Episode Transcript
Announcer 00:00:08 Welcome to the Breakout Growth Podcast, where Sean Ellis and Ethan Garr interview leaders from the world's fastest-growing companies to get to the heart of what's really driving their growth. And now, here are your hosts, Sean Ellis and Ethan Garr.
Sean Ellis 00:00:26 All right. In this week's episode of the Breakout Growth Podcast, Ethan Garr and I chat with Ben Yeager, vice president of EMEA at Moloco. So, Moloco provides machine learning-based advertising solutions that help advertisers reach prospects outside of the walled gardens of Google Meta, also known as Facebook <laugh> and Amazon, and, and obviously Instagram and, and, and others in the meta mix there. So Ben explains that those companies are really great at driving performance. So anyone who's, who's used any of those media properties on the advertising side, you have a lot of controls. They're almost automated in the sense you can, you can put a, uh, a, a target cost per acquisition, and they will automate their way into finding opportunities to drive that, uh, cost per acquisition for you. But getting that same type of control and performance outside of those big media properties has been really tough, and that's what these guys are addressing. So they're, they're going beyond the walls of the big three to br bring performance marketing opportunities that are on a, uh, similar level to what we see in the big three. So, Ethan, what did you find most interesting about this conversation?
Ethan Garr 00:01:34 Yeah, I mean, there's a huge world beyond the big three. So I think this is, uh, this is really relevant and exciting for our audience. But, you know, Sean, we're at such an interesting time in the world of tech because of ai. Half the news is telling us how AI is gonna make our lives and work better. The other half is telling us how it's gonna take our jobs and probably murder us in the middle of the night. But here's a company that's built massive success, five x growth in the last two years with machine learning at its core. So this is really, you know, it became a conversation about outcomes and what machine learning and AI can actually do to help businesses achieve their goals today.
Sean Ellis 00:02:08 Yeah, I just, I just finished up a couple of speaking tours, and it's literally ai, ai, ai, <laugh>, almost every question I get, all the conversations around AI and, and the hype is understandable. I think it is gonna be super transformative to growth, to marketing, to, to business in general. Um, but, you know, ultimately it is about driving results. And I was excited with this conversation because Ben really brought the conversation back down to Earth. He works in performance marketing and using, uh, machine learning, which a, a, a form of ai it, he, he really, uh, he's, he's focused on those outcomes and, and driving good results. And you can't hide from results when you're doing performance marketing. So, um, one of the things that I thought it was, was particularly interesting was that Moloco still uses machine learning in most of their messaging, where if, if you really wanted to like tap into the hype cycle, you'd probably update everything to, to say, yeah, we're an AI driven platform that's gonna help you drive those results. But I think they're, they're just so much more focused on driving the results, and it really seems to be serving them well in, in building a successful company.
Ethan Garr 00:03:14 Yeah, for sure. I have to talk you down from the, uh, calling growth hacking, AI driven growth hacking. No, I'm just kidding. <laugh>. But, uh, <laugh>. But I think, yeah, ulti, ultimately, performance marketing is about optimizing every element of reaching people at the right place at the right time with the right message and machine learning augments that, you know, augments what smart human beings can do to actually achieve that Moloco’s model. I think it makes 8 million predictions per second to get it right. Yeah,
Sean Ellis 00:03:40 That blew my mind. <laugh>, I know
Ethan Garr 00:03:41 <laugh>, and when they, when they, when they do that, when they get it right, they are creating real value for advertisers and consumers.
Sean Ellis 00:03:48 Exactly. So I, I think the, uh, the relevance to the larger AI discussion in the world is, is going to be super interesting for our listeners. But that was really only one of the things that you and I took from the conversation that, that we got excited about. You know, I, I think we both honed in on the fact that, uh, he is the VP of emea. So, uh, for anyone who isn't, isn't familiar with that acronym, that means Europe, middle East, and Africa, and focusing on pushing a solution out in very different regions. Even, even the countries within Europe tend to be pretty different. But across those regions, I think there was a lot of interesting learning there as well. And they've had, you know, it really helped advertisers in each of those markets reach customers through mobile, mobile apps and, and gaming in particular. But not only is he expanding regionally, he's also working to, uh, expand into other markets like retail, food delivery, e-commerce, and, and pretty much anything you can think of to bring that same, uh, performance marketing, uh, that, that we've come to love from the big platforms to, to the broader web.
Ethan Garr 00:04:56 Yeah, I mean, the expansion story here is definitely, um, it's, it's definitely interesting and I think it, you know, both of us left, we, you and I can always judge how, how, how good these, uh, podcast episodes are gonna be by our enthusiasm af in our post, uh, debrief. And, uh, we were, we were pretty excited about this one. So, uh, you know, I mean, Moloco’s on Tear, uh, they have a valuation north of $2 billion now. Uh, their founding team sounds pretty brilliant with experience from YouTube, Google, and Oracle, and they're really extending opportunities for performance marketers all over the world. So I think there's a lot to learn in this one. So, uh, what do you think, Sean, should we jump in?
Sean Ellis 00:05:31 Yeah, I just, you know, you talk about that valuation, but I think it's also the growth rate. What, um, you, you had mentioned a stat to me of, of they were one of the, was it top 10 fastest growing, uh, companies in Silicon Valley based on, I think the Inc 5,000, uh, latest report?
Ethan Garr 00:05:48 Yeah, it was something like that. I mean, it was, it was a pretty staggering, you know, uh, to stand out the way they did. I, I don't remember the exact statistic, but to stand out the way they did was pretty exciting.
Sean Ellis 00:05:57 Yeah. And I think in particular, with having AI as part of their solution that they're offering in a business to business context, to be able to drive that growth rate and those valuations, the sky's the limit on this business and, and many that are tapping into these technologies. So, um, I think everyone's gonna really enjoy this episode. I wanna just acknowledge that it's been a while since we put an episode out. Oh,
Ethan Garr 00:06:22 We've been busy <laugh>.
