All right. Hello everybody. My name's Brett Miller. I'm the Co-Head of software investment banking at J.P. Morgan. 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 omni-channel data-driven cloud platform that provides enterprises with consumer intelligence and marketing automation software, helping brands personalize marketing across channels, including email, 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 LivePerson and Inovalon. 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, an AI decision engine, or some combo?
Well, let's start with yes. I mean, 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. You know, if you look at the way we operate today, we're ingesting 100% of a very large enterprise's first-party data. We're matching it with our data. In the United States, we match at 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 trillion-dollar TAM, right? It was just a very good place to start. It's not where we expect to finish.
I spent a lot of my time today on the debate about the SaaSpocalypse and whether SaaS is going away. What is your view on this debate on the disintermediation by AI?
Well, I think it's gonna be a lot like the dot-com world, except I don't think we're gonna follow that type of bubble because most of the enterprises that are making these investments have, you know, trillion-dollar balance sheets. They're not startups. 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 gonna kill Walmart. It was gonna kill JPMorgan Chase. It was gonna kill Federal Express. In all those cases, those organizations adopted those technologies and became juggernauts. I do think I mean, first of all, right now, all funds are flowing to AI hardware, right? That's one challenge that software companies are dealing with as public companies.
The other really interesting thing is today nobody's willing to take a risk on who's gonna be the winners, who's gonna be the losers, and everybody's sort of throwing the baby out with the bathwater. If you think about companies that are going to win, they're gonna 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 companies that have data at our scale are all trillion-dollar companies. You're 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. According to an independent Forrester survey study, for every $1 a client spends on the Zeta Marketing Platform today, we return 600% return on marketing spend. 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%. I think over the next quarter or two, you know, investors are gonna start to figure out there are gonna be some winners. There are gonna 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 gonna have to figure out how to pivot their businesses to survive, and I think you're gonna 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.
Yeah
that's gonna be tough. The other thing, of course, is we're already partnered with OpenAI. 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. 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 OpenAI and help them run their advertising. We're gonna bring our enterprise clients into the OpenAI ecosystem, and we'll 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?
I mean, listen, we think OpenAI 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 partnerships with them around serving ads into the ecosystem, 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 OpenAI, both through serving ads and through our GEO platform.
Incredible. We've mentioned Athena a bunch. Why don't we just up-level for a second and give just a quick description of Athena, and then also, like, what is the workflow that it's changing for your customers?
Well, we'll step back a little bit. If you think about it, humanity has always communicated through voice, right? Well, I mean, I shouldn't say always, but for, call it 400,000 years. In the 1950s, we created this thing called the keyboard that sits between most humans and technology, I think most of us find it 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 asking for outcomes from the platform. Athena can change the screen in front of the client.
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 costs by an average of 7% per customer acquired." Athena will walk through how a client can get to those outcomes. The way I equate it, and I think many people in this room probably use Bloomberg terminals, right? What percentage of your Bloomberg terminal's capabilities do you use on a daily basis?
1%.
1%. That's I've heard 1, 3, 5. It's the same thing for most software, right? We've built a fighter jet that our average client knows how to fly a Cessna. Athena becomes the co-pilot for how to get to those most valuable components of the platform that they don't know how to use on their own. 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 agentic 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 four-year average basis, this will be our fourth year of greater than 30% organic top-line growth and greater than 50% organic EBITDA growth. What we're doing is working because our clients are consuming more of it. They're growing with us. As we show a greater and greater return on investment, we believe we'll continue to see that growth.
Yeah. We'll come back to the metrics and let Chris brag about those in a minute. On the 700% you know, increase in agentic interactions, like, in the 1% of the Bloomberg, to 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. Athena's 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. 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 them ask for before. You know, for those of you who don't know our business well, we have three 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.
A channel might be Connected TV, a channel might be online video, it might be online contextual, it might be now plugging into OpenAI, 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, 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 three channels in that same period. What we've 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. The reason for that is because the flywheel for intelligence starts with one of them.
