David Steinberg of Zeta Global, co-founder and chief executive officer, outlines the company's pivot to an artificial intelligence, AI-native architecture and the development of one of the largest proprietary data clouds. The discussion addresses modern marketing technology, data sovereignty and agentic decisioning for enterprise use cases.
theCUBE Research and hosts John Furrier and Dave Vellante explore agentic workflows, customer data platform, CDP, capabilities, the Palantir Foundry partnership and how re-architected martech delivers low-latency intelligence for large scale deployment.
Steinberg states that the re-architecture enables millisecond decisions using substantially more data and produces certified marketing return on investment, ROI, of 600–700% and average technology returns of 283% according to Forrester. They emphasize data sovereignty practices that keep client data under customer control and describe the multiplying effect of chained agents on decision quality. theCUBE analysts highlight vendor consolidation and the practical implications of the Palantir Foundry integration for enterprise deployment.
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David Steinberg, Zeta Global
David Steinberg of Zeta Global, co-founder and chief executive officer, outlines the company's pivot to an artificial intelligence, AI-native architecture and the development of one of the largest proprietary data clouds. The discussion addresses modern marketing technology, data sovereignty and agentic decisioning for enterprise use cases.
theCUBE Research and hosts John Furrier and Dave Vellante explore agentic workflows, customer data platform, CDP, capabilities, the Palantir Foundry partnership and how re-architected martech delivers low-latency intelligence for large scale deployment.
Steinberg states that the re-architecture enables millisecond decisions using substantially more data and produces certified marketing return on investment, ROI, of 600–700% and average technology returns of 283% according to Forrester. They emphasize data sovereignty practices that keep client data under customer control and describe the multiplying effect of chained agents on decision quality. theCUBE analysts highlight vendor consolidation and the practical implications of the Palantir Foundry integration for enterprise deployment.
>> Palo Alto Studio Connection, Silicon Valley and Wall Street.
David Steinberg
>> I'm John Furrier, the host of theCUBE, here with Dave Vellante, my co-host.
John Furrier
>> Hello, I'm John Furrier, your host of theCUBE. We're here at theCUBE's NYSE studio. Of course, we have our Palo Alto studio connecting Silicon Valley to Wall Street. This is part of our NYSE Wired program and our Open Community. This is our mixture of experts series where we talk to the leaders and the experts in the field, find out what they're working on, because the AI Revolution continues to power AI infrastructure, accelerating the software layers and the system architecture and the stacks around building AI-native applications. David Steinberg is here, co-founder and CEO of Zeta Global. Great to have you on, David. Good to see you.
David Steinberg
>> John, great to see you. Thanks
John Furrier
>> for—you're also the chairman. I'll get that in there because I wanted to get that in there. You're the chairman and CEO. This is an interesting time. I want you to explain what you work on because you guys, I think, have cracked the code on what we've been covering on the data cloud, I call it modern legacy. I have a cloud, I got stacks, I got multiple silos, trying to stitch them together. That was kind of the SaaS generation. But now the new architecture of AI native looks a lot different, but the functionality is changing because you have essentially prompts, you now have applications, embeddings, and MCP servers. So you got Agentic coming in. So this is changing the work. But ultimately, as the intelligence feeds the agents, that's what you do. I think you really nailed this.
David Steinberg
>> I mean, I think when you think about what we are, we're an intelligent AI infrastructure company, John. We literally have one of the world's largest proprietary data clouds. 550+ million global individuals have opted in to be in our data cloud. We have over 5,000 to 7,000 data elements per person and our technology powers 5.2 million publishers. So we're ingesting trillions of signals on a monthly basis that we then use solely to power our algorithms and train our algorithms. So unlike a lot of other companies, in 2017, we made the decision to sunset our old architecture, re-architect an entirely new platform that put artificial intelligence and data as native to the application layer. That creates a speed. By way of example, we're able to create a decision in a millisecond with 10x the amount of data that one of our competitors needs 7 or 8 seconds to use 1/10 the data. Yeah, when you think about that, that's what creates massive return on investment, whether it's in marketing or whether it's in business intelligence, which are our two main use cases.
John Furrier
>> It's interesting, there's so many things going on in your world and our worlds together. Because digital and physical are coming together. Old school ad tech, old school martech stacks that have been around during the cloud era and the email marketing era has changed. You now have completely disaggregated communities. Well, you have massive amounts of data and signals, but if harvested properly, the specialism that comes out of that. And now people want low latency. Now, one more thing that I'd love to get your reaction to is that humans are great users of intelligent systems. How do I inform my business? But now you've got agents. They're doing work. It's not just a search query. We're talking about decision-making.
John Furrier
>> Yeah.