Sean Ellis 00:06:24 Yeah. We've both been heads down working in, uh, very fast-growing companies. And I think that's, that's, uh, one of the things that helps us add value to these conversations is that we're, we don't just talk about growth, that we actually spend a lot of time, uh, rolling up our sleeves, executing growth and, and moving beyond the theory to what, what practically matters and works. So hopefully you'll pick that up as we have this conversation, but let's dive into it.
Ethan Garr 00:06:47 Sounds good.
Sean Ellis 00:06:57 All right. Hey, Ben, welcome to the Breakout Growth podcast.
Ben Jeger 00:07:01 Good to be here. Thank you, Sean and Ethan.
Sean Ellis 00:07:03 Yeah, as you mentioned, Ethan is here as well. So I'm joined by my co-host, Ethan Garr. Uh, good to see Ethan.
Ethan Garr 00:07:09 Yeah, good to see you too. Nice to meet. Nice to meet you, Ben, in person. Uh, unfortunately you only have part of me, as you can hear. I have a little laryngitis this week, but, uh, I'll do my best to power through.
Sean Ellis 00:07:18 Some might say that's a good thing, Ethan. I'll talk a little less and listen a little more. So, um, that's, uh, I think
Ethan Garr 00:07:24 Our Audi, our audience saw that one coming from a mile away. <laugh>,
Sean Ellis 00:07:28 I may have slipped Ethan, something to give him some laryngitis. <laugh>, slow him down a bit. <laugh>. Um, cool. Well, uh, let's, let's jump right into it. So, so Ben, um, you are the vice president of E M E A at, uh, Moloco, did I pronounce it correctly? How do you, how do you guys pronounce the company name,
Ben Jeger 00:07:46 I guess Moko. M O L O C O.
Sean Ellis 00:07:50 Okay. So, um, yeah, there's a lot of questions that I want to ask about. You know, I know, uh, that, that kind of the hot topics these days are, are AI and machine learning. And, um, I, I just got back from a speaking tour in Brazil, uh, and, and whenever I'm doing a podcast interview, one of the first questions people ask is just how, how is, how is AI in particular, but machine learning as well, impacting growth and how we're, how we're gonna approach our, uh, jobs in the future? And the, the truth is, I <laugh>, I really dunno too much. You're more likely to be an expert in those areas than me, so I'm excited to, to dig into that with you. But I think it's important for our audience to do a little bit of background first. And you can, you can talk a bit about what the company does and, uh, you know, what, what kind of customers you serve and, and, and maybe the outcomes that you, you help to deliver.
Ben Jeger 00:08:41 Malco is a machine learning company. Initially, the founders had M l c machine learning company as, as, as the name, and then added the OS to make it more pronounceable. Um, and, and what it, what it is that we do, um, is, uh, in performance advertising, make sure that we are driving return on ad spend for advertisers. And we, we are specialized with our biggest and, and first, um, business line is, is the D SS p a demand side platform where we help, um, app businesses acquire new users. And the company has been around for, is celebrating its 10 year anniversary. So it, it, uh, it's a bit of a overnight success that took 10 years. Our, our founder, uh, we, we have founders from, um, uh, ex Google and Oracle and, and Ihin, our c e o, he was one of the first machine learning engineers at YouTube. He, um, developed the monetization algorithm for YouTube as in, uh, machine learning engineer, and then thought, okay, I can take this and democratize, um, this technology and help other businesses grow. So this is what we do. Um, and we've been doing it quite successfully, um, in the last, uh, two years growing more than five x, um, which is extremely impressive.
Sean Ellis 00:10:20 Yeah. And, and how big is the overall team?
Ben Jeger 00:10:22 We're more than 500 people now. Okay.
Sean Ellis 00:10:24 Sorry, have you said that? I, uh, I meant suddenly my pen stopped working So <laugh>, I was just like, <laugh> randomly searching for another pen, but now I gotta work it again. <laugh>. So over 500 people. Okay.
Ben Jeger 00:10:34 Yeah, over 500 people. Um, half of them are actually machine learning engineers, um, data scientists and, and, and, and the rest are, uh, the, the people like me are trying to make something
Sean Ellis 00:10:52 Outta that <laugh>. I'm hoping to let people take advantage of it. Smart people <laugh>.
Ben Jeger 00:10:56 Exactly.
Ethan Garr 00:10:58 Yeah. So, uh, yeah, the growth has been incredible. I saw you guys have a valuation north of $2 billion now. Um, and as Sean was saying, like all the rage everywhere we go these days, everything's about ai. I've been working with a, um, a team doing generative AI in the DevOps space. I mean, it, it's permeating everywhere and obviously machine learning is an AI are closely related. Um, do you guys consider yourselves an AI company? Or like, is it really machine learning and maybe like, how do you, what do you see as the difference or, or relationship between those two?
Ben Jeger 00:11:29 So AI is the umbrella term, and machine learning is part of ai. Uh, AI is any, anything that, uh, tries to, uh, emulate human intelligence and teaching computers to behave like humans and, and, and act, uh, and, and achieve outcomes like humans. Um, and ML more specifically is, um, the field of teaching using algorithms and data to teach a system to, uh, self-learn and produce, um, outcomes that otherwise, uh, couldn't have been, um, designed if, if, if the, if, if the person that is writing the code, uh, couldn't actually, uh, achieve this, these type of results themselves, the system is improving and getting better than the human, uh, that is designing the system. So if you think about it in, um, playing chess, so there's, there's a level where you can, to which you can play chess, but if you are very strong machine learning engineer, you can teach the system to, to teach itself and eventually become better than you. And you obviously couldn't disruptively, uh, explain the machine how to beat yourself, but you can teach it to teach itself and then beat you your, um, and that's kind of how machine learning works.
Ethan Garr 00:13:09 Gotcha. And I guess in the world of performance marketing where you just have huge data sets to work with, I guess that's really where that leverage really comes into, into play, right? Like nobody could take all that data and manually, uh, come up with the best outcomes for advertisers on their own, but teaching the system to learn, uh, can then essentially augment the, the knowledge that the programmers have themselves, right?