The data that informs acquisition further informs the data that's necessary for retention, which further informs the data for monetization back to acquisition. The return on investment is substantially greater than our average of 600%. 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 one use case to three use cases, is Athena. 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?" That's how it's already starting.
You're not explicitly monetizing Athena yet. Talk about that decision of when does this become, you know, a line item in your P&L versus when is it just something that drives retention in ARPU?
Well, it's driving ARPU growth. I mean, we had a 21% ARPU growth in the first quarter.
you know, and last year our net retention rate was 120% as a company. We guide to 110%-115%. We were actually well above that in the first quarter. When you look at what Athena's doing, she is driving a massive uptick in our utilization fees. 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, 'cause it's the exact same model.
It's as we run messaging, or we place an ad, or we run a Connected TV ad, we charge.
you know, a fee for that. You know, we've batted it around. There will be an opportunity at some point to build, I think, analytics products and extensions around Athena.
Today, if you look at it, our 189 global Super-Scaled 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. We have some clients that we have 700 basis points - 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. 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, you know, what I think last year we were about $1.35 billion, and then this year we're projecting $1.75 billion.
$1.78, yeah.
$1.78 billion.
You know, that 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.
Yeah
Athena's better served today-
in driving that massive uptick in utilization.
Any plans for the future in how you'll monetize AI differently than you're doing it today?
Yeah. I mean, there's a lot of different ways. Back to the original premise, as you think about Zeta, 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.
roadmap, we'll begin to charge for those products and that will be commensurate with other AI products.
In terms of managing token costs, one of the sessions as of this morning, one of the companies said that they basically had no idea how this was gonna evolve, and they're learning in real time. Like, how do you think about?
Well, we are not that.
Okay.
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. SPADE is an internal proprietary workflow management tool. Last quarter, we publicly announced 75% of our internal new code was generated automatically. 75%. We're ahead of Google.
which is even shocking to me. It works because of SPADE. A programmer goes to SPADE and tells SPADE the type of code it wants to create. SPADE looks at all of the available large language models, which include ChatGPT, Claude, Gemini, you know, 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 least tokens in its generation. For security it might use Claude, for programming it might use GPT, for publishing it might use Gemini. Once it completes it sends it to another program called Zappy. I don't know where we come up with the names for these things. Zappy then QAs the entire thing, sends it over to an architect, who reviews it, pushes a button, and it goes generally available.
Literally we've talked about this and I'll sort of mention today, we're gonna be rolling out the next generation of Athena, which will be Athena for agencies.
Make up about 20, call it 25%, less than 25%, but of our revenue. The product itself would've taken us two years to develop two years ago. We're gonna have the entire product done in less than four 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. I mean, by way of example, we've grown the business again on a compounded four-year growth rate of 30% grade or organically. We've grown headcount just about 10%. I think we can even slow headcount growth even further, and we expect to be a 20%+ organic growth rate company for many years to come.
Speaking of the quarter, great quarter. Another great quarter. Rule of 67 growing 50% year-over-year, and over 20% of that is organic.
20%-29% was organic.
Which is over 20.
Which is well over 20.
It's well over 20.
I mean, it's over 20.
So-
it could be $20.02.
it's approximately 30.
That sounds better.
Chris, if you were to pick a couple drivers of the quarter, and then also talk about where the growth, you know, that organic growth is coming from.
Yeah. 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 were working in tandem. You 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%. Nine 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 three times greater than what we require from our model. As David mentioned earlier, from an ARPU perspective, 21% growth. Our model is 12%-16%. David linked it back earlier to channel expansion and use case expansion. Two 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've been less than 10% of our portfolio. Today, that's double that.
We're approaching 25%. That metric, number of scaled customers using more than one use case, grew 50% year-over-year. Those using four or more channels.
could be any channels in tandem, grew over 40% year-over-year. 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. I'd call it two to five points on the top line.