John Furrier
>> So you have decision-making intelligence going on here with multiple dimensions.
John Furrier
>> What's—
John Furrier
>> explain why this is important and why you—
David Steinberg
>> Well, it's not just agents doing the work, John. We have 4 agents strung together doing tasks. So one might look at what's the best possible audience. The second will figure out where to target it. The third is, will that audience be credit approved by our client standards? Fourth, the attribution capabilities to build full return on investment. As you're thinking about marketing, every agent you add to a string, it's not 1+ 1= 2. It's an order of magnitude smarter per agent. So 2 is an order of magnitude 10 times better. Yeah, 3 is 100 times better. 4 is 1,000 times better. So if you think of how a human would operate, when you start stringing 3 or 4 agents into a task, you're literally 1,000 times smarter. And when you're looking at an organization like ours, which is powering today 51% of the Fortune 100, and, over 800 global brands trust us today to run their marketing CRM or business intelligence. When you start to look at the old school marketing clouds. Yeah. They're really antiquated, right? They've never redone their architecture to put AI as native. They keep signing new partnerships. Yeah, because the old partnerships are not working. So they said, let's choose a new one, a new silo. Right. So this guy's hot this week. Let's go with them.
John Furrier
>> Yeah.
David Steinberg
>> You're stepping out of the platform and, there's a big press release. We're working with these guys now. But the truth of the matter is, unless it's native to the architecture. Yeah. It can't actually create the functionality necessary and the speed necessary to create the true return on investment.
John Furrier
>> Talk about the technology and the business model issues, because you're talking about a couple of things. I want to just unpack that. One, there's a technology play. You have a moat that you've created. Yes, we'll get into that in a second. But the customer, your customer, they have data and they want to leverage that data, unlock the value of that data. But the old business model was I would just hire someone, an agency, an analyst.
David Steinberg
>> You'd actually have a body shop.
John Furrier
>> Okay, give me intelligence from my data so my people can make good decisions. Talk about that business model because you brought up a good point. I got to hire that new firm. A lot of these firms are either old firms or new firms, but their mechanisms are different. So there's one, a technology integration problem. Yeah. And then two, the business model's like, wait a minute, this is a lot of loops, a lot of speed. I can't close the loops.
David Steinberg
>> One of the biggest value adds we do for our clients is we automate the ingestion of all of their data. So we might be with a Fortune 500 company. We're pulling their IVR data, their CRM data, their point of sale data, their prospect data. They've never had it in one place before. And we pull it into a customer data platform. Now, a few months ago, we announced the biggest partnership in our corporate history with Palantir. And what they're doing with their Foundry platform and their Ontology is game-changing for us. So we re-architected our Data Cloud on top of Foundry, and it's now allowing us to ingest data even faster, streamlining it. In the old days, you would effectively have a body shop come in, build it out from scratch, long cycle times. John, recently we just had a massive win. And you look at that win, it was in a business intelligence use case. We competed with one of the 3 most important professional services firms. We weren't competing with the marketing cloud. And our data, which informed the BI, was smarter than this firm that is commensurate with the smartest people in the world.
John Furrier
>> All right. I have to ask you, because you're getting— I want to get into the journey so that you didn't just get here overnight. You have a lot of history and get that data and then now you're leveraging it. But in the analytics world, in the old days, 7 years ago, you'd have dashboards that tell you what happened, not what's happening. So now there's a trend towards what's happening. And then using AI to figure out what will happen.
David Steinberg
>> And that's what we're doing. So we look at most business intelligence as antiquated. It's literally you take 100 people, you put all the data in, you get a static chart and a graph, and you're looking in the rearview mirror. As Ted Lasso likes to say, there's a reason the windshield in front of you is bigger than the very small rearview mirror. What Zeta's doing is Zeta is using our data to build dynamic business intelligence to tell our clients what's next. So we have a hotel client. We literally help them figure out where to put their next 500 hotels. We have a client who's in the restaurant business. Where are they going to put their next locations? We have a client who's a massive retailer. How did we help them shift inventory based on online research for what people are going to be buying in the Northeast versus the center of the country versus the West Coast. They had their biggest back-to-school ever because we were able to help.
John Furrier
>> So your infrastructure— you're an infrastructure provider.
John Furrier
>> Yeah.
John Furrier
>> At the end of the day, we call it whatever you want, but simplify it because you're actually enabling— you're removing middlemen.
John Furrier
>> That's right.
John Furrier
>> In the process, we just— you don't need them.
David Steinberg
>> That's right. When we recently— The Gap announced that they had chosen us as the system of record for their company. And they're obviously one of the most legendary retailers and fashion icons out there. Yes, we displaced Salesforce there who had had that account probably forever, but we also displaced 3 other vendors that were in there and 4 vendors became one overnight.
