Zeta Global Holdings Corp. (ZETA) Earnings Call Transcript & Summary

Good morning, and thank you for joining us today, obviously, in person as well as those virtually. We have an exciting and informative day planned for you. We have new product releases, new members of management, customers and marketing experts you'll be able to hear from and engage with. New structural views of where we believe we can take our adjusted EBITDA margins and free cash flow margins while sustaining our organic at least 20% revenue growth rate and new financial metrics that both underpin past performance as well as our future expectations, all intended to demonstrate the theme of today's Investor Day, a theme that's been entirely generated from your feedback. They can be boiled down to three areas: First, durability, the durability of Zeta's proprietary data, our competitive advantages and our revenue growth rates, the predictability of our business around the ROI that we generate for our customers as well as the consistency of our results and profitability. You'll hear today how we help our customers make more money and what sustains our margin expansion. So with that, let me kick things off with a few slides, and then we'll dive into the agenda and the rest of the day. With 16 quarters of track record as a public company under our belt, we have enough of a sample set now to draw some conclusions and compare ourselves to cohorts. One of those cohorts is through revenue growth and free cash flow margin expansion. And there's a misperception in the market that there's a trade-off believed to exist between driving high growth and increasing your profitability, maybe because so few public companies have been able to do both. As you're familiar with, Zeta's model is to grow revenue each year at least 20% on an organic basis while investing principally in sales, marketing, R&D and extracting savings everywhere else. Case in point, over 500 public technology companies, that's a lot. No one knows that more than you as investors and analysts. However, there have been 22 public technology companies that from 2021, the year in which Zeta went public to what's expected of them this year that have grown revenue at 20% or greater every single year during that period. That's not a lot. And that's frankly an accomplishment in and of itself. But there have been 8 that have been able to do that and that's the operative word, and expanded free cash flow margins every single year over that period as well. Zeta is one of those 8. It's rarefied air, and I would argue it's the epitome of durability. Now as an investor, you're not just looking for durability, you're looking to underwrite predictability. In every year, Zeta sets growth and margin expansion goals. And in the period in which we've been public, we've exceeded those goals, but not to be overlooked. We're the economic conditions that existed over that span of time. In fact, most of which were known for their headwinds. For example, in the aftermath of COVID, in 2021 and 2022 with global supply chain disruption, many growth rates stepped back, Zeta's compound growth rate over that period of time was 27%. In 2022 and 2023, amidst rising inflation, Fed rate hikes certainly impacted the consumer, you would think marketing and advertising budgets as well, Zeta's compound growth rate over that period was 26%. And as we sit here today, through 2024 and the beginning of 2025 with new U.S. tariffs shifting monetary policy, federal workforce reductions, broader workforce reductions, each of which causing their own recessionary fears, based upon our guidance, our growth rate over that 2-year period is expected to be 32%. The point is Zeta's growth has been durable and predictable throughout, but not just durable and predictable, increasingly more and more profitable. Since going public in 2021, we've increased our annual free cash flow generation by more than 8x and on a compound growth rate basis over that period, 70%. We've taken our free cash flow margins from 4% to 11% and have effectively doubled our free cash flow conversion over that time period as well. Not only do we see these types of rates of improvement as sustainable, but what I'll talk through later today to carry us even beyond Zeta 2028. So with our agenda of durable, predictable, profitable growth in front of us, let's dive into what we have in store for the rest of the day. In a moment, I'll hand the baton off to Steve Gerber, our President, to talk about Zeta's competitive edge. You'll then have a chance to hear from our Chief Operating Officer, Matt Mobley, talking about the drivers that have contributed towards our margin expansion to this point. But I think more interestingly, what are we doing today to leverage automation and AI to further bend the curve down. We'll then shift gears a bit. You'll hear from Chris Monberg, our CTO; and Neej Gore, our Chief Data Officer, who will dive into the platform and talk about many of the new products being announced today in even more detail tomorrow at Zeta Live. We'll take a break. And then after that, we'll hear from external stakeholders through the form of panel discussions, first, hosted by Ed See, our Chief Growth Officer; and then by Jed Hartman, our President of Activation. I'll jump into the financials, and then David will come on stage, wrap things up, pull it all together, and we'll have an extended Q&A session with the entire group. So with that, let's kick things off and join me in welcoming Steve Gerber, our President to the stage. Steve?