Yeah.
The other thing really is Athena.
We're seeing Athena out there, and we're taking meaningful market share.
from competitors, and one of the challenges we have as a public company, right, is are you a CRM platform? Are you an activation platform? Are you an ad tech company? Are you 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.
Yeah
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. They manufacture and sell their own apparel across multiple brands. This is a company based in San Francisco. It had been a total Salesforce shop, and we were able to rip and replace them out. We also replaced three other vendors in that because Salesforce, you know, can't provide everything a modern marketer needs.
Yeah
outside of, you know, a very sort of narrow CRM and CDP capability, whereas we're able to bring CDP, data cloud, you know, best in breed data activation to CRM, customer acquisition, and customer retention. We were told we were in the top three going into the end of the sort of ninth inning of the process. We asked if we could come in and do an early demo of Athena. We did the demo of Athena. They called us the next day for pricing.
Nice.
Yeah. It's really I think Athena is gonna be a major game changer for our company.
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, you know, drivers of that leverage?
Yeah, what we've done a really good job of, and David mentioned earlier, is automating more and more of what we have. We have kind of a philosophy in the company of where is value created. We're creating the world's best products. We put resources and investment in engineering and the tools they use, selling it as fast and efficiently as you can in the market. We put resources in quota carriers. Everywhere else, we cut, we trim, we automate.
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, adjust the EBITDA margins and free cash flow margins faster than the rate at which we're growing the top line. The rest of the year, we'll get back to very strong adjusted EBITDA and free cash flow margins as well.
It's also important to note that we built a lot of this stuff ourselves. As everybody's now talking of the evolution of AI, right? It's starting with large language models, and it's moving to what's called inference models, right? I don't wanna bore everybody in the room with this, but we've been building inference models for five years. The idea that one algorithm can focus on one 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. You know, 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 big basis for that.
Yeah. The quarters are often driven by shifts in the mix shift, the last quarter you talked about agency wins and social being the big drivers. Why don't we just spend a minute on mix shift and how what that did for the quarter and how you think that's gonna evolve?
Yeah. We disaggregate revenue in a number of different ways, but one 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%-75% of our revenues. I'd call it a gross margin of 70%-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.
Meta is a great example. David talked about others. That's about, you know, call it 25% of our revenue. It has a lower gross margin profile.
A lot of the inventory gets passed through to the customer. What we've found empirically is that when agencies, which have been, call it in the last two years, a new buyer of Zeta, and they've grown and scaled to, you know, approaching 25% of revenue, they first test Zeta data, and they first test our platform with social. 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 on Zeta's channel. These two large wins, like patterns in the past, started in social, and it's our expectation that as they grow, they'll migrate to direct.
take some pressure off of the gross margin side. 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.
It's important to note that we're really the only platform of our type that plugs into these walled gardens. Agencies start with us because there's nobody else who can actually do this. 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.
You've touched on this once before, maybe twice before, but you talk about in your words, Super-Scaled, which customers, which is my favorite metric that any company displays.
Well, we're gonna move to super duper scale.
Oh, that-
Yeah
Even better. On the Super-Scaled customers, you know, you're at 189 of them, I believe, and you're scaling that ARPU pretty significantly in that cohort of customers. One, how are you continuing to keep the momentum, gaining those customers, and what is driving that ARPU expansion?
There's a, for those that know our story well, and for those that are new that wanna 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 five years worth of this slide, that the vast majority of the time we are not beholden to an RFP because we are proud to start with a $50,000 pilot or $150,000 proof of concept. What we found is that those very small pilots in the first 12 months almost get to $1 million in spend, which would then, you know, flip them over to that Super-Scaled category. Beyond that, our fastest growing set of customers are those that have been with us five or more years.