John Furrier
>> Actually, you don't really hear the vendor consolidation story in AI usually. It's vendor expansion, right? You're actually hitting both. Correct. So talk about the value. Let's take the Gap example and maybe some other customers can illustrate this. But okay, vendor consolidation is almost like cost savings. Yeah, you get it. But the real value is that either top line revenue or product service excellence.
John Furrier
>> Yep.
John Furrier
>> What is Gap getting now with—
David Steinberg
>> I can't talk specific to Gap, but let's talk about our average client. Yeah, our average client is getting a 283% return on technology spend with Zeta. And for every dollar they spend with us in marketing, we return between 600 and 700% return on marketing spend. That's a certified number by Forrester. That's not us just saying that. So when an enterprise chooses us, they're winning on technology return on investment. They're generally able to reduce their headcount pretty meaningfully. And we're able to return 600 to 700% return on marketing spend. By the way, I think this is one of the reasons, John, last year our net retention rate as a company was 120%. Our clients really love us. last quarter we grew the business 44% top line, 56% EBITDA growth, 73% free cash flow growth. And people keep saying, how are you doing that? It's what we drive— better value. John, you've been running a business for years.
John Furrier
>> The only way to win is to drive value to your clients and actually extract value. Yes. And you get— and value is through profit. Happy customers buying more, more profit. All right, so let's get into some of the tech stuff. I know the numbers are great. By the way, you should be on our CMO series too, because CMOs always tell us they're looking for modern solutions. And by the way, the shelf life of a CMO these days is almost 4 years. Brian and I were just talking about that, but we think they're more like CIOs, right? Because they're starting to get into more performance. This isn't your usual performance marketing. There's no question every CMO knows what performance marketing is, but they don't know what the modern
David Steinberg
>> version—here's what they want. They want outcomes. And what Zeta guarantees is outcomes. All right.
John Furrier
>> So I'm a customer. So I'm a CMO. David, you got me. You sold me on the idea. Okay, let's merge our data together. But my other guy is over here in my IT department saying we should build a single tenant cloud. But because I'm giving you my crown jewel. So, although you're a cloud, can you give me a single tenant experience?
David Steinberg
>> Yeah. Let me be clear. We don't take any of our clients' data. We create a consumer data platform. We input all of their data. They still own it. They have total data sovereignty. In fact, whenever Alex Karp and I are talking, this is like data sovereignty central. We then merge our data into that CDP and it's their infrastructure. It's our infrastructure. But the ownership of the data, their data is theirs. The ownership of our data is ours.
David Steinberg
>> And you're running on your cloud.
David Steinberg
>> Correct. But we never use any of it to inform any of our other customers, and we never make our data cloud smarter from their data.
John Furrier
>> I wanted to bring this up because one of the biggest trends in our AI factories and the Neo Clouds is— and this is more of an Amazon disruption conversation— is that you have multi-tenant clouds using AI to create essentially single-tenant experiences, which is wild because the workloads are end-to-end.
John Furrier
>> That's right.
John Furrier
>> And Amazon has VPC. So, this has been around. It's not a new concept, but It does open up the efficiency side of having the scale.
David Steinberg
>> Exactly. So what it also does is it creates zero data exhaust.
John Furrier
>> Yeah.
David Steinberg
>> So no foundational model has ever seen the Zeta Data Cloud, nor does Palantir. It sits on top of their architecture, but they don't see the data. When we import our clients' data, our data enriches it. They have their own algorithms that get smarter and smarter.
John Furrier
>> Yeah.
David Steinberg
>> Once again, here's what's really interesting. If they were ever to fire us, and I will tell you, I can't remember the last time we actually got fired.
John Furrier
>> Well, if you bring a lot of data intelligence to the table, they only win with you.
David Steinberg
>> Correct. But if they did fire us, all of that data just goes away. Yeah, we don't get to keep it. They already keep their data.
John Furrier
>> So they have a kill switch, basically.
David Steinberg
>> They do.
John Furrier
>> In a way, on the data.
David Steinberg
>> No, they do, but they lose all of the intelligence. Yeah, goes away.
John Furrier
>> That's like going to school and then forgetting everything. Correct. I want to get to the jury.
John Furrier
>> Well, it never feeds back to them.
John Furrier
>> Yeah, well, we go to school and then you get smarter and then you infer off the data you learn. It's like training and inference kind
David Steinberg
>> of—No, but I want to be clear again, we're not doing that. So we're not using that data to build inference for any of our other clients. They can't.
David Steinberg
>> Oh, they can't? Okay.
David Steinberg
>> They can't. The data lives in the CDP. Now, when they see—
John Furrier
>> What is CDP?
