s been working. And then within four days, we’re delivering a first set of ads. And that’s getting shorter and shorter timeframe, it’s a really quick turnaround, from onboarding to like four days out. And then it’s a constant feedback loop of within our platform, we deliver ad creatives, once the customer approves them, they’re launched into the platforms, we’re collecting data and then iterating, in real time off the data.

Mike: I say interesting. So you’re building these models? I mean, obviously, an important part of that is defining the audience. How do you do that? Because I think a lot of marketers find it quite hard to go from having an audience definition to seeing what that means really, in Google ads or on Facebook or on LinkedIn?

Matt: Sure, so you want to test two different things. So one is your testing actually defined audiences. So let’s just give an example. You could pick different criteria of what you believe it’s a good fit on the platform, you launch ads that are uniquely created exactly for that audience. The second one is you also want to use the algorithms that like performance Max and Google, for example, that just optimise on their own. So two different strategies there, you figure out what’s working better there. And you know, a lot of times those algorithms that you’re utilising with the platform that aren’t just making a narrow targeting outperform the ones that are, you know, defined audiences. But really, you understand the customers belief for ideal customer profiles, and then you can go test each one of them. And then you might uncover some new ones based on the data, which is what we you know, we do as a company as well.

Mike: Fascinating. I think you keep coming back to talking about testing as well. And and you came up with this stat earlier, that is 70% of your ad budget should be placed on the on the sort of existing ads and and 30% on testing, I think you said, can you just unpack that and explain why you think that’s important?

Matt: Yes, because still, like what we noticed across the market is there’s lots of different platforms you can test on. So one of the beautiful things with Omneky is we have integrations with all the major channels. So when I say testing new concepts, it might just be expanding to a new platform even right, so you might want to go test Reddit, or Pinterest or you know, programmatic, like the trade desk, but you only understand the history from what you’ve tried from data. So there might be new avenues like testing, you know, like I mentioned performance Max with a brand new set of creative that you were before just doing, you know, narrow targeting that are going to outperform and you want to have creative for each one of these. So what I’m gonna keep does is we put like a strategy in place across all the different types of potential going to market and then we have creative that aligns with each one of those and you want to test both video and images for each one of those videos is still like 60% of ad test. And then for companies that are doing it in house, a lot of times they might only have expertise in one place and what are the key does we bring in the ability to go launch and all these different places very Be very quickly with whatever assets you have.

Mike: Awesome. And I mean, you’ve talked about AI. You know, I think people are imagining that there’s, there’s some AI just firing out all these different versions. But actually, you also have real humans behind this as well. So tell us, you know, I guess what are the humans do? And then why do you feel you still need human input?

Matt: Sure. So the best part about AI also is, people’s jobs are not necessarily being eliminated, they’re being changed. People can think much quicker on concepts and stuff. So AI, and we plug it in, in a lot of different areas of the workflow. And, for example, for ideation, for humour, different things like that. So creators could potentially use it to figure out brand new ideas on concepts, we have images, pretty much automated, right? So you can pull in, you can use assets from like four different places. One is from brand assets, you give us all your raw assets, we can use those for ads. The second is AI generated assets. So the technologies keep getting better, we also have an AI team that’s refining all these processes and building your own algorithms. And then humans still have to review all the creative because AI is not perfect in any situation. So there’s always a finishing touch where human craters can can look it over and also use or scanning for bias, like generation one of these models had a lot more bias than generation two, right. And so it requires a human on the loop on our side. And then also on the customer side, you want to have two different checkpoints. before things go live, we have this approval dashboard, the customer could have, you know, five different approvers in there, including legal and compliance. You don’t want anyone anything going live until you know it’s got a stamp of approval that it looks ready to go. And then video, there are video tools that are amazing. And we’re working with some really, really cool technology we’re building. But video cannot be completely done through automation today. It’s not it’s not there yet. It can though. Plugin inputs help you piece together the story, what assets to use, but it’s still going to have to have a human that helps piece it all together. For the most part.

Mike: It sounds fascinating. It sounds like you’re, you’re using AI as an accelerant to really speed up what individuals can do to be able to scale at the kind of scale you’re talking about.

Matt: That’s exactly right. So like a lot of enterprise businesses are either like duplicating assets times, you know, 50 within a whatever programme they’re using, and then they’re changing stuff, or, you know, manually and what we’re doing is we’re making that whole workflow so efficient that AI can help power the different areas, the content and the images, and then click a button and you have all the different sizes you need and ready to go.

Mike: Cool. So maybe we can dig into some of the uses, particularly in B2B. I mean, does Omneky go as far as being able to do sort of, you know, Account Based Marketing campaigns where you’re, you’re focusing down on single big accounts or two people tend to use it for, you know, broader campaigns.