Good morning. Thank you, Chris, and thanks to all of you for being here. So let me start with a question. How many of you saw the Yankee game last night? Thought there'd be more sports fans. So if you didn't see it, Aaron Judge launched a moonshot that clinged off the foul pole. It changed the course of the game and quite possibly the Yankees playoff run. The announcer said for the last 10 years that ball would have landed foul. Last night, it was fair. Same swing, new conditions, better outcome, new story. After 16 years, at Zeta in '26 at the intersection of data, technology and marketing and is a true believer in the power of parable, I can't help but see the parallel with us. We're taking the same swings but in better conditions and more are landing fair. But greatness, as you know, isn't just about [ goudy ] stats. It's doing it again and again and again. It's meeting the moment. So today, I'll show you why we are meeting the moment and how we're making growth predictable for our customers and for Zeta. Now let's go way back to two years ago, the last time that we met in this setting. Since that time, we put up some [ goudy ] stats. Zeta has outperformed on every single dimension. Growth metrics, customer metrics and innovation that moves the needle for our customers and for Zeta. Most importantly, we believe this is outperformance with headroom. At our town hall yesterday with our entire company, we said something that we truly believe. We are just getting started. But we know that it's more than just putting up big numbers. Investors value what endures. Durable growth, predictable profits, defensible advantage. That's the standard and that's meeting the moment. Our model delivers on each of these. And today, I'm going to go deeper on that through the form of answering the questions that matter. I will talk about why now is the moment, why Zeta is built to meet it, why acceleration is structural and why growth is profitable and predictable. So first, why now? Why have conditions changed? So the market is at an inflection point. These forces, which I will detail further are converging. That's the setup for category change, because when forces converge, markets reset, and that's what we're seeing. The replacement cycle I talked about two years ago is accelerating. We're seeing cracks in legacy stacks. Only 33% of MarTech tools are currently used by enterprises overbuilt and underused as the recipe for change. At Zeta, we've seen a 70% increase in RFP volume. And this tailwind isn't felt just by us. The whole cohort of scaled insurgence is growing 3x faster than the incumbents. The conditions are changing. This is the changing of the guard. And that's what we're seeing. So it starts with AI, but it's not just AI. AI is the spark, but what we need to recognize is that AI is a catalyst for replacement, but capitalizing on the promise of AI beyond polishing memos and generating [ CAT ] creative images is hard. A recent report that many of you saw from MIT showed that 95% of AI pilots fail. And here's a big reason why? AI is fueled by data and data pipes at most enterprises are leaking. That's why as enterprises rethink their approach to technology in the AI era, they are starting from the ground up not from the shiny presentation layer down. Now that's just one consequence of a change in tech strategy. From the beginning of the digital era, CIOs would pick from one of two approaches, best-of-breed products or single-sourced vendor, usually implemented by an SI. That's why you may have heard a CIO say something like, we're a Salesforce shop, even though Salesforce is 17 different companies. This approach has led to the overbuilt underused stack of today. But the old ways are changing. Rather than getting locked into a cloud as container, enterprises are constructing cohesive consoles that are comprised of components, modularity, not monoliths. Fully 77% of the enterprise RFPs that we see are focused on one thing, unbundling clouds. Right. I got through 6 without a problem. The modularity isn't just cleaner, it's faster to value. 68% of replacements are evaluated within six months. So proof is the gate to scale. That's why the CFO is now in the room. 79% of MarTech purchase decisions have CFO decision power. That's a change. Enterprises are now buying the business case, not the bundle. And I'll finish this with this statement, Replacement cycles turn when buyer standards change and boy, are they changing? The other big change is the elevation of the CMO. Along with the CFO, they are at the table making AI-powered tech decisions. Today, CEOs have put CMOs on the front line of growth. CMOs overwhelmingly see AI as a game changer. 5 and 6 -- AI is a game changer, but the same 5 of 6 believe that their infrastructure is too rigid and fragmented to capitalize on the power of AI. So the gap is not ambition, it's architecture and under the hype most programs stall on a shaky data foundation. And that's happened even after massive investment in getting their data house in order driven by a fight for fidelity after the changes in ID and new consent rules. And a demand for data control because in the last era, enterprises gave that up to the walled gardens. You raised that to the power of AI and first-party data at enterprises has become the center of gravity. It's become a strategic asset. Now the investment in Snowflake and Databricks more than 1,300 enterprises are at scale with those companies and the like. Getting that done was necessary, but it's not sufficient. The question remains, once