David Steinberg
>> I'm sorry, Customer Data Platform. So it's a fractionalized system, just like you talked about. It's effectively a multi-tenant cloud with a single—
John Furrier
>> they lose your intelligence.
John Furrier
>> Correct.
John Furrier
>> They can keep whatever they—
John Furrier
>> well, they—
John Furrier
>> whatever they already had.
David Steinberg
>> Yeah, their data, they keep it. But the point is the clients benefit from the massive intelligence that lives in the CDP. Now they can infer certain things, but at the end of the day, we never use their inference information or their actual information for
John Furrier
>> other—and that's why Palantir likes you. Because you fit into their platform as a system, subsystem of their system.
David Steinberg
>> Correct. And you look at data sovereignty Alex and I think very similarly on that.
John Furrier
>> Yeah, data sovereignty is a huge discussion. Talk about that, because cloud sovereignty is more about privacy, with GDPR, we've been through that movie. But when you talk about AI native sovereignty, you've got geographical boundaries, but enterprises are starting to use the word sovereignty for their domain.
David Steinberg
>> Well, if a large enterprise feeds 100% of their data into a foundation model, Alex would say you're giving your entire business away. And I think it's hard to argue with that, right? Because we're now seeing real-world examples where researchers are using foundational models and that foundational model comes up with a solution to their research. And in their own disclosures, they're saying, yeah, we can't say that no inference came from their research, but we were doing this without them.
John Furrier
>> I do like Alex's focus on domain expertise as the moat. Yes, I think he's right on that one. I think he's got— people are smart, they're trying to figure it out. So I think they'll work on some of those things. Some will die. I think definitely the laggards will kind of fall away. But I have to ask you about your journey because you didn't just get here overnight. How did you get the data moat? So go back in time. When was the moment you said, okay, we're doing a service, we have to get this AI? When did you identify the moat? Opportunity.
David Steinberg
>> So we had been sort of a mid-tier, what we called customer lifecycle marketing platform, where we were the first company that we knew that was doing CRM, customer acquisition and customer monetization. And then we entered into 2017 and we had built this very large data repository, John. And what we were starting to see was the capability of making it actionable was dissipating because it was so much data humans couldn't process it in time to make it actually work.
John Furrier
>> Yeah, data gravity, right?
David Steinberg
>> So then I started researching this new technology, natural language processing. We'd already been using machine learning for some automation. And, literally in 2017, we decided to pivot the entire company We sunset our old platform, took 500 full-time engineers and re-architected a brand new platform, which today we call the Zeta Data Cloud and the Zeta Marketing Platform. One is native to the other. And when you look at it, it was the decision that changed everything for us. I'll tell you just a funny anecdote. We put it live in 2020. Big announcement. Nobody cared. AI what? Yeah, AI what? But we're not conversational AI, right? We're pitching it like crazy. All of a sudden, 2022, the day after Thanksgiving, ChatGPT comes out.
John Furrier
>> Yeah.
David Steinberg
>> And it changed our
John Furrier
>> world.
David Steinberg
>> Right.
David Steinberg
>> Yeah.
David Steinberg
>> AI went from science fiction to boardroom conversation. Every board of directors went to every CEO and said, what's our AI strategy? Every CEO went to every CMO, CTO, CIO. What's our strategy? And we were there. And now 4 years in a row, we're on a 4-year compounded 30% plus growth rate, top line, 50% compounded EBITDA growth and 75% compounded free cash flow growth since sort of the year following.
John Furrier
>> It's nice when your bets come in and also because it's also personally rewarding, I imagine, for you because you were misunderstood Well, no, for many years. And you're like, no, no, it's going to happen. You had to have the conviction.
David Steinberg
>> Well, starting in the 2000s, by the way, there was very interesting Harvard case study published with Columbia University on the board meeting that I had to get this approved just recently, which was cool for me.
John Furrier
>> That's cool.
David Steinberg
>> And people don't understand our private equity partners were like, what?
John Furrier
>> We've been in founder mode, basically. Yeah, go into founder mode, make things happen.
David Steinberg
>> And I'll tell you what, I think people ask me all the time what differentiates our team. And I think execution's— the landscape is littered with great ideas, right? You've got to have a great idea and you have to be able to execute. But I think the commonality of my senior executive team is we all have a massive chip on our shoulder.
John Furrier
>> Of course. And I think it drives us because people weren't endorsing and you were misunderstood. But the feedback in
John Furrier
>> private—it was the opposite. Well, they weren't just not endorsing us, they were saying we were idiots.
John Furrier
>> Yeah, yeah, yeah. Well, that's okay. Like I said, we've all been there. Founders have that. Every founder has, you know, a little bit of scar tissue.