Ben Jeger 00:13:38 Absolutely, absolutely. And we're talking about huge amount of data. Um, so when the, the scale that that we are at, we, our D S P is plugged into 35 different exchanges, and, um, we're receiving about 6 billion bid requests per second. Um, and, and the machine needs to, uh, make decisions in less so. So the, the, the, it's a real time bidding auction, and the machine needs to respond in less than a hundred milliseconds. We take about 50 to 80 milliseconds to answer, and we need to make a decision on what ad creative should we show, uh, what ad format is most suitable, and then what is the, the appropriate bid price for this specific impression. Um, and it's, it's unimaginable, right? Uh, the, the scale and, and the speed at which these systems operate.
Ethan Garr 00:14:41 So I just wanna ask one more related question to that because, uh, I was reading an article just coming into this conversation about Moloco and trying to better understand what you do. And one of the things that struck me is that it seems like an area where you are really trying to differentiate yourself is in terms of ad relevance. You know, I mean, ads are, you know, let's say it's on a, you know, they're sold on a C P M basis. There's this idea, you know, simply, you know, trying to optimize for the immediate value of, you know, who, like, who gets the, who, who's bidding the most is one thing, but ultimately the suc the long-term success is gonna be on the relevance of that, of that ad. Is that a a, is that really a big part of what you're training, trying to train your machine learning algorithm to do? Is to not just look at one parameter, the, the, the dollars and cents, but look at the long-term value to the end user so that you make long-term a lot more value for the, for the advertiser?
Ben Jeger 00:15:38 Abso absolutely. Everything that Moloco does is about value creation. Um, and, and that's, that's the beauty of performance marketing where, uh, the incentives are aligned if we do not deliver performance and performance in this instance means return on ad spend. So if we don't return ad dollars back, we did, um, to, to, uh, the advertisers then dollars, uh, ad budgets shift to other pa uh, other players. And so the only way we can sustain and grow is by actually delivering value, which means long-term outcome. Like buying ads from a loco is, is like an investment. You, you, you pay X and you expect to get X plus, um, back, um, out of it. And if we can't deliver that, then people won't continue to buy from us. Um, so yes, we're very much focused about, uh, on, on, on going beyond, uh, just showing the highest paying, um, ads to the person. It, it needs to be, uh, we, we, we need to show the ad to the person that we believe is, is the most relevant and, and is the per the, is has the highest user value for this specific, um, advertiser.
Sean Ellis 00:17:07 And do you feel like, um, that, that just like on, on the AI kind of side, that it's, it's just in such like a hype cycle right now that people are, people are focused on, on that just because everyone else is talking about it and there's like, how's this gonna help my job? Is this gonna take my job away? Um, and and they should really be talking about machine learning, or, or should it really just be yeah, outcome focus. What are the outcomes we're trying to accomplish? What are the tools to accomplish those outcomes? And, and, and kind of the, the technology that drives those outcomes is the name of that technology doesn't really matter that much. What, what, how, how would you kind of, uh, <laugh> differentiate between those things? It's
Ben Jeger 00:17:51 A good question. One, one is like marketing the company or the business. And, and, and you rightly pointed out before we went online that we don't mention AI too much on, on our website. I'm torn be because I'd, I don't know. I think potentially there's value in, in, in saying, and we wouldn't lie if we say that we are an AI company because as I, as I said, AI is an umbrella term, and machine learning is, this is a, um, category of, of ai. Um, but I, I think the, the, the vast majority of people, um, do think about it like you just described. There's, there's an engine that gets me from A to B, and I don't necessarily, there's some people that really care and look under the hood and want to understand the, exactly the mechanics of, of the engine, but most people want to get, um, from A to B in a comfortable way, in a reliable way, um, and what exactly the technologies that drives it is less relevant.
Ben Jeger 00:18:57 And, and I think it's the, the same is true for us. If we, if we throw around fancy words but don't deliver value, it doesn't really matter at all. And we couldn't, we couldn't achieve continuous growth. So really focusing on, on getting the outcomes that advertisers, um, need is, is all that matters if you playing the long game, if you wanna like jump the, the, the, on the hype. But, but as I said, we we're, we're 10 10 years in the making, so we're about to celebrate our 10 year anniversary. Okay, yeah, yeah. At mocco. Um, and, um, so it takes a long time to do this well and do it right. For the first five years, years, I years, I don't think Ma Loco made a cent. And, uh, and only five years in we started to actually, um, make revenue and then grow, right? Because it, it's complex. It's, it's really, really difficult to do.
Sean Ellis 00:19:56 Some might say that, that you, uh, hit product market fit at that point, I'm assuming <laugh>,
Ben Jeger 00:20:02 Yes.
Sean Ellis 00:20:03 I think this, this question of, uh, or this, this outcome focus that you have, where, where really what you're doing is you're, you're leveraging machine learning to drive better return on ad spend. And in, in the world of, of competitive bidding, which everything's turning into, even if you buy C P M, it's, you know, it, it, it really all comes down to if you, if you don't get that return on investment, you can't sustainably, uh, invest money there. And so, um, if, if we kind of play that out for a while and we start to say, all right, if, if, if a tool like Moloco is, is able to drive better return on ad spend, make you more competitive, then the ones that are really going to be competing for, for all the top spots are gonna be leveraging something like, like your tool set.
Sean Ellis 00:20:51 Um, how does, how does that start to kind of play out long-term? Um, is, you know, I've, I've seen companies kind of all over the board in terms of leveraging technology, including companies that are, you know, six and seven figure a month spending on ads with no even tracking of return on ad spend, let alone having the tools to optimize that return on ad spend. Um, but, but clearly, clearly, you know, the a again, the more you can have a positive return on investment and then really scale that spend, that's, that's how you, how you buy market share and you, you own a market. So do you have thoughts in kind of how, how this starts to play out in, in the next few years as, as more and more companies leverage, uh, leverage machine learning in their, in their approach to, uh, performance marketing?