that is in place, what runs on them? And the winners won't just have the data to run where the data lives and turn that into sharper, faster decisions and measurably better performance. Better performance comes from a better system, a new system that is modeled off of what the Walled Gardens didn't, with first-party data at the core of an enterprise's ecosystem, authenticated identity is the connective tissue. It's how to get precision and scale. One brain coordinating both paid and owned channels just like the Walled Gardens. But again, ambition is ahead of architecture. Marketers want personalization across the journey, but fewer than one in three can actually do this at scale. That's the personalization gap that we've talked about before, and it won't close with channel-centric tools. It needs one decision engine across every touch point, which is why convergence is identity-led and outcome-driven. Convergence is driving the birth of a new category, what we call AI-powered marketing. This is an answer driven system, not another stack. It's a smart system that gets smarter over time, and delivers better results over time. It requires three things: authenticated identity, a central decision engine and closed-loop measurement. It delivers precision at scale, faster time to value and compounding returns. Bringing this to life is the catalyst for the industry shift from disconnected stacks to a cohesive system. So why is this the moment? The switch is underway with three shifts in the marketplace. The replacement cycle is accelerating because buyer standards are changing. It's not just AI. Buyer standards are changing. And because of that, a new category is emerging. So the market as it moves from stacks to systems and systems that prove outcomes faster and more predictably, those are the ones that will win this cycle. So why Zeta? Because we are purpose-built for this exact switch. This is what we've been doing for the last 8 years is preparing for now. Our job is to make it simple for enterprises to transition to AI-powered marketing and turn measurable results into a growth engine. A growth engine for enterprises and a flywheel for Zeta. But why Zeta begins with our reason for being? Our promise is simple, compelling and provable, more value with Zeta than without. It starts with speed on ramps and weeks, outcomes in a quarter. Simplicity, the easy button, on to AI-powered marketing we are consolidating stacks, which is shrinking the time to value and driving material savings. Lastly, certainty. Forrester's TEI shows the 6x return on ad spend. That combination makes it hard to compete with Zeta, and it also showcases Zeta's Edge. The Zeta Edge is foundational. We run where the data lives. When people hear Zeta data, they think super graph, which Neej will go much deeper on today, that's our fused identity and intelligence system. And that's true, but it's only one part. Our data foundation also includes low- and no-code connectors that ingest data from all corners of an enterprise and outside of their four walls, and it pushes it back out as actionable intelligence. And it runs inside a container with a robust yet flexible data model. So it can serve as the system of truth to drive the business from. That is durable infrastructure. It is not episodic activation, and it's the base for everything that follows. On that foundation sits one decision engine, answer driven coordinating painted own channels. We built this system to answer the fundamental questions of marketing, who to reach, what to say, how and where to execute, decided in context, not channel by channel. That's how you close the personalization gap and get precision at scale, but advanced AI tools let us go a step further, it allows us to answer the hardest question of all, why? Why is what unlocks a flywheel for our customers and it locks Zeta in. And when we think about our data foundation, it exists to do one thing. To create an enterprise decision standard. Now standards is something you're going to hear a lot about today. Another area where we've done it is to create a proof standard. Along with my co-author Ed See, who you will hear from later on today, we developed a new index called the true value of marketing, which was launched last week in the Harvard Business Review. It is one number to value -- to measure value creation. Think about NPS for marketing. So if NPS changed how companies listen, TVM changes how marketers decide. The core idea is that one standard, one truth beats 1,000 dashboards. It's the core of My Zeta Live panel tomorrow, 9:15, I hope you all get there early, and it will receive more support in the ecosystem later this quarter and into next year because our goal is to make this ubiquitous, ubiquitous like AI. AI is ubiquitous, but it has to live where users actually work, not a separate screen. So think of a Bloomberg's dial command center, one screen where work and answers live side by side. Ask and play in English, see the answer and execute with approvals. That's how AI becomes the new UI across the enterprise. And that creates an enterprise interface standard that my partner, Chris Monberg will go much, much deeper on today and tomorrow at Zeta live. So I know what you're thinking. How did I miss the Yankee game last night. You may be thinking that couldn't others do this too. And the short answer is that design is destiny. Not all platforms are built for this era. Workflow first tools, optimize point-and-click journeys. They're great for manual teams, but the lift is still human