John Furrier
>> Every
John Furrier
>> founder.Congratulations. The momentum is awesome. And you made the right bet. You're on the right wave at the right time,
John Furrier
>> early.And by the way, John,
John Furrier
>> too.Yeah, we're trying our
David Steinberg
>> best.No, I think what you're doing is amazing.
John Furrier
>> Well, I appreciate that. And again, make sure we can put you in the CMO series in this one. We will certainly follow up. Congratulations. And yeah, love the success. AI native is here. And what's happening is it's changing the user experience, which changes their expectation. And the underlying platforms have to adjust. You can't modernize legacy and just pave over the cow path. You have to actually understand how the data works. Low latency, feed the engines, provide the intelligence. That's the future. And again, more AI native. Entrepreneurs are coming. So it's an AI-native world. We're just living in it and just got to adapt, doing our part here on theCUBE to share the data with you. Thanks for watching.
>> Palo Alto Studio Connection, Silicon Valley and Wall Street.
David Steinberg
>> I'm John Furrier, the host of theCUBE, here with Dave Vellante, my co-host.
John Furrier
>> Hello, I'm John Furrier, your host of theCUBE. We're here at theCUBE's NYSE studio. Of course, we have our Palo Alto studio connecting Silicon Valley to Wall Street. This is part of our NYSE Wired program and our Open Community. This is our mixture of experts series where we talk to the leaders and the experts in the field, find out what they're working on, because the AI Revolution continues to power AI infrastructure, accelerating the software layers and the system architecture and the stacks around building AI-native applications. David Steinberg is here, co-founder and CEO of Zeta Global. Great to have you on, David. Good to see you.
David Steinberg
>> John, great to see you. Thanks
John Furrier
>> for—you're also the chairman. I'll get that in there because I wanted to get that in there. You're the chairman and CEO. This is an interesting time. I want you to explain what you work on because you guys, I think, have cracked the code on what we've been covering on the data cloud, I call it modern legacy. I have a cloud, I got stacks, I got multiple silos, trying to stitch them together. That was kind of the SaaS generation. But now the new architecture of AI native looks a lot different, but the functionality is changing because you have essentially prompts, you now have applications, embeddings, and MCP servers. So you got Agentic coming in. So this is changing the work. But ultimately, as the intelligence feeds the agents, that's what you do. I think you really nailed this.
David Steinberg
>> I mean, I think when you think about what we are, we're an intelligent AI infrastructure company, John. We literally have one of the world's largest proprietary data clouds. 550+ million global individuals have opted in to be in our data cloud. We have over 5,000 to 7,000 data elements per person and our technology powers 5.2 million publishers. So we're ingesting trillions of signals on a monthly basis that we then use solely to power our algorithms and train our algorithms. So unlike a lot of other companies, in 2017, we made the decision to sunset our old architecture, re-architect an entirely new platform that put artificial intelligence and data as native to the application layer. That creates a speed. By way of example, we're able to create a decision in a millisecond with 10x the amount of data that one of our competitors needs 7 or 8 seconds to use 1/10 the data. Yeah, when you think about that, that's what creates massive return on investment, whether it's in marketing or whether it's in business intelligence, which are our two main use cases.
John Furrier
>> It's interesting, there's so many things going on in your world and our worlds together. Because digital and physical are coming together. Old school ad tech, old school martech stacks that have been around during the cloud era and the email marketing era has changed. You now have completely disaggregated communities. Well, you have massive amounts of data and signals, but if harvested properly, the specialism that comes out of that. And now people want low latency. Now, one more thing that I'd love to get your reaction to is that humans are great users of intelligent systems. How do I inform my business? But now you've got agents. They're doing work. It's not just a search query. We're talking about decision-making.
John Furrier
>> Yeah.
John Furrier
>> So you have decision-making intelligence going on here with multiple dimensions.
John Furrier
>> What's—
John Furrier
>> explain why this is important and why you—
David Steinberg
>> Well, it's not just agents doing the work, John. We have 4 agents strung together doing tasks. So one might look at what's the best possible audience. The second will figure out where to target it. The third is, will that audience be credit approved by our client standards? Fourth, the attribution capabilities to build full return on investment. As you're thinking about marketing, every agent you add to a string, it's not 1+ 1= 2. It's an order of magnitude smarter per agent. So 2 is an order of magnitude 10 times better. Yeah, 3 is 100 times better. 4 is 1,000 times better. So if you think of how a human would operate, when you start stringing 3 or 4 agents into a task, you're literally 1,000 times smarter. And when you're looking at an organization like ours, which is powering today 51% of the Fortune 100, and, over 800 global brands trust us today to run their marketing CRM or business intelligence. When you start to look at the old school marketing clouds. Yeah. They're really antiquated, right? They've never redone their architecture to put AI as native. They keep signing new partnerships. Yeah, because the old partnerships are not working. So they said, let's choose a new one, a new silo. Right. So this guy's hot this week. Let's go with them.
