Zeta Global Holdings Corp. ($ZETA)

Hello, everybody. My name is Brett Miller. I'm the Co-Head of Software Investment Banking at JPMorgan. Thanks for being here. Today, it's my pleasure to lead a discussion with David Steinberg and Chris Greiner of Zeta Global. Zeta is an AI-powered omnichannel data-driven cloud platform that provides enterprises with consumer intelligence and marketing automation software, helping brands personalize marketing across channels, including e-mail, social web, chat, connected TV and video. David, the company's CEO and Chairman, co-founded Zeta in 2011 and took it public in 2021. Chris, the CFO, joined Zeta in 2020 after serving as the CFO of [indiscernible]. David and Chris, thanks for being here today.

Thank you for having us.

First off, big picture. What is Zeta trying to become for the enterprise? Is it a marketing operating system, a data cloud and AI decision engine or some combo?

Well, let's start with yes. I mean we're -- our real vision is to become the operating system for our clients' entire marketing ecosystem. And if you look at Athena, our new sort of AI-driven super agent, she really positions us to do that really well. And if you look at the way we operate today, we're ingesting 100% of of very large enterprises first-party data. We're matching it with our data in the United States, we match it greater than 92%. And that's where the algorithms start training inside of the consumer data platform. Once we do that, all of the business intelligence and all of the data for our clients exist in that ecosystem. And I think one of the things people don't really understand is we think of ourselves as an AI-driven business intelligence company that started focusing on marketing because it's a $1 trillion TAM, right? It was just a very good place to start. It's not where we expect to finish.

So I spend a lot of my time today on the debate about the SaaS [indiscernible] and whether SaaS is going away. What is your view on this debate on the disintermediation by AI?

Well, I think it's going to be a lot like the dot-com except I don't think we're going to follow that type of bubble because most of the enterprises that are making these investments have trillion balance sheets. They're not start-ups. But what I would say is companies that adopted the Internet are the ones that have flourished from a technological perspective. If you think about it, I remember -- and yes, I'm old. I remember when the dot-com boom was coming, and they said it was going to kill Walmart. It was going to kill JPMorgan Chase. It was going to kill [indiscernible]. In all those cases, those organizations adopted those technologies and became juggernauts. Now -- I mean, first of all, right now, all funds are flowing to AI hardware, right? So that's one challenge that software companies are dealing with as public companies. The other really interesting thing is today, Nobody is willing to take a risk on who to be the winners, who's going to be the losers. And everybody is sort of throwing the baby out with the bathwater. If you think about companies that are going to win, there are going to be companies that have moats around their business. If you look at Zeta, we have 555 million global individuals who have opted in to be in our data cloud. The only other company that have data at our scale are all trillion company, talking about Meta, Google, Amazon, and you can go through that list. We use that data, and of course, we're ingesting the data today 51% of the Fortune 100 largest companies in the United States use our platform, and they're trusting us with their first-party data. We're using that data to create intelligence. And according to an independent Forrester survey study for every dollar a client spends on the Zeta marketing platform today, we returned 600% return on market spend. Now if you look at the adoption of Athena, which rolled out in the first quarter, we did say in the first quarter, we saw our agentic workflows go up by 700%, and Athena was a very big driver of that. Clients that are using Athena are seeing an even greater return on investment than that 600%. So I think over the next quarter or 2, investors are going to start to figure out there are going to be some winners. There are going to be some losers. I think companies that are workflow management tools, don't create intelligence, don't own data and don't have meaningful defendable assets are going to have to figure out how to pivot their businesses to survive. And I think you're going to have companies like Zeta that are creating intelligence, creating massive return on investment. And once again, I don't see Fortune 500 companies turning over their first-party data to large language models. [indiscernible] The other thing, of course, is we're already partnered with Open AI. We've already announced an enterprise partnership with them. We already work with Anthropic. We work with Google. We're already in that entire ecosystem.

You just teed up about 20 questions in that response. So thank you for that. So at CES, you did announce, you just mentioned it, the major partnership with OpenAI, which powers Athena. Tell us about that relationship, how it's evolved, where it's going.

