Building a New Operating Model for Ecommerce Scale With ZyG

[00:00:00] Do you need AI agents that you can trust? Well, with an AI data layer providing real-time connection within your data platforms, you can trust your agents to provide accurate solutions. So, scale your business by trusting your agentic AI accurately getting the work done for you. Trust its capabilities with Denodo. And you can do that by simply visiting denodo.com to learn more.

[00:00:26] Could AI solve one of e-commerce's most stubborn problems? Turning a promising product into a profitable global brand? Well, in this episode of Tech Talks Daily, I'm going to be joined by the co-founder and CEO of a company called ZyG. And that's spelled Z-Y-G. And he's building an operating system for e-commerce scale.

[00:00:54] They identify products with real scale potential, then take on all the digital work needed to grow them. And they do this by combining AI agents with specialist teams, predictive modelling and a strong data layer. And ZyG handles everything from storefronts to advertising, retention and customer support. So, e-commerce entrepreneurs can focus on what they actually do best, developing great products.

[00:01:23] But behind all of this is an amazing and inspiring story. Because my guest previously helped build IronSource into an $11 billion public company before its later acquisition by Unity. So, I want to learn more about everything here and also discuss what the entire experience taught him. And after an experience like that, why he then returned to startup life. And how ZyG is testing demand with real customers.

[00:01:52] And why e-commerce could be moving from software tools towards real accountable business outcomes. But enough for me. Let me beam your ears all the way to Tel Aviv, where our guest is waiting to speak with us today. So, thank you for joining me on the show today. Can you tell everyone listening a little about who you are and what you do? So, thank you for having me. It's great to be here. My name is Omer Kaplan.

[00:02:20] I am one of the founders and the CEO of a company called ZyG. Well, it's a pleasure to have you join me today. You're remarkably humble as well. Because for people listening, before this, you previously built IronSource into a $11 billion public company before its acquisition by Unity. So, I've got to ask, what did that experience teach you about scaling a company on a massive scale?

[00:02:44] And any lessons that you learned along the way that you're applying differently as now you build ZyG? Yeah. So, IronSource was a crazy journey. And I think that, by the way, it was pre-AI, which sounds like decades ago, but really, right?

[00:03:01] But I think that in IronSource, what we knew to do in, I think, a pretty good way and what we are trying to do today in ZyG, and today, by the way, it's harder to do, is to identify trends soon enough to execute upon them. So, in IronSource, we started where desktop apps were bigger than mobile, right?

[00:03:26] And then we quickly saw the trend for everybody moving to using mobile apps. So, we were fast enough to adapt our entire technology around mobile app advertising and monetization, and then evolved also into game publishing and creation. And we knew how to see trends.

[00:03:47] And even if we weren't the first ones, we knew how to execute really effectively and then to have significant market share and also to learn from what others are doing. And we are trying to implement the same type of thinking in ZyG. And today, it's obviously very challenging because things are changing every day, right?

[00:04:12] But I think that nobody out there knows today what's our world, kind of the higher world is going to look like even a couple of quarters from now. But I think that if you build the right DNA of adapting quickly and being open enough also to kind of fine tune what you're doing, I think that that's the key. And that's what I've learned in trying to adapt the same methodology in ZyG.

[00:04:39] And I've got to ask on a personal level, when you've built a company into an $11 billion public company, but then it gets acquired, what makes you want to jump out of bed and get back in the game? Because a lot of people listening will be thinking after an exit like that, they just want to sit on a beach drinking cocktails. But, of course, we all need a reason to get out of bed. I'm just curious, what made you want to go straight back in? So I'll divide my answer to two.

[00:05:06] I think, by the way, it wasn't an easy decision, right? I'm also a part-time musician. And I thought about going all in around music. And I have three amazing kids. So we were talking about traveling the world and all of that. But I think that, for me, there isn't a big... I'm motivated by creativity. Yeah.