John Furrier
>> Yeah.
David Steinberg
>> You're stepping out of the platform and, there's a big press release. We're working with these guys now. But the truth of the matter is, unless it's native to the architecture. Yeah. It can't actually create the functionality necessary and the speed necessary to create the true return on investment.
John Furrier
>> Talk about the technology and the business model issues, because you're talking about a couple of things. I want to just unpack that. One, there's a technology play. You have a moat that you've created. Yes, we'll get into that in a second. But the customer, your customer, they have data and they want to leverage that data, unlock the value of that data. But the old business model was I would just hire someone, an agency, an analyst.
David Steinberg
>> You'd actually have a body shop.
John Furrier
>> Okay, give me intelligence from my data so my people can make good decisions. Talk about that business model because you brought up a good point. I got to hire that new firm. A lot of these firms are either old firms or new firms, but their mechanisms are different. So there's one, a technology integration problem. Yeah. And then two, the business model's like, wait a minute, this is a lot of loops, a lot of speed. I can't close the loops.
David Steinberg
>> One of the biggest value adds we do for our clients is we automate the ingestion of all of their data. So we might be with a Fortune 500 company. We're pulling their IVR data, their CRM data, their point of sale data, their prospect data. They've never had it in one place before. And we pull it into a customer data platform. Now, a few months ago, we announced the biggest partnership in our corporate history with Palantir. And what they're doing with their Foundry platform and their Ontology is game-changing for us. So we re-architected our Data Cloud on top of Foundry, and it's now allowing us to ingest data even faster, streamlining it. In the old days, you would effectively have a body shop come in, build it out from scratch, long cycle times. John, recently we just had a massive win. And you look at that win, it was in a business intelligence use case. We competed with one of the 3 most important professional services firms. We weren't competing with the marketing cloud. And our data, which informed the BI, was smarter than this firm that is commensurate with the smartest people in the world.
John Furrier
>> All right. I have to ask you, because you're getting— I want to get into the journey so that you didn't just get here overnight. You have a lot of history and get that data and then now you're leveraging it. But in the analytics world, in the old days, 7 years ago, you'd have dashboards that tell you what happened, not what's happening. So now there's a trend towards what's happening. And then using AI to figure out what will happen.
David Steinberg
>> And that's what we're doing. So we look at most business intelligence as antiquated. It's literally you take 100 people, you put all the data in, you get a static chart and a graph, and you're looking in the rearview mirror. As Ted Lasso likes to say, there's a reason the windshield in front of you is bigger than the very small rearview mirror. What Zeta's doing is Zeta is using our data to build dynamic business intelligence to tell our clients what's next. So we have a hotel client. We literally help them figure out where to put their next 500 hotels. We have a client who's in the restaurant business. Where are they going to put their next locations? We have a client who's a massive retailer. How did we help them shift inventory based on online research for what people are going to be buying in the Northeast versus the center of the country versus the West Coast. They had their biggest back-to-school ever because we were able to help.
John Furrier
>> So your infrastructure— you're an infrastructure provider.
John Furrier
>> Yeah.
John Furrier
>> At the end of the day, we call it whatever you want, but simplify it because you're actually enabling— you're removing middlemen.
John Furrier
>> That's right.
John Furrier
>> In the process, we just— you don't need them.
David Steinberg
>> That's right. When we recently— The Gap announced that they had chosen us as the system of record for their company. And they're obviously one of the most legendary retailers and fashion icons out there. Yes, we displaced Salesforce there who had had that account probably forever, but we also displaced 3 other vendors that were in there and 4 vendors became one overnight.
John Furrier
>> Actually, you don't really hear the vendor consolidation story in AI usually. It's vendor expansion, right? You're actually hitting both. Correct. So talk about the value. Let's take the Gap example and maybe some other customers can illustrate this. But okay, vendor consolidation is almost like cost savings. Yeah, you get it. But the real value is that either top line revenue or product service excellence.
John Furrier
>> Yep.
John Furrier
>> What is Gap getting now with—
David Steinberg
>> I can't talk specific to Gap, but let's talk about our average client. Yeah, our average client is getting a 283% return on technology spend with Zeta. And for every dollar they spend with us in marketing, we return between 600 and 700% return on marketing spend. That's a certified number by Forrester. That's not us just saying that. So when an enterprise chooses us, they're winning on technology return on investment. They're generally able to reduce their headcount pretty meaningfully. And we're able to return 600 to 700% return on marketing spend. By the way, I think this is one of the reasons, John, last year our net retention rate as a company was 120%. Our clients really love us. last quarter we grew the business 44% top line, 56% EBITDA growth, 73% free cash flow growth. And people keep saying, how are you doing that? It's what we drive— better value. John, you've been running a business for years.