Matt: It’s typically more broader campaigns today with our success, like we use it for ourselves. So we have a number of different focuses. One is enterprise B2B. One is resellers agencies that are using our product. So each one of those has a specific advertising goal and a specific value prop and messaging, each one of them has different things. That’s where we plug in, we tell the stories for each of those specific audiences in different ways. You could, with enterprise, you could take it deeper into Account Based Marketing, where you’re focusing on one single account doing the ads, it’s just, you’re not going to have as much reach and as much data coming back because you’re targeting like one very small audience.

Mike: That’s interesting. So you need to you need that volume of data to be able to analyse what’s working, presumably.

Matt: That’s exactly right, the more data the better. So like, we recommend that the minimum like our minimum spend for testing is typically like $10,000 a month in ad spend. That’s where you’re getting enough eyeballs. And then when B2B that the other thing I wanted to mention is sales has changed a lot like people don’t pick up their phone, you’re getting 1000s of emails a day might and better say like, you know, schedule a demo, will advertising polls customers to you. And then you can figure out how you’re how you can start to refine your demo in your questioning and moving the process through the funnel in a different way. And so, historically, sales organisations had lots of people doing outbound and meeting with customers. Today, you can have a smaller team, that’s figuring out how like to deal with the incoming leads, route them in the right way, you know, don’t take meetings that don’t fit with who you can sell to, and then refining your value prop and pitch and questioning until you start to improve the ratio of sales close. That’s really the way we look at it. It’s like big deals coming to us. We figure out how to refine the process and prove efficiencies there. tell our story and better ways to drive more and then continually qualify and more Wow, that sounds

Mike: cool. I mean, maybe you can, you know, just paint a bit of a clearer picture. Do you have a couple of campaigns you can talk about that, you know, have really worked on on Nikki and delivered some great results.

Matt: Sure. So one specifically, we have a couple in. One is omni channel, the one you said earlier, Omni platform will call Omni platform distribution, this campaigns worked really, really well for us, because B2B marketers, and anyone in marketing has, as I mentioned, a big big challenge figuring out how to produce content for all these different channels. They might have expertise and just meta or LinkedIn, excuse me, but they don’t across all. So we’ve gotten tonnes of interest from all different sizes of corporations, including lots in the Fortune 1000 range from those add greatest. The second one is if you have any great live, like videos of explaining your product. So another one for us was TechCrunch. We were a finalist at TechCrunch. disrupt the CEO did a demo of that on stage. And you can repurpose all this as ads. So that was focused on really the the mid market enterprise space. And that performed extremely well, any of that content, you can have and repurpose, like right away. When we start having content like that a lot of times we’re repurposing his ads, and if they perform extremely well,

Mike: that’s great. I mean, I think great content always works well, doesn’t it? And any kind of AI magic is going to struggle unless you have that inherent good content start with.

Matt: That’s right. Cool.

Mike: I mean, you mentioned people need to check. You know, everyone’s gonna be wondering, we’ve all heard about AI getting things wrong. I mean, what are the main problems you find? When people are rejecting ads that have been generated by the system? I mean, what’s the AI doing to get things wrong?

Matt: So some of the things that we see is one is, and this is what we see is one of the major challenges with AI, a lot of times it will repeat the same things over and over again. So you have to figure out how to ask it the prompts and different ways to generate different emotional responses or different ways to, you know, tell your story. So that’s one thing we’re building there. The second is a lot of the image generations in the early stages are not perfect. So you can train AI on what a product looks like, you could have a, you know, a specific product that has your brand logo on it and everything, when you’re just trying to regenerate that in completely new situations, a lot of times, the text on it doesn’t show up, right, there’s a lot of challenges. So now, you know, what you’re doing is you’re figuring out how to make that exact product or service appear with whatever the production is you want without production, manipulating the backgrounds in different areas or putting into videos with overlays. But a lot of times the biggest challenge was not getting things perfect. And then you have to figure out other ways of doing it that will make that area of it perfect.

Mike: That makes sense. So so it’s it’s not necessarily going for some really crazy disastrous failures, it’s much more it’s not quite perfect. And, you know, clearly brands want it to be perfect.

Matt: The brands want to be perfect. And that’s still why you need a human touch point in there for a lot, especially for the enterprise space.

Mike: That makes sense. This, this has been fascinating, man. I mean, one of the things I’m intrigued with is, you know, you’re obviously not actually drilling from a marketing background. We’re talking a lot about marketing and marketing technology. I mean, what’s the best marketing advice you’ve ever received?