Ben Jeger 00:21:38 What happens is that it, it gives the opportunity for the best products to rise to the top because underlying is, is an, an in, in our case, we're advertising certain apps. So if the app itself is not, um, attractive to users isn't, um, is and, and so isn't delivering the utility or entertainment or whatever, um, it's trying to drive, then you can have the best, uh, machine learning to actually try and, um, to get users, uh, in, in the door. But if you can't keep them and maintain them, then, then that's, that's nothing can help you. So the answer is, uh, a long-winded answer is I think machine learning has the potential to level the playing field and allow the best products to rise to the top. That's maybe an idealistic view of, of, uh, a, a potential future, but I think there's something there.
Sean Ellis 00:22:47 Yeah, I, I, I think you're right. And I'm really glad you touched on, on kind of the, the quality of the product experience as, as being a, a major factor. If you're, if you're just really efficient at, at reaching customers and, and driving that return on investment, but your ability to convert those customers to a, to a, to a great experience in a product that delivers on their need, um, is, is limited. You're you in the long run, you're not gonna be able to, to build a, an effective business. And so, um, in my experience, I started in the performance marketing side of things, but I quickly found that a lot of investment in, in activation. So how do you, how do you get a new customer or a new prospect to the right experience than the product was really where I had a lot of leverage to become a lot more competitive in those channels. So is is that an area that you, you guys also work in or do you have like other oth other tools that you integrate with that are, that are effective there, or, or how do, how do you kinda work in, in the stack that helps someone be ultimately really competitive in, in reaching the right prospects and converting them and, and, and building market share?
Ben Jeger 00:23:58 For the D S P business specifically, we're very much focused on, um, the user acquisition aspect. So finding the right user for your product, um, finding people that look similar, look alike, the people that are doing well within your, um, product, and we're using your first party data to, um, train our models and find you more of what, of what you already have. That's, that's the, the, the main advantage there. There's, there's a second and third business line that we have that we have, um, our retail media platform business, which is, um, the, the flip side, it's, it's, it's allowing retail, uh, marketplaces, um, of all shapes and sizes, uh, to monetize, uh, the, the users. So, so create an ad, an ads business and having merchants, um, advertise and, and then create return on ad spend for your merchants on the platform. So it's using the same, um, performance marketing mindset and, and technology. Um, but here we're actually to some extent further down the funnel in the stack helping you, uh, generate, um, uh, a more profitable business rather than on the D S P side, we're helping you acquire users on the r and p side, we're actually making your product more profitable and, uh, yeah, high margin, um, ads, business creating and high margin. Yeah.
Sean Ellis 00:25:40 So it sounds, so it sounds, I, I know I just said, so Ethan and I kind of communicate offline a little bit, and I'm like, you are up, and so I'm gonna, I'm gonna take that back. So it sounds like that part that I talked about in terms of activation, companies still need to do that. Well, and it doesn't mean like one tool doesn't necessarily serve all the needs of a company. So just, just for, for our listeners out there as you, as you kind of think about how these pieces fit together, really efficient and, and well-managed customer acquisition is really important. It sounds like that's, that's where you guys play a really big role. Very good. Um, uh, revenue optimization is also really important, and it sounds like you can play a role for, for particular, maybe not SaaS, but for a, uh, ad supported company there.
Sean Ellis 00:26:26 And then, but just don't forget about that layer of, uh, you know, that often sits in between marketing and product that how do, how do you onboard that new customer to the right experience in your product so that ultimately they get to that aha moment and wanna come back more and more? And that's, and that's often more, more process driven in my experience, than it is necessarily tool driven. Yeah, there might be a lot of ab testing, which would require the tools, but, um, just, just to kind of draw the full picture of where, where do you really drive success in, in, uh, performance marketing? I think you, what you're doing is a incredibly important part of that stack, but, um, it, it's important to look at that big picture as well.
Ethan Garr 00:27:08 That's, I think that's a great way to tie that together, Sean. But also, um, I, I wanted to go back to one thing you said earlier, Ben. Um, you know, you, you mentioned that, uh, mal Malko is really able to use ML to sort of level the playing field. And I think if you think about this industry, I mean, it's been dominated by Google and Meta, right? For, for a long time. Do you see what you're doing as, uh, fitting in in a, in more of a niche? Or is it disrupt? Is it ultimately the goal is to disrupt that part of the, you know, that part of performance marketing that they've, they've dominated so well,
Ben Jeger 00:27:43 What, what sets, uh, Google and Meta, uh, apart from all the others is that they actually, um, are excel at driving, um, advertise, uh, the, the results that they're looking for. So return on ad spend and driving real performance is what, what made them, uh, grow to, to the behemoths that they're on today. And I think outside of, um, meta Google and, and Amazon by the way, who also have, uh, uh, a performance, um, ads business on, on, like, it's, it's similar to our retail media platform business, to be honest. Um, but outside of those three companies, then there's not, there's no one, um, that, that has the level of sophistication when it comes to machine learning in the, um, in the performance marketing space. So we, uh, we see ourselves as, um, outside of these world gardens, um, if you want to grow, and there's, there's audiences that are spending a lot of their time, a lot of eyeballs are going outside of meta and, and, um, Google in people are spending time in apps and, and on websites and so on. And if you're outside of, of these world gardens, this is where we see ourselves as, um, the, the real, uh, alternatives to, to drive performance and give you the same results that you're used to from these type of companies, um, in, in, in the open internet, so to speak.
Sean Ellis 00:29:23 So are you not, uh, like, how, how much of the business, I mean, not with like specific numbers, but how, how much of the, the ad spend that goes through you guys goes to these big platforms versus, versus some of the, the, the, the rest of the internet, um, is I'm assuming that you also integrate with AdWords and, and, uh, and, and Facebook.
Ben Jeger 00:29:46 No, so yeah, so we, we do not, so, so, uh Oh, you do
Sean Ellis 00:29:51 Not, okay, interesting. Sorry,
Ben Jeger 00:29:52 We don't see no, so No, no, no worries. I think it's good. Um, it's a good point you raised because I think it's important to clarify. We think that they know, they really know what they're doing, right? So I think it, it, it doesn't make sense for us to compete on, on their traffic. Um, and, and, and so, so besides the fact that they don't, they don't allow us to, if they were allowed us to, I think we would, we, we would give it a shot, but I think, um, as, as it stands now, that's why we, we call them walled gardens because there, there's only one you go in, but you can't let, they don't really, um, let external parties, um, buy or, or get access to the data and so on. So every, everything outside of, of, um, those world gardens is where we are acquiring users, and we are driving similar, if not better results for our advertisers than they can get, um, with Met and Google.