Well, I'm super excited to mention today that we have now executed an agreement to partner with open AI and help them run their advertising. We're going to bring our enterprise clients into the open AI ecosystem and will begin to serve ads there on behalf of our enterprise clients.

Anything more about where that's going and like what you can be doing generally with it?

Yes. I mean, listen, we think open AI is going to be one of the winners in the next generation. And the fact that now we've executed partnerships with them around Athena and we've executed partnership with them around serving ads into the ecosystem. I think it's going to be game changing to our organization. If you think about it today, we are the only company I know of that is fully integrated into Meta, into Google, into the Open Web, into messaging, into connected TV and now connected into open AI, both through serving ads and through our GEO platform.

Incredible. We've mentioned Athena bunch. Why don't we just up level for a second and give just a quick description of it and then also like what is the workflow that it's changing for your customers?

So Athena is -- well, we'll step back a little bit. If you think about it, humanity is always communicated through voice, right? I mean, I shouldn't say always, but for, call it, 400,000 years. In the 1950s, we created this thing called the [indiscernible] sits between most humans and technology. And I think most of us find it very, very frustrating. Athena was created to be a voice-enabled fully conversational agent who helps our clients navigate our entire platform, not just by trying to figure out how to use different features and functions, but by literally acting for outcomes from the platform and Athena can change the screen in front of the client. So a client might say, I'd like to create 2 million incremental customers this quarter and I'd like to do it in an environment where I can lower my marketing cost by an average of 7% per customer acquired. And Athene a walk through how a client can get to those outcomes. So the way I equate it and I think many people in this room probably use Bloomberg terminals, right? What's ended your Bloomberg terminals capabilities do you use on a daily basis. 1%. That's -- I've heard 1, 3, 5. It's the same thing for most of. So we've built a fighter jet that our average client knows how to fly assess. And Athena becomes the copilot for how to get to those most valuable components of the platform that they don't know how to use on their own. And what we're seeing, once again, Athena rolled out in Q1, she was beta for much of it. She rolled out generally available in March. Even with that limited period, we saw a 700% uptick in a genic workflow, and we saw Athena, as most of it now, I mean, we did -- our business grew 50% top line in the first quarter, 42%, EBITDA growth, 42% free cash flow growth. This will be on a 4-year average basis, this will be our fourth year of greater than 30% organic top line growth and greater than 50% organic EBITDA growth. So what we're doing is working because our clients are consuming more of it. They're growing with us. And as we show a greater and greater return on investment, we believe we'll continue to see that growth.

We'll come back to the metrics and let Chris brag about those in a minute. On the 700% increase in Agentic interactions, like in the 1% of the Bloomberg use your analogy, what are you seeing about how customers want to use AI through that early signal?

We're seeing a lot of clients move right to how do I get to this outcome versus trying to navigate the platform to get to the outcome. And then Athena is able to control the entire experience and she actually changes the screen to show audience types, activation capabilities and all of the different return on investment in real time as you experience it. So that's a big one. Another big one interestingly enough has been analytics. We're seeing a lot of clients ask for analytical outcomes that we haven't seen the mask for before. And for those of you who don't know our business well, we have 3 main use cases, it sounds complex, but it's pretty simple, helping enterprises to create customers, maintain their existing customers and further monetize their existing customers. And we do this by activating across multiple channels, channel might be connected TV, a channel might be online video, it might be online contextual. It might be now plugging into open AI. It might be plugging and targeting into meta. All of those things are sort of use cases versus channels. If you've looked at our business since our IPO, we've been public for 19 quarters, I will point out, 19 consecutive quarters we've beaten our guidance and raised guidance, but the way we've grown our business is by adding channels. And we've gone from an average of about one channel to an average of over 3 channels in that same period. What we found is when enterprises use multiple use cases, so they do customer acquisition and customer retention and customer monetization. They spend 250% more on our platform. But the reason for that is because the flywheel for intelligence starts with one of them. So the data that informs acquisition further informs the data that's necessary for retention, which further informs the data monetization back to acquisitions. So the return on investment is substantially greater than our average of 60%. The single best tool to ultimately get our clients from an average of 1.4 -- I don't know the exact number, but sort of call it, just about over 1 use case to 3 use cases is Athena. Because after you've asked Athena for outcomes around acquisition, she might say to you, by the way, did you know that this 1.2 million of your existing customers began the process of churning off your platform and discovery for your competitors' products. Would you like to save them, and that's how it's already starting.