Matt: Yeah, I was actually a marketing major, believe it or not back in the day, and then went into the sales path, and then corporate strategy, and then transition to marketing. But some of the best advice I’ve heard is just start testing. Like, even with whatever, you know, I mentioned, you have to have a pretty good budget. But you can learn so much from getting 1000s or millions of eyeballs on something that could take a team, you know, months or years to realise your product might not sell the way you believe it’s going to so you can just start testing. The second one is with AI the way it is today, try out as many of these tools as you can, that are available out in the market. Like, I’m sure you do this to Mike. But every morning, I review a newsletter I love about AI, I look at the 10 newest products on there. And I go test one or two of them. Because eventually you start to figure out how to piece all these together and figure out what helps us for what we’re building but to it helps you understand the big picture of how all these pieces can fit together. Because we’re at this stage right now, where AI is the first initial wave of it here after chat GPT got launched in you know, the open initial open API’s. It was a cool factor. It was like this is cool. This has never been done. But it wasn’t completely solving a business problem. Now we’re entering the stage where businesses are getting to the point where they’re solving business problems and beginning to learn how to scale those problems. test as many of the tools as possible.

Mike: I think that’s great advice. I mean, there’s so many AI tools that you look at and you see the script, you think Oh, that’s amazing. And then you start playing with it and you go Yeah, I’m not sure how it’s gonna help me. And then the cost of

Matt: compute star I’d say add up to with anything with scale, like you can try it with a small scale. But then once you start to like, do it a larger scale cost a lot more money.

Mike: Yeah, definitely. I mean figures? Well, you know, I mean, you obviously started in marketing, you moved out of marketing, you’ve kind of come back a little bit into marketing. I mean, you’re more business than the marketing still. I mean, do you recommend young people look at marketing as a career? Or what would you do? If you were starting again? Would you take that marketing major?

Matt: Yes. So I would, growth is one of the biggest roles if you want to join a startup, it’s going to be a role that comes in more like its series, a stage head of growth, but head of growth has to understand marketing direct partnerships channel, they’re kind of that overall marketing person that’s in your company. And, and I have learned so much in the last two years from talking with eight customers a day sometimes or prospective customers a day might I hear I hear feedback from all these agencies, enterprise companies of what the business problem is. And I look at the world completely differently on how to go to market now. You have to figure out how to synergistically combine all your different direct outreach with retargeting with ads. Otherwise, none of it works. If you’re not your PR is not firing away with news, your ads aren’t going and your direct is not going. So yes, I believe it’s a great base, but you also want to go try out different areas of the business because it gives you a much wider view of strategy.

Mike: Definitely, I think it’s good advice. I mean, I’m very mindful of time. I’m in tricks, though, you know, the platform I’m Nikki seems to have so many different capabilities. Is there anything else you’d like to talk about or highlight from the platform that you think we haven’t covered yet, Matt?

Matt: Sure. So one of the really exciting things we’re working on right now is, is of course video and figure in, there’s some really great AI tools that help tell different languages, transcribe what’s on it. And then really exciting to is these virtual avatars. So one of the things we’re we are working on right now is you can write a script and everything will follow our company’s specific product. And then you can immediately create a virtual avatar that tells your story that can go on ads. So I really am excited about this technology, as we’re, as we’re developing it as another, you know, another area from testing for for ads.

Mike: Oh, that’s cool. I mean, we we’ve been playing with some of that technology as well. And I think it’s certainly at the moment, it’s very compelling whether people will, in the longer term get to be able to spot you know, who’s a real person who’s not? I don’t know, that’s an interesting question.

Matt: Right? I know, it’s gonna be interesting, because it went from like, user generated content to you know, there’s a lot of different people that can go tell tale product stories to now. Virtual.

Mike: Exactly. I mean, Matt, it’s just been amazing. We’ve we’ve covered so much, it feels like we’ve only scratched the surface of Omneky and your experience, but it’s been fascinating. If anyone’s listening or they’d like to get ahold of you, what’s the best way for them to contact you?

Matt: Sure you if you want to get a demo, and on occasion, go to and schedule a demo and put in the code you heard about in the marketing B2B technology podcast. That would help and then or you can reach out to me at Matt ma TT at Or find me on LinkedIn.

Mike: That’s awesome. Matt, thank you so much for sharing all your knowledge and the information about Omneky, I really appreciate it.

Matt: Thank you so much might been a pleasure.

Mike: Thanks so much for listening to marketing B2B Tech. We hope you enjoyed the episode. And if you did, please make sure you subscribe on iTunes, or on your favourite podcast application. If you’d like to know more, please visit our website at Napier B2B dot com or contact me directly on LinkedIn.