Sean Ellis 00:30:59 That's fantastic. 'cause I, I know personally when I'm working with a company, I tend to, you know, I, I tend to focus kind of the, the, the post click experience and then, and then either through external agencies or just internal experts within the business, they're doing a lot of the advertising management side of things. But it, uh, it, it, it seems that, that Google and, and Facebook really have dominated the, the ad spend of the, of the companies that I've worked with. And I think it's because they provide all of that data and, and obviously they have the reach, you have all of the intent that sits inside Google, and then, and a lot of targeting data that sits inside Facebook. But, um, to be able to, uh, to, to be able to leverage other traffic sources that combined are, are probably bigger than, than than Google and, and Facebook is, is really exciting as a way to expand, you know, a additional high return on investment opportunities.
Ben Jeger 00:31:59 Absolutely. Yeah.
Ethan Garr 00:31:59 Yeah, absolutely. So do, do you see customers coming to you, uh, should customers potentially come to you first or, you know, because there's, you see more opportunity outside of those walled gardens for them to, to really find high performing channels? Or is it usually the, you know, they should probably, you know, sort of test the waters elsewhere, get a, get a sense of what they can do within Google Meta, et cetera, and then, or is it just a combination of both? Yeah,
Ben Jeger 00:32:27 Yeah. I don't, I think the beauty is that it's not mutually exclusive unless, I mean, if you have a, a limited, um, budget, then yes, you need to. But, uh, assuming, assuming that, um, you have sufficient budget, uh, and given that, that the ideas you, it's, it's an investment that that pays back and you can, you can measure, um, the return on ad spend. Um, budgets should be, uh, unlimited, right? Like, it's just, um, you, you just, you, you are spending money and you're receiving, you're getting more. So it's, um, it, it, it might be a cash flow, um, question at some point. But theoretically, if, if performance is strong budgets and, and you can, you can scale, uh, infinitely budgets should be infinite as well. Um, meta and Google make it extremely easy, um, for you to, to get going and started. And, and we are trying to do exactly the same. There, there, there's no reason why you shouldn't, um, start with us. Uh, is, is, is, is kind of what I'm saying, but I don't, I I don't think it's, it's mutually exclusive. You don't have to make the, the tough decision, um, is, is really, uh, where I'm going.
Sean Ellis 00:33:52 Yeah. And in, in my experience, as you said, the the goal is as many positive return on investment opportunities as possible, uh, with, with an acceptable payback window. So if, uh, if your positive return on investment takes you four years, then then maybe you're not gonna have the balance sheet and cash flow to, to support that. Um, but assuming you have a relatively fast return on investment, you want as many of those as possible. And then what I started to, I was gonna quickly just chime in that, um, there's enough savvy investors out there that if, if you have a, a a lot of, uh, fast return on investment opportunities that are untapped in a business, that's, that's usually the most attractive investment for even, even, uh, debt investors. So you, you could do equity investment or debt investment. And so, um, yeah, that's, that in my experience with any company I've ever worked with is always the biggest challenge is how, how do you find additional positive return on investment ways to drive growth in the business, uh, beyond what you've already identified. And, uh, and as long as it's an acceptable payback window, um, you should be doing it.
Ethan Garr 00:35:05 So, Ben, I know in your role you're tapped with driving growth in, in Europe, middle East, Africa, um, my, I'm curious, where, what do you see as the big opportunities in those regions and why, what's exciting about it for you, and where do you see the business going, um, in those markets?
Ben Jeger 00:35:23 So, so I think, um, big opportunity for us is, uh, growing outside of, uh, gaming apps. Um, so, so we have, um, we we're strong with, uh, we, we have some really nice clients on the, um, travel, transportation, FinTech, um, e-comm, um, food delivery. Uh, but, but really where we are particularly strong in EMEA is on the gaming side. So, uh, gaming app developers, um, with within a purchase, uh, events, uh, work extremely well. And we've, we've, we've scaled, um, that those businesses, um, dramatically. Um, and I think the opportunity is, is for us in EMEA particularly, is, uh, replicating what we've seen our us, my US counterparts and our US teams doing as well as our Apex team is, um, capturing much more of market share outside of, uh, the gaming, um, space.
Sean Ellis 00:36:35 Yeah, I, I think the value proposition that you've laid out for us is, is really strong in, in what you're doing for companies, but even beyond the expansion as, as Ethan was just asking about, I think it'd be probably pretty helpful to just understand kind of what the, what the go-to-market mechanism is for your business. How, how do you guys, how do you guys acquire your customers? Um, is it, uh, is it a, is it a largely a, a touch sale? Is it a highly consultative sale? Um, is it, is it more self-service? And, and just may you, you touched on the growth, I think you said like it, what did you say five x growth in in the last couple of years? I mean, so, so two years, incredible growth rates. I think, um, I, I had read that, uh, you're the fifth fastest growing company in Silicon Valley based on the, the Inc 5,000. So clearly, clearly you have a solution that's resonating with the market, and you've figured out a really good way to get that solution to market. So yeah, more insights and, and how you're doing that would be really helpful as well.
Ben Jeger 00:37:35 Yeah, so, so, um, what we, we have, uh, sales reps that, that good reach out, um, to prospects, um, via LinkedIn, um, and, uh, attend a lot of the industry events where, uh, marketeers are, and we, I I don't know how many, um, events I, I would, I would love to, um, have this number off the top of my head, but I think it's north of 50, um, events that we've, uh, attended in, uh, uh, this year in EMEA alone. Um, and, um, and then we also have, uh, partner channels where we collaborate with, uh, the various mobile measurement partners and other tech partners, um, to, uh, bring clients in and, and make them aware of us. So we, we feature in several of the rankings of best, uh, best media sources and, um, and so on. So, uh, yeah, this is kind of how we, we we go to markets.