So you're not explicitly monetizing Athena yet. So talk about that decision of when does this become a line item in your P&L versus when is it just something that drives retention and ARPU?

Well, it's driving ARPU growth. I mean we had a 21% ARPU growth in the first quarter, and last year, our net retention rate was 120% as a company. We guide to 110 to 115. We were actually well above that in the first quarter. But when you look at what Athene is doing, she is driving a massive uptick in our utilization fees. So if you think of our business, about 60% of our revenue is subscription and 40% is utilization. If we were a large language model, we would simply be calling our utilization tokens instead of utilization because it's the exact same month. It's as we run messaging or we place an ad or we run a connected TV ad, we charge a fee for that. we've batted it around. There will be an opportunity at some point to build, I think, analytics products and extensions around Athena. But today, if you look at it, our 189 global superscale customers will spend approximately $110 billion on marketing this year. At the middle of our range, we have approximately 170 basis points of wallet share. Now we have some clients that we have 700 to 800 basis points of wallet share. And I don't see any reason we can't get all of our clients there at some point on average. So if Athena can help us go from 170 basis points to 200, 300, 400 basis points -- the return on investment to us is so much massively greater as you go from what I think last year, we were about $1.35 billion. And then this year, we're projecting $1.75 billion -- $1.78 billion. But you're looking at sort of the business is not just growing at 40% or 50%, it's also dropping a disproportionate percentage of that to the bottom line. So we think Athena is better served today in driving that massive uptick in utilization.

Any plans for the future and how you'll monetize AI differently than you're doing today?

Yes. I mean there's a lot of different ways. And back to the original premise, as you think about data, we think about ourselves as a business intelligence company that happens to focus on marketing. As we roll out business intelligence products, which is in our long-term road map, we'll begin to charge for those products, and that will be commensurate with other AI product.

And in terms of managing token costs, one of the sessions this morning, one of the companies said that they basically had no idea how this is going to evolve and they're learning in real time, like how do you think about how...

We are not that. We are fully and completely aware as to how we utilize tokens and how we program. What I would tell you is we built an internal platform called Spade and Spade is an internal proprietary workflow management tool. Last quarter, we publicly announced 75% of our internal new code was generated automatically. We're ahead of Google, which is even shocking to me. It works because of space. So a programmer goes to spade and tell spade the type of code it wants to create. Spade then looks at all of the available large language models, which include ChatGPT, Claude, Gemini, all the way through cursor and it makes the decision on which platform is right to create that piece of code and is utilizing the lease tokens in its generation. So for security, it might use cloud for programming, it might use GPT for publishing it might use Gemini. . Once it completes it, it sends it to another program called [indiscernible]. I don't know where we come up with the names for these things. But [indiscernible] then QAs the entire thing, sends it over to an architect who reviews it pushes a button and it goes generally available. So literally, we're doing stuff. We've talked about this, and I'll sort of mention today, we're going to be rolling out the next generation of Athena, which will be Athena for agencies. Agencies make up about 20%, call it, 25%, less than 25%, but of our revenue. And the product itself would have taken us 2 years to develop 2 years ago. We're going to have the entire product done in less than 4 months because the pace at which we're able to accelerate code generation. And the way we've been able to control cost while doing it. So I mean, by way of example, we've grown the business again on a compounded 4-year growth rate of 30%, great organically. We've grown headcount just about 10%. And I think we can even slow headcount growth even further, and we expect to be a 20-plus percent organic growth rate company for many years to come.

Speaking of the quarter, so great quarter, another great quarter, rule of 67%, growing 50% year-over-year and over 20% of that is organic.

29% was organic.

0 Which is over 20. It's well over 20.

It could be 20.02.

It's approximately 30.

That sounds better.

Chris, if you were to pick a couple of drivers in the quarter and then also talk about where the growth that organic growth is coming from?