To David's point, it's taken some of those longer tenured customers to find out where are all the corners in the platform that I'm not using today that I should be using. Athena unlocks that to everybody, it has the potential to take those that are earlier in their life cycle and have them climb to that much higher level of 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, you know, I had two or three salespeople in the room, and they were all really nervous about getting this deal done, and the CMO of this very large company asked me how large I thought the test should be to really get to a statistical sample. I said, "Listen, I wouldn't start with any more than $10 million." If we do more than $10 million, it's really gonna get us past the point of diminishing marginal return. If we start with that, it'll give us really good statistical data. They were like, "Okay.
Yeah.
We're not just taking existing clients and growing them, which has been our traditional business, to Chris's point.
He's totally right, the credibility that's now coming with our current size, scale, and return on marketing spend is leading clients out of the box to start at bigger numbers than we've seen before.
On that dynamic, your net revenue retention rate is remarkably consistent and considerably high, 110%-115%.
Last year it was 120%.
Right. It's the consistency of it, 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 retention?
Well, 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, right?
It's still statistically similar. A lot of the companies we start with, we're starting with a small pilot and you scale. That actually leads to a higher net retention rate, right?
Of course. Yep.
They're growing and growing, and I think that Listen, 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 it greater than 92%. We remove the personally identifiable information from a regulatory and keeping the consumer's data private. The algorithm then gets incredibly smart on how your customers came to be your customers. What did they read? What did they search? What transactions did they do? We go into our data cloud. Let's say just in the U.S. we have 245 million opted-in people. We'll say, "Okay, great. These 50 million people are already your customers. Don't waste money marketing to them." Think about how often you get an ad for a product you already have.
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." Now you've gone from 245 million potential customers down to a million. You hyper target 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. What happens is the longer a client's 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 gonna feed all of their first party data to a large language model. Then of course, all of our data, all 555 million people multiplied by 5,000 - 7,000 data elements, multiplied by all of their web behaviors across trillions of active pages on the internet, has never been fed into a large language model ever, nor will it. That's our proprietary data for training our models in partnership with our clients' data.
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 gonna fold a few questions together here. One, 19 consecutive beat and raise quarters, as David mentioned. After this last quarter, you did it once again, raise your guidance around revenue, EBIT 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 two to five points of growth cushion in our models, so it gives us doors A, B, C, D, E, and F every quarter. 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 to be upside. Then we wanted political, which we break out anyway, to be upside. 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 or holding out quarters consistent is consistent with what we do as our model anyway. I know we've gotten questions on going from 29% organic growth to call it low 20s in the, you know, 2Q, 3Q, 4Q.
That's totally consistent with how we've guided in the past and wasn't meant to infer.
Yeah
anything related to a slowdown. It's just we're keeping our process and our practices consistent as our guidance.
Unlike other years, because of the Marigold acquisition, we actually gave our guidance for this year early. 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. About consistency, you know, 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 in our utilization fees, we have one-year contracts on most of that. We're not including it in subscription 'cause it's only one year, but it gives us unbelievable visibility into our business. 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 gonna ask you a broad question about the competitive environment. You compete against legacy marketing clouds, you compete against, you know, potentially horizontal AI platforms. What do you wanna highlight on what's happening? What are the moats around Zeta? You know, this week there was obviously the LiveRamp acquisition. Like, how does that change that competitive dynamic? That's a whole lot in one minute.
Well, so let me start by saying we love LiveRamp. We've been partners with them for years. We love Publicis. We've been partners with them for years. I see this as a major win for Zeta, both with our existing client, and our partner there. I think a lot of the other agencies are gonna be looking for new solutions which Zeta can provide for them. I think we're in a very unique position to win both ways. Once again, we I will say, I thought this is a brilliant acquisition by Publicis. This was a really good decision on their part. You know, we spoke to them at length yesterday. I think that's gonna 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 AI platforms to integrate them into what we're doing and integrate them into our stack as we've already announced with OpenAI today on the ads 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.