Sean Ellis 00:38:48 Yeah. And then, uh, it from a, from a value proposition out, uh, perspective on the outreach, like, to me, I think one of what, from what you've talked about, one of the things that's most appealing is yeah, you, this idea that, you know, are you completely reliant on, on Google and, and Facebook for, for your, your ad spend? Would you, would you like to tap into all of the alternative sources out there with similar targeting and, and optimization opportunities? Is that, is that kind of what the, what the value proposition is when you're, when you're reaching out to people and, and, uh, and if, if so, what are the, what are the types, the kind of more company stage? Like are they, do they tend to be pretty early stage? Are they, are they big companies or, or everything across the, across the board?
Ben Jeger 00:39:38 That was, that was pretty good. Uh, Sean, do you wanna join us or we
Sean Ellis 00:39:43 Sure. Hi, where Do I sign
Ben Jeger 00:39:48 You made it, you made it sound so easy. But yes, that's, that's, that's ba basically the value proposition. Um, and, um, in terms of, uh, company size, the only, uh, prerequisite is that you, that, that your app, uh, generates, um, enough, uh, events. So it's big enough to generate enough events to, uh, for our ML to have data in order to optimize, uh, um, against, if you want to run a basic, just an install campaign, then you need X amount of installs per day. Um, but those are, those are not really the, that's not the holy grail of, of, of what we do. What you really want us to run is return on a spend, um, campaigns. And for that we need, um, payment events and we need, um, x amount of payment events to train the machine and, and then find users that, that can do that. So, uh, size does matter to some extent, or the amount of data that, that your, that your app business currently is producing matters. Um, but other than that, I mean, it, it doesn't matter if you're an enterprise with, um, with, with, with an e-comm app or you're a two person gaming studio, uh, we, we, we are open to all,
Sean Ellis 00:41:15 And I and I assume it's mostly consumer businesses, then that they're gonna have that data volume versus, versus say, say B two B applications.
Ben Jeger 00:41:25 Absolutely. Absolutely.
Ethan Garr 00:41:28 So is it safe to say though, that, um, as long as you have a reasonable amount of events happening, as you're saying that the budget you would need to test the value of Moloco is probably fairly low, because the, I mean, I assume it doesn't take that long for the ML algorithm to figure out and start optimizing, right?
Ben Jeger 00:41:50 Yes. And what we do is we, um, one ingenious, um, move by our ML engineers is that we actually are able to train our models before you start spending, um, by enabling, uh, ingesting data into our systems in advance. So we can start two weeks prior to launching, um, we can start ingesting, um, your event data into our system. We can train the, the, the models, and then we can go and we already have, um, a head start. And then depending on the amount of data that we get, it'll take another 2, 3, 4 weeks, um, to, to, to ramp up and, and reach, um, your campaign goals.
Sean Ellis 00:42:38 So, so do they need to make a, uh, kind of a budget commitment to you to, to do that work? Or are you able to kind of offer that as a, as a kind of presale value add to say, this is, this is what we think we can deliver to you? Um, or is it, is it kind of too expensive to, to, to, to offer that without some kind of, uh, commitment and spend for you guys?
Ben Jeger 00:43:03 No, so, so as, as we mentioned, um, earlier it, right, we, we can deliver people to your app, but then de depending how strong your product is, uh, it, it, it will, the results will largely depend on, on the, on, on the app as well, right? So for us to, to take the risk, uh, with any business to, to say, okay, we're gonna, uh, we know exactly how your app works, how it monetizes is, is, is difficult. Therefore, we, we, we basically say, okay, you want, you know, your product, what we can do is deliver you the users, and then you need to, um, do the rest. You need to retain them and monetize them and so on.
Sean Ellis 00:43:50 So, so I guess building on that question, how, how do you actually charge for your product? Do you, do you charge as a percentage of ad spend that goes through it, or is it a kind of a flat SaaS fee?
Ben Jeger 00:44:00 It's on an, uh, O C P M basis. So, um, it's, it's optimized, uh, cost per mill. Um, and that's, uh, yeah, that's, that's how we charge.
Sean Ellis 00:44:14 Okay. So it's, it's based on the, the volume that's basically going through it.
Ben Jeger 00:44:18 Exactly. So it's, it's, it's essentially like a, a media cost. We, it's a cost plus. So whatever we, we, we are, 'cause we are also buying, um, the media on your behalf and we're charging, um, we're taking, um, uh, uh, a markup,
Sean Ellis 00:44:36 But it, but it does seem like I'm just, again, maybe overthinking your go-to market and may maybe you do something like this and maybe, maybe it's some new ideas for you, but like, uh, even, even though you can't guarantee that we think we could get you this much, I think if you still said, if, you know, based on a model of conversion rates of this monetization, of this, uh, you know, repeat purchase, whatever, um, if, if you can deliver on those pieces, we think we can give you this much incremental growth. And if, if your sales team could essentially offer that assessment for free as a, as a kind of proof of concept, it feels like you'd get, you get a lot of people saying, holy crap, yeah, this, let's, let's test this. This seems fairly low risk to test. Um, have you, have you tried anything like that?
Ben Jeger 00:45:26 Like we haven't, uh, so, so the whole like value engineering, um, concept is, is, um, I don't want to simp uh, simplify it too much because I think we have brilliant sales reps, but pretty much the pitch that you gave earlier, um, is, is is close to, um, how a conversation goes in reality. Do you like, um, the results you're getting from, uh, meta and from from Google, would you like to expand on that opportunity on, on the vast majority of the open internet that is currently untapped? Um, yes. Okay. Let's go. Yeah.
Sean Ellis 00:46:07 And it's already, I guess
Ben Jeger 00:46:09 Simpl sim Yeah. Simplified dramatically <laugh>,
Sean Ellis 00:46:11 And I guess it's already low risk enough that they, that they could basically try it and turn it off if it's not delivering.
Ben Jeger 00:46:19 Absolutely. Okay.
Sean Ellis 00:46:20 Sorry.