Yes. I think what stood out to us as we even looked at it internally, certainly, as we spoke to it externally, was just how many parts of the growth ecosystem of Zeta, we're working in tandem. We talked about the 29 points of organic growth, and the balance that we had, 14 came from existing customers, 15 from new. If you look at the industries that rely upon Zeta's platform, we're in 15 different industry verticals. Our top 10 generate about 90%, 9 out of our top 10 verticals grew over 20%. When you think about the KPIs that power our growth, the customer additions and the customer spend expansion, we had 19% growth in super-scaled customer count. That's more than 3x greater than what we require from our model. And then as Dave mentioned earlier, from an ARPU perspective, 21% growth, our model is 12 to 16. David linked it back earlier to channel expansion and use case expansion, 2 data points that we shared with investors in the quarter was those that are using more than one use case. And if we were sitting here a few years ago, that would have been less than 10% of our portfolio. Today, that's double that. We're approaching 25%. And that metric, number of scaled customers using more than one use case grew 50% year-over-year and those using 4 more channels. any channels in tandem, grew over 40% year-to-year. So you had many different parts of the portfolio all working and executing really well that led to a much bigger beat than what we would typically have of, call it, 2 to 5 points on the top line.

The other thing really is Athena, seeing Athena out there. And we're taking meaningful market share from competitors. And 1 of the challenges we have as a public company, right, is are you a CRM platform or you an activation platform an ad tech company or you're a marketing technology company, are you a data platform? The answer is yes. Because our goal is to displace all point solutions in the marketing space. And if you look at our prepared remarks from our most recent call, we announced what I think is the most marquee client win we've ever had. It's a retailer with greater than 3,000 global locations and a and sell their own apparel across multiple brands. This is a company based in San Francisco. It had been a total sales force shop, and we were able to rip and replace them out. We also replaced 3 other vendors in that because Salesforce can't provide everything a modern marketer needs outside of a very sort of narrow CRM and CDP capability, whereas we're able to bring CDP, data cloud, best-in-breed data activation to CRM, customer acquisition and customer retention. We were told we were in the top 3 going into the end of the sort of ninth inning of the process. And we asked if we could come in and do an early demo of Athena. We did the demo of Athena and they called us the next day for pricing. So it's really -- I think, Athena is going to be a major, major game changer for our company.

It sounds like it. On the bottom line, you did grow your EBITDA by 42% year-over-year and your free cash flow by 48% year-over-year, which is pretty remarkable. What are the biggest drivers of that leverage?

Yes. Well, we've done a really good job of and David mentioned is automating more and more of what we have. We have a kind of a philosophy and company of where is value created. And we're creating the world's best products and we put resources and investment in engineering and the tools they use and then selling it as fast and efficiently as you can in the market. We put resources in quota carry. Everywhere else, we cut we trim, we automate. So that's allowed us to invest and have the best product in the market, sell at what is a very productive rate in the market and expand adjusted EBITDA margins and free cash flow margins faster than the rate at which we're growing the top line. rest of the year, we'll get back to very strong adjusted EBITDA free cash flow margins as well.

It's also important to note that we built a lot of this stuff ourselves. So as everybody is now talking to the evolution of AI, right? It's starting with large language models, and it's moving to what's called inference models, right? And I don't want to bore everybody in the room with this. But we've been building inference models for 5 years. the idea that 1 algorithm can focus on 1 task with the data set that is necessary to complete that task is really what inference is. We don't need to ingest the entire Internet to figure out what we're doing because we have so much proprietary data we can focus on, we're not sort of trying to boil the ocean here. Now of course, we love our partner, OpenAI, we love what they're doing, and they're trying to do something on a very, very big basis for that.

Yes. So the quarters are often driven by shifts in the shift. So last quarter, you talked about agency wins and social being big drivers. Why don't we spend just a minute on mix shift and how -- what that did for the quarter and how you think that's going to evolve?

Yes, we disaggregate revenue in different ways, but 1 of which is what we call and report as direct revenue contribution and integrated.