powered. Channel-first tools optimize individual lanes. They sure are strong in silos, but they're weak across the whole. This is an era where the whole is greater than the sum of the parts. Zeta is data and intelligence first, composed on the data foundation, learning in place and judged by outcomes. Workflow-heavy suites, especially those aimed at SMBs moreover, are the most exposed as general AI Copilots compressed the UI, and in that context, it's data quality, decisioning and measurable outcomes that are the differentiators. The bottom line, AI is only as powerful as the data that fuels it and the outcomes it drives and not every platform is built for that. So why Zeta? Why are we meeting this moment? I talked before, why now buyer standards have changed. We are the ones aligned with buyers' needs. The Zeta promise is showing, not telling our incremental value. We have a warehouse native core that's easy to adopt, hard to leave. We establish enterprise standards across decisioning, proof, interface. And most importantly, we are optimized for AI. That is why we are positioned to meet the moment. So why are we accelerating? Well, the standards are getting set. The flywheel is starting to turn, but we know we need to speed up. The window of opportunity is open, but we know it's not open forever. So we have three drivers of outsized growth that we are pulling the levers in parallel. First, AI-powered operations, expand capacity and capability at a lower cost per unit, that's how we hit that 25% plus adjusted EBITDA margin. Second, what I've come to call impossible products so that we could seize the leadership position in the AI race, leading to a doubling of our scaled customer base. Third, which I will go much deeper on and then my partner, Ed See, will have a panel today and tomorrow talking about, which is packaging and paving that make it simple to start and obvious to expand. That's how we get to a 4x ARPU over time. These are individually important, but collectively, these are transformational. Together their speed to scale and a repeatable path to accelerated growth. I'll go through in more detail, but each of the speakers after me are focused on each of these topics. So first, I'll talk about AI-powered operations. This is Zeta-on-Zeta. We run our own operations on agents, not on tickets. So what does that mean? It means on-boarding is 80% faster. Cost of revenue was 31% lower and productivity is tremendously higher. Same team, same global footprint, new tools to deliver more throughput and less variance. That's how we scale execution without scaling headcount. You're going to see a lot about impossible products, impossible products, raise our trajectory. Neej and Chris today and tomorrow will talk about our incredible, I mean, impossible road map. But I'm going to spotlight on these four to bring it to life for you. Vertical clouds, think about health care or commerce or advocacy. Verticals in which the right data at the right time is the difference between success and setbacks. Zeta Media Engine in partnership with Snowflake is the easy button for the world's largest enterprises to capitalize on AI-powered marketing full stop. Prospect CDP is one of one to disrupt customer acquisition. And lastly, Zeta Answers, that's what is fueling AI-powered marketing. Now the reason I spotlighted these four is that they blend both owned and paid channels, one brain, every channel. They're practical innovations. They move the numbers for customers and for Zeta, and their Blue Ocean. Others cannot play here, without our data foundation without our capabilities. Now I just want to come back to why impossible, and we've even got the TM against it. To me, these are products that make our customers say wow and CFOs say yes. But it's about OneZeta of how we bring this all together. OneZeta is how we make it simple to scale AI-powered marketing. We build on a win. We take the first on-ramp, capture what works and then make it a repeatable model. We always show and we don't tell. Every expand and extend step comes with a business case tied to the numbers that matter. And then lastly, it's what I call Growth-as-a-Service. We add the next use case without any rewiring still aimed at the same North Star metrics. So for customers, this means fewer vendors, one brain, faster wins. For Zeta, each win raises our value and makes the next win easier, more predictable. It's the conversation mover from tactics to predictable results. And with OneZeta, we are simple to start, obvious to grow and super hard to leave. Now many of you asked why Marigold, the hidden question. We really think of Marigold as an accelerant for the OneZeta model impact. It's a bigger top of funnel, more enterprise doors and new regions. It's deeper signals, loyalty and first-party data at scale. And it's a new distribution option. It's a clear path to a bigger and more impactful publisher cloud. And the category play is compelling. AI-powered loyalty is a better offering where there is no sales force, there is no Adobe to rip and replace. As we scale the same standards across a larger base the unit economics improve, that's operating leverage that we can count on in the quarters and years to come. So when some acceleration is happening because OneZeta ignites a growth flywheel for us and a performance engine for our customers. Here's how it turns. We embed the Zeta data foundation. We set the decision standard across all of the components that I talked about. We power decisioning and orchestration through both paid and owned channels