Ethan Garr 00:46:21 Yeah, I think that, no, I was, I was gonna say this basically the same thing. I think what, you know, what you're hearing is, Sean and I always are get, we always get excited when we hear about, you know, businesses that sort of have, um, really connected value for their end users. And what, what, what this really talks about is like, hey, this is sort of, if you're getting value here, it's kind of a no-brainer to try it here because it's only going to be to your benefit. It's only to be, it's only expansive to that, and the risk is low, and the time to, to learn is quick, right? I think that's, you know, if, if you can get an answer in a few weeks as to whether this is gonna be an effective channel, I mean, how many, you know, you talked about like going to 50 events this year. The problem with events, right, is it can take a while to figure out really how effective they're gonna be for you, right? And, you know, whereas this is, you know, this is instant gratification. So I know we're, we're starting to run short on time, you know, I, we didn't dig too much into your specific role,
Sean Ellis 00:47:17 <crosstalk>, I have one question on his specific role, if you,
Ethan Garr 00:47:19 Maybe you're
Sean Ellis 00:47:20 Gonna hit the same one, but I, I'm just really curious. I think that it feels like it's such a pure value proposition, such a, such a clean one. Is there, is there any kind of tweaking to that value proposition as with your focus on E M E A? Is there any kind of tweaking to that value proposition in different markets? Or is is, does pretty much the same pitch work in each market
Ben Jeger 00:47:42 There? There are, um, local nuances, uh, for sure. So I think, uh, one, one challenge we have in EMEA is when you think about E-com, it's, EMEA is an extremely fragmented market. You don't have, like in the us, uh, one, uh, massive market with one language, with one store to, to go after. In emea you have hundreds of, of different markets with, with languages and, and so on.
Sean Ellis 00:48:16 Even just within Europe, you're gonna have different, huge differences. And then you compare European countries to African countries or Middle Eastern countries. It's, uh, yeah,
Ben Jeger 00:48:25 Absolutely. And, and so that is, that, that is, um, one big challenge. It, it's, it's the, the challenge is twofold. One in how do you structure the team to go after, um, these opportunities, right? Because, uh, as you know, people tend to buy from people very much like to speak their own languages. Um, so this is a, uh, a talent question and challenge. And then it's on the, on the product side, um, rescale really well, um, for, for businesses. But if you are only present in one lang in one language, in one market, the value that we can deliver is limited by, by, by your market, right? So I think, um, that is, uh, that, that's part of the challenge, and that's why in EMEA gaming has worked so well, because gaming is global. Gaming tends to be, um, gaming apps tends to be available all over. And there's amazing, um, talent game developers in, in E M E A. And, um, so, so that's, that's one of the advantages and that's why we went after, uh, gaming companies in EMEA specifically first. Whereas in the US we see food delivery and e-comm and, and all those apps do extremely well because it's, uh, they don't have the same constraints. I hope that answers
Sean Ellis 00:49:58 No, it does, it does. Good question. Thanks. For sure.
Ethan Garr 00:50:02 So I just have one last question, and then I, uh, Sean, I'll ask our, uh, our famous, uh, wrap up question. But, you know, if you look back, uh, Ben, and, and let's say, I don't know, you tell me two years or so at your efforts here at, um, at Moko, um, what will success look like for you? What, like, if you can say, man, I hit it outta the park. What's happened in the, in that time period?
Ben Jeger 00:50:27 I think we, we, we would've established it. We would've come onto this podcast and you would've known exactly, um, who Moloco is, I think becoming a household name, uh, is as, as one of the leading software companies in the world, is something that we, um, have the ambition to achieve, and we have all the ingredients to actually achieve. You mentioned with the fifth fastest growing company, um, in Silicon Valley. And, and, and so if we continue on this trajectory, I think we can get there.
Ethan Garr 00:51:04 Gotcha. So I guess that informs sort of, uh, what I've read about you guys and also a little bit about why, why the push into, uh, beyond just gaming, right? It's product diversification for you guys is really about showcasing who you are beyond just that, that one niche, right? That it's a big niche gaming, but, um, that's, that's the importance of being present in e-commerce and retail and other places as well, right?
Ben Jeger 00:51:31 Yes, absolutely. And we have, we, we have other businesses that we are launching and, um, where the retail, uh, media platform business has hit product market fit. And now it's about scaling that to the same extent that we, um, have cr um, scaled the D S p. And, and so creating further, uh, s-curves and extending the s-curves is, is what what we're about. And we're tapping into really, really big markets, um, that, that, uh, are, uh, ready and, and and ripe to, to actually, uh, benefit from, from machine learning at, uh, at this level.
Sean Ellis 00:52:16 So I am, I'm gonna cheat and I'm gonna add one more question beyond before my last question. Um, it just, it just struck me that like, I, I feel like in, in the past, you know, when I, I, I mentioned, I originally started in a performance marketing role, and it was a very manual process to, like, we would run a macro and an Excel sheet that would give us kind of the bid adjustments. And it was, it was, it was a, a very kind of hands-on process, you know, more and more you get, you, you know, you, you put your target cost per acquisition or even your return on investment and, and you're getting directly in systems like yours or in Facebook or in in AdWords, your ability to make those adjustments. Um, agencies have kind of come in and out of playing a role for me over the years, um, with that, uh, you know, but, but as you, as you can start to do buying across a lot of different media and, uh, and, and through a platform that, that, that tests and optimize that media, are you finding that a lot of your businesses through agencies, or is most of it direct to the clients, and, and do you see that that, that changing over time?
Ben Jeger 00:53:27 Yeah. Um, I, I think you hit the nail on the head. Um, it, it is becoming increasingly easy to buy from platforms because machines are taking over a lot of the heavy lifting, which means that a lot of our cl our clients, um, feel comfortable with buying direct from us. And I think agencies, um, still play a role, and I don't think they're going anywhere. Um, I think very often, uh, we, we have the case where, uh, there's teams that are scaling and they don't have the capacity, and then they, they bring in an agency to fill in the expertise gap and, and just actually the manpower, uh, and, and woman power. Um, and, and then eventually, um, in-house a lot of these activities because it's fairly easy, um, to run on these platforms, including ours. Um,
Sean Ellis 00:54:26 And I, and I've even seen agencies like rolling up landing pages now and, and kind of try trying to do the value add on the conversion side, knowing that, uh, if they just focus on the customer acquisition side, that, that they're likely to be disintermediated by, by technologies.