Platform revenue contribution. Direct is nothing more than when customers use Zeta data and Zeta channels to do their activation. And that regularly contributes 70% to 75% of our revenues that call it a gross margin of 70% to 75% on average. The integrated platform revenue is when customers rely on Zeta's data but the ability to go market inside the walled gardens. Met is a great example. David talked about others. That's about, call it, 25% of our revenue. It has a lower gross margin profile. A lot of the inventory gets passed through to customer. What we found empirically is that when agencies, which has been called the last 2 years, a new buyer of Zeta and they've grown and scaled to approaching 25% of revenue, they first test Zeta data and they first test our platform with social. And what we've seen is as they grow their spend, as they give Zeta more and more brands within their ecosystem, they do that by expanding as channels. So these 2 large wins like patterns in the past, started in social. And it's our expectation that as they grow, they'll migrate to direct, which will then take some pressure off the gross margin side. But it's really important from an investor's perspective, even though social has a lower gross margin profile, it's still accretive to adjusted EBITDA and free cash flow.

And it's important to note that we're really the only platform of our type that plugs into these walled gardens. So agencies start with us because there's nobody else who can actually do this. And then as they do it with us, they see the power of our data, and we're able to expand out into other use cases that are much higher margin.

So you've touched on this once before, maybe twice before, but you talked about, in your words, superscale customers, which is my favorite metric that any company -- we're going to move to [indiscernible] So on the super scaled customers, you're at 189 of them, I believe, and you're scaling that ARPU pretty significantly in that. cohort of customers. So one, how are you continuing to keep the momentum gaining those customers and what is driving ARPU expansion?

Yes, there's a -- for those that know our story well and for those that are new that want to pick up on it really quick, there's a slide in our investor deck that shows that the longer our customers are on our platform, the bigger they become. There's 5 years' worth of this slide that the vast majority of the time, we are not [indiscernible] we are proud to start with a $50,000 pilot or $150,000 proof of concept. And what we found is that those very small pilot in the first 12 months, almost get to $1 million in spend, which would then put them over to that superscale category. But beyond that, our fastest growing set of customers are those that have been with us 5 or more years. So to David's point, it's taken some of those longer tenured customers find out where all the corners in the platform that I'm not using today that I should be using. Athena unlocks that to everybody. So it has the potential to take those that are earlier in their life cycle and have them climb to that much higher level spend faster.

By way of example, I was at a conference just a couple of weeks ago, we were with a very large new partner. And I was -- I had 2 or 3 salespeople in the room, and they were all really nervous about getting this deal done and the CMO of this very company asked me how large I thought the test should be to really get to a statistical sample and I said, listen, I wouldn't start with any more than $10 million. if we do more than 10 million it's really going to get us past the point of diminishing marginal returns. But if we start with that it will give us really good statistical data. And they were like, okay. So we're not just taking existing clients and growing them, which has been our traditional business to Chris' point, he's totally right, but the credibility that's now coming with our current size, scale and return on marketing spend is leading clients out of the box [indiscernible] bigger numbers than we've seen before.

And on that dynamic, your net revenue retention rate is remarkably consistent and considerably high, 10% to 15%.

Last year, it was 120%.

Right. It's the consistency that I think, that I would call out at a time when a lot of other companies had seen degradation in that metric. And then in some cases, a recent recovery. How have you been able to maintain such consistently high net revenue?

I think that goes back to what Chris was saying, right? When you start with a client and by the way, the client that spend we're asking for $10 million has a $4 billion annual budget. So it's still statistically similar A lot of the companies we start with, we're starting with a small pilot new scale. That actually leads to a higher net retention rate, right, because they're growing and growing. And I think that, listen, we One of the things people don't understand is we build every one of our clients a consumer data platform. We ingest all of their data. We match it with all of our data. We match a greener than 92%. We then remove the personally identifiable information from a regulatory and keeping the consumers' data private. The algorithm then gets incredibly sort on how more customers can be your customers? What do they read? What do they search, what transactions did they do. We then go into our data cloud. You'll say, just in the U.S., we have 245 million opted in people. and we'll say, okay, great. These 50 million people are already our customers don't waste money marketing to them. Think about how often you get an ad for a product you already have. Then what we do is say, okay, these 2 million people are in market for your product, but only 1 million of them would be credit approved by your criteria. So now you've gone from 245 million potential customers down to 1 million you hypertarget them. And as they buy, it feeds their data back into the CDP through the CRM integration and the algorithm gets smarter. If a client were to fire us, they lose 100% of the learning. All of that data goes away. So what happens is the longer a client is with us, the smarter the algorithm gets the better we can either lower their churn or help them create customers at a lower cost. The higher the rate they move budget to us, the higher our net retention rate. When you think about sort of AI disintermediation, I couldn't see an environment where a Fortune 500 company is going to get all of their first-party data to a large language model. And then, of course, all of our data all 555 million people multiplied by 5,000 to 7,000 data elements multiplied by all of their web behaviors across trillions of active pages on the Internet has never been bedded into a large language model ever nor will it. That's our proprietary data for training our models in partnership with the clients' data. So that's why our net retention rate is so high, and it's one of the biggest moats around our business.