and then we closed the loop to prove our value. Proof, unlocks scale, scale unlocks profitability, profitability unlocks predictability. Each cycle raises our share of wallet while lowering our cost to serve. That is acceleration that could be measured and repeated, and that's what makes growth predictable. So predictability shows up in our math. When we go beyond land, expand and extend into embed, we see massive upside. Customers who embed, adopt more use cases and generate more revenue. That lifts unit economics and sets up the next turn. The point, expansion isn't luck, it's a playbook. And we have more than 80% of our customer base with headroom for significant growth because embedding multiplies impact and our unit economics. Now I'm going to walk you through some examples here because OneZeta has evolved from a sales motion into an operating model. However you enter with us, Platform Out, Media In or OneZeta as a system, the path is the same. Start small, show results fast and then make it part of how you operate. Platform Out, where we would start with the CDP or some other embedded technology, for a major retailer that was where we started, but the hinge point, where this went from smaller to bigger and bigger to transformational for them was when we were able to take Connected TV and make it an addressable channel for them. We were able to connect an individual to in-store visits and in-store visits to sales so they knew what to scale, that's knowledge they could not have gotten anywhere else, and that is something that's repeatable creating a flywheel for them. Media-In where we started with a smaller activation program. This is a major airline. We have gone from a spoke in their hub to a hub and some big spokes. And that's because they began to see that we knew more about their customers and their prospective customers than they did. We also were able to prove to them that loyalty did not mean devotion. So we focused on those loyalists that they were able to get more of share of wallet, because it all started with authenticated identity. Authenticated Identity is the unlocked to AI-powered marketing. And then what we've done more and more of is starting with what I call marketing-intensive middle market companies. The ones we're marketing is the distinction between surviving and thriving. And we've begun to pitch the full system out of the gate. When we do that, they commit to us. Everything connects. Nothing competes. All the tools are built for each other for us and our partner. The ZMP becomes the center of gravity and what that happens for us is it increases deal size materially in this particular case, 4x larger out of the gate, but even better, they are seeing much stronger results from us than without us with this change. Let me add one more for you, as I talked about authenticated identities, is the unlock to scale. We just met with a Fortune 50 company top 100 advertiser and talked about our AI-powered marketing system. Every program begins the same. We connect their first-party data to our SuperGraph. The CMO was expecting us to match at a rate of 70% or 75%. The gold standard is 80%. The first run came back at 92% and the CMO who we like to think of as a friendly said, "This cannot be, that is impossible". So they ran it again. They made a few adjustments. They worked with our team, wanted to make sure everything was connected properly and it came back with a new number, 94%. That is how you win in this era because these are not in isolation, the data foundation makes this repeatable and it ignites faster ARPU growth. I will now talk about how once we embed this data foundation, we take our share of wallet from that 1% to 2% range that we are starting at to that 5% goal that we have over time, embedding the data foundation with our SuperGraph at the center of their AI-powered system is the unlock for extended use cases increasing audience scale, expanding our share of marketing budget that we can address. And then ultimately, when you are delivering results at scale and you are locked in with standards you have pricing power. This is our end state. The cadence is steady. It's about one meaningful step per quarter until we get closer and closer to that 5%, and better unit economics fund that expand, extend and embed. This all comes back to business cases that prove our value, proof unlocks scale. So I said there were four questions that I was going to address today, but I do have a fifth. And it's the one that decides who leads this new era? How do you move from predictable performance to definitive leadership? And the journey that we've been on at Zeta is to become one of one. And the way we believe we do that is to set the standards to become the standard. And it starts with the embedded data foundation, the dominant data foundation, it's then on top of that, the three enterprise standards that I talked about, a decision standard for how the work runs, a proof standard for how it's funded and an interface standard that's a command center that people actually live in. With these standards, tools don't compete. They connect, reducing the cost of ownership and locking us in further. Together, these create a compounding growth engine, which makes us one of one. Companies that are one of one lead new cycles. What we've seen today is that the conditions have changed, and we are meeting the moment. I believe you can see why we have such conviction that only Zeta can lead the AI revolution and marketing. I'll now turn it over to my colleague, Matt Mobley. Thank you.