John Furrier
>> The only way to win is to drive value to your clients and actually extract value. Yes. And you get— and value is through profit. Happy customers buying more, more profit. All right, so let's get into some of the tech stuff. I know the numbers are great. By the way, you should be on our CMO series too, because CMOs always tell us they're looking for modern solutions. And by the way, the shelf life of a CMO these days is almost 4 years. Brian and I were just talking about that, but we think they're more like CIOs, right? Because they're starting to get into more performance. This isn't your usual performance marketing. There's no question every CMO knows what performance marketing is, but they don't know what the modern
David Steinberg
>> version—here's what they want. They want outcomes. And what Zeta guarantees is outcomes. All right.
John Furrier
>> So I'm a customer. So I'm a CMO. David, you got me. You sold me on the idea. Okay, let's merge our data together. But my other guy is over here in my IT department saying we should build a single tenant cloud. But because I'm giving you my crown jewel. So, although you're a cloud, can you give me a single tenant experience?
David Steinberg
>> Yeah. Let me be clear. We don't take any of our clients' data. We create a consumer data platform. We input all of their data. They still own it. They have total data sovereignty. In fact, whenever Alex Karp and I are talking, this is like data sovereignty central. We then merge our data into that CDP and it's their infrastructure. It's our infrastructure. But the ownership of the data, their data is theirs. The ownership of our data is ours.
David Steinberg
>> And you're running on your cloud.
David Steinberg
>> Correct. But we never use any of it to inform any of our other customers, and we never make our data cloud smarter from their data.
John Furrier
>> I wanted to bring this up because one of the biggest trends in our AI factories and the Neo Clouds is— and this is more of an Amazon disruption conversation— is that you have multi-tenant clouds using AI to create essentially single-tenant experiences, which is wild because the workloads are end-to-end.
John Furrier
>> That's right.
John Furrier
>> And Amazon has VPC. So, this has been around. It's not a new concept, but It does open up the efficiency side of having the scale.
David Steinberg
>> Exactly. So what it also does is it creates zero data exhaust.
John Furrier
>> Yeah.
David Steinberg
>> So no foundational model has ever seen the Zeta Data Cloud, nor does Palantir. It sits on top of their architecture, but they don't see the data. When we import our clients' data, our data enriches it. They have their own algorithms that get smarter and smarter.
John Furrier
>> Yeah.
David Steinberg
>> Once again, here's what's really interesting. If they were ever to fire us, and I will tell you, I can't remember the last time we actually got fired.
John Furrier
>> Well, if you bring a lot of data intelligence to the table, they only win with you.
David Steinberg
>> Correct. But if they did fire us, all of that data just goes away. Yeah, we don't get to keep it. They already keep their data.
John Furrier
>> So they have a kill switch, basically.
David Steinberg
>> They do.
John Furrier
>> In a way, on the data.
David Steinberg
>> No, they do, but they lose all of the intelligence. Yeah, goes away.
John Furrier
>> That's like going to school and then forgetting everything. Correct. I want to get to the jury.
John Furrier
>> Well, it never feeds back to them.
John Furrier
>> Yeah, well, we go to school and then you get smarter and then you infer off the data you learn. It's like training and inference kind
David Steinberg
>> of—No, but I want to be clear again, we're not doing that. So we're not using that data to build inference for any of our other clients. They can't.
David Steinberg
>> Oh, they can't? Okay.
David Steinberg
>> They can't. The data lives in the CDP. Now, when they see—
John Furrier
>> What is CDP?
David Steinberg
>> I'm sorry, Customer Data Platform. So it's a fractionalized system, just like you talked about. It's effectively a multi-tenant cloud with a single—
John Furrier
>> they lose your intelligence.
John Furrier
>> Correct.
John Furrier
>> They can keep whatever they—
John Furrier
>> well, they—
John Furrier
>> whatever they already had.
David Steinberg
>> Yeah, their data, they keep it. But the point is the clients benefit from the massive intelligence that lives in the CDP. Now they can infer certain things, but at the end of the day, we never use their inference information or their actual information for
John Furrier
>> other—and that's why Palantir likes you. Because you fit into their platform as a system, subsystem of their system.
David Steinberg
>> Correct. And you look at data sovereignty Alex and I think very similarly on that.