On the guidance, I'm going to fold a few questions together here. So one, 19 consecutive beat and raise quarters, as David mentioned, and then after this last quarter, you did once again, raise your guidance around revenue, EBITDA and free cash flow. What made you comfortable doing that? And how have you managed to achieve that level of, again, just remarkable consistency.

We are very transparent, and we give ourselves 2 to 5 points of growth cushion in our model. So it gives us doors A,B,C, D E and F every quarter. So we know what those doors are in our model. we tend to put our guidance at the lower end of what our KPIs say we need to do. This year, we added layers of conservatism for Athena. We wanted Athena to be pure upside. We wanted Marigold and the synergies that we drive upside. And then we want to political, which we break out anyway to the upside. So the fact that we beat by $26 million in the first quarter, we felt comfortable rolling through the year. We obviously felt comfortable in rolling the next or I should say, adding to the 2Q guidance by $4 million. Holding 3Q and 4Q are holding out quarters consistent is consistent with what we do as our model anyway. So I know we've gotten questions on going from 29% organic growth to, call it, low 20s in the 3Q, 4Q. That's totally consistent with how we've guided in the past and it wasn't meant to anything related to a slowdown. It's just we're keeping our process and our consistent as our guidance.

And unlike other years, because of the Marigold acquisition, we actually gave guidance for this year early. So if you take that raise for this year, plus the first quarter raise for this year, we've already raised this year by $55 million on the top line. So -- and about consistency, what a lot of people don't understand is, yes, 60% of our revenue is subscription. You get a lot of visibility into that. But even our utilization fees, we have 1-year contracts on most of that. So we're not including it in subscription because it's only 1 year, but it gives us unbelievable visibility into our business, and quite frankly, even in what appears to be a tough economic environment, we continue to see our growth at the rates that we expect it to be at.

David, I'm asking you a broad question about the competitive environment. So you compete against legacy Marketing Cloud, you compete against potentially horizontal AI platforms. What do you want to highlight on what's happening? What are the moats around Zeta? And then also, this week, there was obviously the LiveRamp acquisition. Like how does that change that competitive dynamic?

That's a whole lot in one minute. Yes. Well, so let me start by saying we love LiveRamp. We've been partners with them for years. We love [indiscernible]. We've been partners with them for years. I see this as a major win for Zeta both with our existing clients and our partner there. And I think a lot of the other agencies are going to be looking for new solutions, which data can provide for them. So I think we're in a very unique position to win both ways. And once again, we -- I will say, I thought this is a brilliant acquisition by Publicis. This was a really good decision on their part. And we spoke to them at length yesterday. We're seeing them multiple times this week, and I think that's going to work out very well for us once again, as I expressed. We haven't seen any horizontal AI competitors at this point. Just to be very clear, we don't even see them moving into what we're doing. We're having lots of conversations with the horizontal platforms to integrate them into what we're doing and integrate them into our stack as we've already announced with open AI today on the ad side and had already announced working with them on the athena side. As it relates to the marketing clouds, listen, these are great companies. I sort of joke we compete with a few small companies, right? Salesforce, Oracle, Adobe, Trade Desk, the truth of the matter is most of their technology is built for where the market was, not for where the market is going. We're in the biggest replacement cycle I've ever seen for marketing clouds and we are winning at a disproportionately higher rate, and we expect that trend to continue.

Incredibly exciting time at Zeta. Chris, David, thanks for being here.

Thank you, Brett.