[00:05:31] And for me, the biggest vehicle or the most significant vehicle to deploy creativity into is building a company, building a startup. And the concern is that if you're taking too much time off, it's very hard to go back in. You're becoming used to a slower kind of pace, right? And you can even become a bit irrelevant. And then I have many friends.

[00:06:01] I've seen it happening, right? And so my decision was, I'm going to take a few months off. I'm going to travel a bit, spend time with the family, do some more music. But I want to quickly find my way back in. And when I thought about the idea of Zig, I felt it's so significant that it was clear that I'm going back in, back all in and bigger than ever. So that's reason number one.

[00:06:26] Reason number two is that we are in a timeframe right now where transformational companies are evolving, right? Because the world is just like when internet started like 20-something years ago. I think that it's the same kind of time period. And it's very rare to be an entrepreneur when you have this kind of time, right, that you can build.

[00:06:54] And I would have, I usually as a person, I don't have FOMO too much. But I would have a very painful FOMO if I wouldn't be an entrepreneur right now building something that I think can be transformational. It's such a great story. I absolutely love it. Fast forward to present day. Of course, there's a lot of noise around AI. Starting a consumer brand has arguably never been easier.

[00:07:20] But building one into a profitable global business, I would say, remains incredibly difficult. So where does that journey typically break down? And why do great products and strong brands, even with so much backing, often fail to scale? Yeah. So I think what you said remains an enormous problem. I think it's becoming easier to sell but harder to scale, right? Just like you said.

[00:07:46] And the reason is because if I have an amazing product and I invested years in developing it and it has great value and I'm now ready to sell, what are my options today? Right? It's very, I can go on Amazon or any other marketplace and I'll be able to get some distribution. But I'll probably drown in a very crowded market, very hard to kind of stand out. I can go to Shopify, which is an amazing infrastructure.

[00:08:13] And I would very easily build a great store. But it's just the store itself, right? Nobody, like, it's very different than building a business that now everybody is coming to.

[00:08:27] And I have no solution out there that if they verify that my product is really as important as I think or that the potential is as high as I think, that they can take care of everything around scale. But there's nothing out there like this in e-com. And e-com is obviously a huge market.

[00:08:50] And the reason, by the way, that until today there wasn't anything like it is that pre-AI or pre-agentic capabilities, in order to provide something like that for hundreds or thousands of brands, you would need, I don't know, enormous amount of people. The business model wouldn't work because building an e-com business and scaling it is very complicated.

[00:09:17] And it requires many, many, many pieces that need to work extremely well together. And when you only have humans involved, it's very labor intensive. And what we're doing is we literally took all of the things that you need other than building the product itself, right?

[00:09:36] So everything online that you need to do to scale a brand, we're building the infrastructure to be able to take this end-to-end, right? So we're literally building this enormous agentic infrastructure, which also has humans, which are the most creative or the most talented people around in the different areas of e-com.

[00:10:03] And then we can go to companies and we can tell them, hey, if we verify, and we can speak about how we're doing it, but if we verify that your product can scale, we'll deliver it. We would literally deliver an outcome as a service, right? We wouldn't give you, here is our software, now use it, because I think the world is moving away from the traditional SaaS model of just use my software, right?

[00:10:30] But we're giving it, we're building the software as our own infrastructure. And upon that, we're building the services layer and we would drive the car for you. And that's what we're building. And before you join me on the podcast today, I was reading how you believe AI could make consumer businesses attractive to venture investors again. A great point now.

[00:10:54] And I've got to ask from your viewpoint here, everything you're seeing and hearing, what is changing in the economics of building and scaling consumer companies? And what costs or risks can AI meaningfully start to reduce as well? I would imagine it's slightly different this time around from last time. Yeah, so I think that investors, usually it's very hard to raise money for consumer businesses, right?

[00:11:17] It's very hard because the investments are usually intuition-based, right? It's very hard to see a company at the beginning of the world that they have this great physical product. And now as an investor, how do I know, does it have the potential to scale, right?