Ben Jeger 00:54:44 Yeah. I, I think, by the way, there's also value add in, in the creative production. So there's agencies that are, um, adding, uh, creative production and media buying as, as services. And, and given that, uh, creative is one of the few levers that one has, um, in this new world, it's becoming increasingly important to get that right. And, and having someone, um, with a lot of expertise like an agency to help you is, is very useful and powerful.
Sean Ellis 00:55:16 And that'll be an interesting question to kind of come back to our original, and it's, it's a question without an answer right now, but the, uh, what role does AI play in in that media creation itself, in the advertising creation and landing page creation? Because I know, I know there's a lot of tools out there that are, are quickly creating different types of, of advertisements and even full websites at this point. So, um, it's, yeah. Yeah. All of this is evolving really quickly, and it's, and it's exciting area to, to watch. And I think you guys play a, a really critical role. So we have, we have one final question that we'd like to end every, uh, every one of these conversations with. And, and it's, uh, what do you feel like you understand about growth today that you may not have understood a couple of years ago, at least? Not as well.
Ben Jeger 00:56:08 I, I, I love that question. Um, to me it's the impact individuals have, um, on, on growth. So you, you, you can have out outsized impact, um, by ex extremely high talented individuals that, that basically can, can set your company on a completely different, uh, growth trajectory. And I think, um, that is something that I wasn't as, uh, aware of. And, and I've, I've learned that over the last, uh, a couple of years I would say, or more. But, uh, it, it became in, I I be, it became increasingly aware how important it's to have these, uh, superstars within your team.
Ethan Garr 00:57:03 I love that. 'cause I don't think it minimizes everybody's, uh, impact on growth, but it says that, like, I think as an individual for, if someone's listening to this, it says to you, uh, don't wor, you know, don't be afraid to be the change maker to throw, you know, to, you know, throw out the big ideas even if they, if they sound crazy.
Ben Jeger 00:57:23 Yes. Yes. And, and, and, and put in the work. Um, because, uh, yeah, I think that that can really set people apart. Like there's a lot of people like us who like to talk, um, <laugh>, but actually the people who like, uh, get stuck in and do the work and, and are creative and, and, and find a way to get things done and see the world slightly differently and have some that, that, that really makes the difference. That makes the whole thing fun. And, and I think you also need to pick an environment where this is celebrated and, um, where you can, where people are open to, to, to hearing good ideas, uh, and allow them to come from anywhere, right? Yeah, absolutely. Then you can rise to the top.
Sean Ellis 00:58:11 Absolutely. And, you know, just one, uh, before we, uh, kind of, uh, lean too far into the positioning of talkers and not doers, <laugh>, uh, you know, I just, I just finished up a role with, with, uh, bounce. Uh, I think it's one of the fastest growing companies in, in the world. And, uh, I, I love rolling up my sleeves and doing, because it is really easy to get theoretical about these things and, and become academic about 'em. And I know Ethan has been hands-on with the company as well. And, uh, just, just, uh, it tho that's where, that's where kind of this, this stuff is, is reality. Um, and, uh, and, and kind of the, the hype cycle as we kind of talked about with AI and some of these other pieces, outcomes, outcomes matter. Outcomes are what, uh, are, are what help you drive impact in a business, whether it's games and the impact is just entertainment and fun, or you're solving a, a hard problem that people have.
Sean Ellis 00:59:06 If you don't have the right tools to reach those customers and, and, uh, cost effectively acquire and serve those customers, you're not gonna provide very much impact, and you're not gonna build a valuable business. And so, um, I'm, I'm really excited by this, this conversation. My, my big takeaway, um, again, comes back to just like, there, there's so much hype around AI right now, and, and that machine learning is, is a piece of ai, and that you guys are applying it in a way that that really helps companies drive a lot more impact on their customers by being able to expand the, uh, the, the strong return on investment opportunities to, uh, strong return on ad spend opportunities to, to acquire lots of customers. And, um, so yeah, it's a super cool conversation, a fun conversation. Ethan, do you have any other big takeaways from this conversation?
Ethan Garr 01:00:00 No, you really stole mine again, Sean <laugh>, but, uh, no, but I, but I, but I, yeah, I a hundred percent agree. I think it comes down to, you know, get stuff done. You wanna talk about ai, great, but if you want to, if you want to get, if you like, turn that into action. You know, figure out how AI is gonna change your future, whatever it is. You know, it's, like you said, it's, the language becomes less important than the, than the effort to make those, those things come to life. So, uh, yeah, Ben, I equally, uh, enjoyed this conversation. Um, I probably will not be able to speak for another week, but, uh, thank you. But it's been, uh, it's been <laugh>.
Sean Ellis 01:00:34 Ben, any, any last words that you, you want before we wrap things up?
Ben Jeger 01:00:40 I, I, I wanna thank you both for having me. Um, I, I enjoyed the conversation very much, and I, as I told you, um, it went on longer than, uh, we all expected, but, uh, I, I, I really enjoyed myself a lot, so thanks. Thanks for the questions and the prep.
Sean Ellis 01:00:56 Absolutely. And when, when it goes on longer, that means that Ethan and I are really excited about the, uh, the topic and the guest and, and the company. So yeah, thanks for, thanks for bringing an interesting conversation and, uh, for Ethan and I, it's the first, first, uh, podcast interview we've done for a while because we have both been so busy executing. So it's, it's great to, great to be back in and have you back on as one of our first guests after an extended break, but we've got a lot more planned. And, uh, so for those who have tuned in, thank you for listening and we'll, we'll bring you another episode soon.
Ethan Garr 01:01:27 Thanks everyone.
Ben Jeger 01:01:28 Thank you. Thank you.
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