John Furrier
>> Yeah, data sovereignty is a huge discussion. Talk about that, because cloud sovereignty is more about privacy, with GDPR, we've been through that movie. But when you talk about AI native sovereignty, you've got geographical boundaries, but enterprises are starting to use the word sovereignty for their domain.
David Steinberg
>> Well, if a large enterprise feeds 100% of their data into a foundation model, Alex would say you're giving your entire business away. And I think it's hard to argue with that, right? Because we're now seeing real-world examples where researchers are using foundational models and that foundational model comes up with a solution to their research. And in their own disclosures, they're saying, yeah, we can't say that no inference came from their research, but we were doing this without them.
John Furrier
>> I do like Alex's focus on domain expertise as the moat. Yes, I think he's right on that one. I think he's got— people are smart, they're trying to figure it out. So I think they'll work on some of those things. Some will die. I think definitely the laggards will kind of fall away. But I have to ask you about your journey because you didn't just get here overnight. How did you get the data moat? So go back in time. When was the moment you said, okay, we're doing a service, we have to get this AI? When did you identify the moat? Opportunity.
David Steinberg
>> So we had been sort of a mid-tier, what we called customer lifecycle marketing platform, where we were the first company that we knew that was doing CRM, customer acquisition and customer monetization. And then we entered into 2017 and we had built this very large data repository, John. And what we were starting to see was the capability of making it actionable was dissipating because it was so much data humans couldn't process it in time to make it actually work.
John Furrier
>> Yeah, data gravity, right?
David Steinberg
>> So then I started researching this new technology, natural language processing. We'd already been using machine learning for some automation. And, literally in 2017, we decided to pivot the entire company We sunset our old platform, took 500 full-time engineers and re-architected a brand new platform, which today we call the Zeta Data Cloud and the Zeta Marketing Platform. One is native to the other. And when you look at it, it was the decision that changed everything for us. I'll tell you just a funny anecdote. We put it live in 2020. Big announcement. Nobody cared. AI what? Yeah, AI what? But we're not conversational AI, right? We're pitching it like crazy. All of a sudden, 2022, the day after Thanksgiving, ChatGPT comes out.
John Furrier
>> Yeah.
David Steinberg
>> And it changed our
John Furrier
>> world.
David Steinberg
>> Right.
David Steinberg
>> Yeah.
David Steinberg
>> AI went from science fiction to boardroom conversation. Every board of directors went to every CEO and said, what's our AI strategy? Every CEO went to every CMO, CTO, CIO. What's our strategy? And we were there. And now 4 years in a row, we're on a 4-year compounded 30% plus growth rate, top line, 50% compounded EBITDA growth and 75% compounded free cash flow growth since sort of the year following.
John Furrier
>> It's nice when your bets come in and also because it's also personally rewarding, I imagine, for you because you were misunderstood Well, no, for many years. And you're like, no, no, it's going to happen. You had to have the conviction.
David Steinberg
>> Well, starting in the 2000s, by the way, there was very interesting Harvard case study published with Columbia University on the board meeting that I had to get this approved just recently, which was cool for me.
John Furrier
>> That's cool.
David Steinberg
>> And people don't understand our private equity partners were like, what?
John Furrier
>> We've been in founder mode, basically. Yeah, go into founder mode, make things happen.
David Steinberg
>> And I'll tell you what, I think people ask me all the time what differentiates our team. And I think execution's— the landscape is littered with great ideas, right? You've got to have a great idea and you have to be able to execute. But I think the commonality of my senior executive team is we all have a massive chip on our shoulder.
John Furrier
>> Of course. And I think it drives us because people weren't endorsing and you were misunderstood. But the feedback in
John Furrier
>> private—it was the opposite. Well, they weren't just not endorsing us, they were saying we were idiots.
John Furrier
>> Yeah, yeah, yeah. Well, that's okay. Like I said, we've all been there. Founders have that. Every founder has, you know, a little bit of scar tissue.
John Furrier
>> Every
John Furrier
>> founder.Congratulations. The momentum is awesome. And you made the right bet. You're on the right wave at the right time,
John Furrier
>> early.And by the way, John,
John Furrier
>> too.Yeah, we're trying our
David Steinberg
>> best.No, I think what you're doing is amazing.
John Furrier
>> Well, I appreciate that. And again, make sure we can put you in the CMO series in this one. We will certainly follow up. Congratulations. And yeah, love the success. AI native is here. And what's happening is it's changing the user experience, which changes their expectation. And the underlying platforms have to adjust. You can't modernize legacy and just pave over the cow path. You have to actually understand how the data works. Low latency, feed the engines, provide the intelligence. That's the future. And again, more AI native. Entrepreneurs are coming. So it's an AI-native world. We're just living in it and just got to adapt, doing our part here on theCUBE to share the data with you. Thanks for watching.
John Furrier