[00:11:36] And what you can do with AI, and this is in the heart of what we're building, is you can literally create at a relatively early phase, when the product is selling and you see value, but it's not scaling yet. You can literally do what we're calling a product market fit or a scale market fit test where you're building all of the assets. You're using, of course, authentic capabilities.

[00:12:02] You're doing different campaigns and combining real-world users that you are driving at scale to the store, to the website. You're analyzing all of the behavior of the users, the KPI, what was the cost per acquisition. You're comparing that to different benchmarks, and then you can literally create a score.

[00:12:27] That score would predict what is the chance of this brand to scale significantly. We're focusing on scaling in the U.S. market, right? The company itself can be in Europe or anywhere else, but we're checking the scale in the U.S. market. And the ability to create all of the brand assets, to run campaigns, to build really sophisticated models around it, and to analyze that is completely different in how you're doing it today.

[00:12:55] We can complete it end-to-end in about a week. I think that pre-AI, that would take, I don't know, a year, right? And endless resources. So that's number one. And when you're doing it right, then the chances of the brand to succeed, the bet, is a much easier one. So that's number one.

[00:13:19] And number two, which is a macro trend that I think is very interesting, I think that when code in general is becoming a commodity, I think investors are going back to want to invest in physical things, right? So I think that people are going to see, like, it's clear that e-com is only going to continue and grow whatever happens in AI, right?

[00:13:49] People will still want to buy tangible things. So you're seeing more and more VCs and more and more investors who used to really only go after deep tech. They are now trying to find opportunities in things that they can grasp that are going to stay here, you know, for a long time. So I think that the ability to better predict and going back to kind of fundamentals of what trends will remain,

[00:14:18] I think are going to make consumer investments now much, much more popular than they've been in the last few years. And I was also reading how at ZyG you're using predictive modeling alongside real-world testing to help determine which brands have the potential to scale. So what signals separate a potential breakout brand from just another expensive failure?

[00:14:43] And how much can technology genuinely predict before the market ultimately decides? Yeah, so what we're trying to do, and there are two kind of theses here that you can follow. One of them would be, I would say, completely predictive, where also the audience that you're bringing would be synthetic audience, right? So agents and these kind of things. And then you're building this model by analyzing these synthetic behaviors.

[00:15:14] But I think that that's limited. And what we're doing, which as far as I know is unique, is we're building all of the assets in an agentic way, right? So we're building the way the brand would look like because it needs to look good enough to compete with big brands. We're building the store. We're building the creatives. We have agents who are doing the advertising on Meta.

[00:15:42] We're using models to predict all of the KPIs. But the users that we're bringing to the store are real users, right? So every test that we will do, we would spend around 10K of literally media spend to bring real users. And we would monitor real KPIs. Like literally, how much did it cost for this company to bring a paying user?

[00:16:12] How does it benchmark in that category to all of the top competitors? And how would that KPI change when the scale would become bigger, right? So you're combining agentic capabilities, different type of predicted lifetime value modeling and these kind of things. But you're also doing it with real world data of bringing real users and measuring real behaviors.

[00:16:41] And when you're doing that, we believe, and we're already seeing it, by the way, we've done more than about 100 of these tests until now and in scale. Some of them, we believe that you're getting to a real, real strong correlation. So that's what we're doing. Excuse me.

[00:17:00] So if we zoom back and have a look at the old landscape there, e-commerce businesses have traditionally accumulated enormous technology stacks, including or involving platforms, agencies, advertising tools, logistics, analytics, and manual processes. But what stands out for me here at Zieg is you're taking a very different approach by assuming responsibility from the outcome.

[00:17:25] So why do you think the next software model moves from just selling tools towards actually delivering complete business outcomes? It's so refreshing to hear. And I'd love to hear more about why you're taking this approach. So I think that the problem with using so many different software, right, or so many different tools is that each of them is siloed, right?

[00:17:50] And the real value is created when the different pieces are working on kind of one infrastructure, one data. And I'll give you an example. When I'm, if I'm generating creative to run ads for my business, right, I want them to communicate. I want them to say the same message as the landing page of my store.

[00:18:17] And I want to use the same message when I'm now doing email marketing for that customer to offer them additional offers. And I want to use the same message when now this customer is calling my customer support. I want to have that end-to-end funnel experience, right, and understanding. And most companies today, they are working with multiple vendors. They have agencies doing creatives.

[00:18:47] They have agencies doing the advertising. They have different companies answering their customer support. They have internal teams who are either doing it themselves or just managing the agencies. And it doesn't communicate together. And what we're building, we have an agent that are doing the advertising on meta. And that agent understands what creative needs to be generated.

[00:19:14] And they are communicating that to the agents who are generating creative and then to the retention and the entire funnel. And only when you're connecting everything, you are creating this exponential value that AI can give you. And I think that it's almost not fair to think that an e-com company, people that have developed real great physical product,

[00:19:41] that they can also have the relevant people, the relevant tech talent or the relevant people or the e-com experience also build something like that. And I think that when you're giving them kind of siloed solutions, it's very hard to really create disadvantage, right? So first of all, from the value proposition itself, we're giving it end-to-end, right? And so it's first of all, it's even before the business model.

[00:20:11] It's about let's give you a holistic solution that will create an exponential value, right? In addition to that, I think that where AI is going is to a place where companies want to get the service as well, right? So they don't want to get just software because they're saying, well, I'll do it myself or I'll use Cloud or whatever.

[00:20:37] They want a company that can tell them, I'm also providing the service and enhance the outcome, right? And I think that the world is moving to a place where if you want to have Moat as a company providing services, you're not going to be able to just give the software. You need to put the services layer above that and basically provide an outcome as a service. Yeah, I completely agree with you.

[00:21:06] But I suspect we will have a few people listening that when they hear about the service as software, interesting question around accountability. So if technology providers start promising outcomes rather than capabilities, how do you see that relationship between customer and technology company changing and who owns the risk when results don't materialize? How do you see that evolving? Yeah, listen, I think that...

[00:21:32] So our business model, by the way, is a consumption-based and it's a percentage of revenue that we're managing. So eventually, when I'm saying outcome as a service, it doesn't mean that if something doesn't work, we are the only one who are taking the risk.

[00:21:54] But I mean that it's very clear that the way that we are measured is by delivering the end-to-end outcome. So I think that it's not that service companies from tomorrow morning will now only be paid if they succeed. Because that wouldn't scale. But I think that they would be measured in delivering an outcome.

[00:22:21] And I think that today, it's very vague, right? You're working with a creative agency and something doesn't work in your advertising. So they will say, it's not the creative, it's the way you're optimizing your campaigns. And the agency would say, it's not the campaigns, you don't have enough creatives. And then they will say, listen, the ROI that we gave you is as high as you can get. Now it's all about retention.

[00:22:49] And you don't have kind of this single entity that is accountable for the outcome. And that's the nuance, which is accountability. It doesn't mean that you're taking the entire risk, but you are accountable for delivering the outcome. And your passion for this really shines through in our conversation today. And I'm curious, when you're looking towards everything you're working on and what your plans are for the future,

[00:23:15] what excites you about everything you're working on at the moment and what this could turn into? I literally feel that this can become, that ZyG can become the third kind of missing pillar in the e-com landscape next to Amazon and Shopify.

[00:23:33] I truly believe that every great consumer or e-com company out there that will want to focus on their product and have somebody else take care of scale, that they would want to go to ZIG. And by the way, it's important to say, we are going through a very, we are only onboarding companies that we think can significantly scale. Right?

[00:24:00] So from every about 10 companies that will start the process with us, we're only going to scale one, something like that. Right? Because we are really looking after the ones that can be significant. Right? So we want to create a reality that if I'm, if I like, if I can dream for a second that every brand that dream, like every brand dream would be to be accepted to ZIG.

[00:24:30] Right? Because they would know that once ZIG is scaling them, then they are on the path to huge success. Right? So, and I think that it's definitely feasible and we are already starting to see really exciting case studies around it from companies that we are working with. So I'm very, very excited about, about what the future holds here. Love it.

[00:24:53] And looking at your story that we began with there, the origin story, you've already experienced the kind of exit that many founders dream about. And there are so many opportunities out there for everybody listening as well. And as somebody that's been there and done it and then going down the same path again, what are you seeing in this current technology cycle that makes you maybe think that we're witnessing a very rare opportunity to create a new generation of defining companies?

[00:25:20] I, my advice would be to dream as big as you can. I think, I think that solving, solving today a niche problem is becoming very hard and very, I wouldn't say hard, but it's very hard to build a company upon and raise money because it would be how to convince you have a moat. Right. Right.

[00:25:46] I think that the moat today, when all of the LLMs can do everything and they're, and obviously they're improving every day. I think that the moat is only if you're trying to solve a very, very big, complicated problem, right? Like what we are doing in, in scaling e-com.

[00:26:05] And I think that if before founders or entrepreneurs, if before they, you know, the, the usual feedback was focus, focus, focus, and think about something really clear.

[00:26:20] Now I think that be as high as wide as you can try to find a very big problem or value that you can generate and don't afraid to do, to go after something that previously would be a combination of 10 different companies. Right. That's exactly what we were following in Zig. And I think that this is what, and this is how entrepreneurs should think like today. And that would be my advice.

[00:26:50] I think that is an inspiring moment to finish on. So thank you so much for sharing how Zig is revolutionizing e-commerce with the first agentic operating system for e-com scale, an end-to-end platform, helping product inventors, entrepreneurs, brands, turn their products into successful D2C businesses. There's a lot of opportunities there. I'm hoping we can try and harness some of that energy and passion for the opportunities available.

[00:27:17] So for everyone listening, where is the best place for everyone to find you and your team online or find out more about anything that we talked about? So we, we have a very catchy name and domain, which is zig.com. It's with a Y though, because it looks better than an eye. So you can very easily reach out from there. And we'd love to see if we can help anybody who reaches out. I love what you're doing with this connected system of AI agents built on a unified data infrastructure.

[00:27:46] And for everyone listening, I'll include links in the show notes to everything we've talked about as well to help bring that to life. And please dream bigger. I'd love to hear some success stories from each and every one of you listening here. But more than anything, thank you for sharing your inspiring story and starting this conversation. Appreciate you, Tom. Thank you for having me. I think my guest's argument today leaves e-commerce founders with a very useful question. Are they assembling more tools, agencies, and dashboards?

[00:28:15] Or are they starting with the outcome they wanted to achieve? I think Zig's answer is to focus right on that business outcome. They take on everything it takes to scale an e-commerce business from creative advertising, fulfillment, and then combining AI agents with data and experienced people to deliver it all from end to end.

[00:28:38] But what is really interesting here is that if you're an e-commerce founder, you don't actually need to pay attention on how it's all happening. The outcome is that your business is scaling. And yes, it's a new model, but equally incredibly practical and quite exciting here. Because rather than relying entirely on synthetic audiences, Zig is building the assets, spending real media money, observing real customer behavior, and comparing the numbers with category benchmarks.

[00:29:07] And this is an approach that cannot remove every risk from consumer growth. But what it can do is make an expensive decision so much more better informed. That's got to be a good thing, right? But at the heart of all this was an inspiring story. Beginning with IronSource explaining why he returned to a company building and outlining that ambition for Zig. So you can learn more by visiting zig.com. Links will be in the show notes. But over to you.

[00:29:36] Which part of your e-commerce operation would benefit most from one accountable owner? Love to hear from you. TechTalksNetwork.com. If you've got a story you'd like to share or you'd like to meet me at an event when I'm on the road, again, send me an audio message or connect with me on LinkedIn at Neil C. Hughes and we'll see what we can make happen there. But I've taken up far too much of your time today. So I'll speak to you again real soon. Bye for now.

[00:30:02] Bye for now.