Good morning, everyone. We're starting actually on sort of the application of some of the technology on these pieces. So admittedly, I think the [indiscernible] side of this conversation will come when Chris and Neej come out to talk about the innovation that we actually create. But the -- my argument is to it, as I look at these things is the fact that as much innovation that we can create out there in the AI world, the problem is people are sort of like struggling to sort of get through sort of the notion of how they look at the applying it to the actual business. We -- we're in a world where there is a place where sort of AI is sort of ramp it across the organization. People are sort of pursuing sort of the options to it, but are people actually getting value out of the things that they're actually doing with it? We can create the sexiest agent in the world that does everything for you in essence that goes to it, but are the -- do people understand the expectation set within the organization that's out there. So -- as we look at it, we think about it, we're saying, "Hey, listen, Zeta is becoming this fully AI-powered sort of organization." It's not just about the things that we pass on to our customers, but it's also about the things that we create for ourselves in order to do the work and to accomplish the things that we want to do, at a level of being able to lower costs and increase productivity to those things. But also focused on not only operating leverage, but even as we think about like platform adoption, as they think about what pieces are people sort of using and being able to do within the platform every day, do the agents and does the AI help promote those things and educate our customer base and help them understand how to sort of move on to new use cases in it and ultimately giving them something in which we deliver to, be it the notion of mail or e-mail or SMS or all these things, but ultimately, all powered by the AI side of this thing. The challenge, as I was talking about, as I look at it, this is arguably, I would say that every company has this problem, which is AI is sort of ramping, its across the organization. They've all created a mandate. They've said, listen, you shall go forth and use AI in the organization because we want to drive cost down to it. But the reality is, is that it's sort of the value of AI is really locked up in those organizations because it's sort of opportunistic, enthusiast, sort of the tech guys that sort of get it -- they go out there. She grabs it, puts it on there and goes, "Hey, this is the agent that we're going to do." But it's in a small silo that can't have enough of an impact on the organization. So we took a look at the problem and said, "Hey, we have to rethink the model and order the way that the model of which we sort of adapt and sort of use that AI in order to be able to accomplish more with it." We can't just go out there and say the mandate, we have to actually set the expectation to it. So along with all of the innovation that we had, we created an operating model, that goes out and helps the organization sort of digest how they should think about AI. And in our operating model, we look at it from a standpoint of all the way from David Steinberg down to the the lowest individual within the organization, we're going to set expectations at every role of how much AI they should be using as part of what they do for a living. Also, we started to set it up. We know we do a -- we have a sort of a dual layer sort of model. One is that we govern it centrally so that we can have compliance and standards and figure out the right tooling, Think about how we're sort of going to approach all of the innovation that goes in, but we create local champions that are within every group within the regions that are out there so that they understand from the central governance gets past the local champions. They understand exactly how their SOPs work. They understand exactly how their processes work and all of those things, so that they can go apply it to the things that they do every single day. And they have expectations set at that level. They have a metric set at that level. So that there's no doubt on what they have to do with those things. We've created training AI immersion, we've set policies, and said "Listen, we're going to do everything, AI first." There's no sort of default. The natural default is everyone because of sort of adapting or adopting new technologies. You go back to sort of those human-centric ways of saying, "Well, that is the way we've done it." I can guarantee every time that if I do these 12 steps, we're going to move through and I get this sort of outcome to it. But the reality is we can do the same thing within AI, we just have to force that change in what is that sort of natural behavior that they have to it. And then we also look at things like cultural integration. How do we make it sort of part of the core of Zeta? How has it become part of everything that anyone thinks about, anyone that joins the company, they're going to think that I'm joining an AI company. I'm going in that the work I do is about orchestrating agents. It's not necessarily about performing it myself every time that's in there. So getting it in there creating cultural integration, we do this through not only just through the training, but also as we look at thinking about leaderboards, we're thinking about their everyday life that they going through. When I have to write a review about myself, am I using an agent to write my review, my self assessment every year or am I going out there and spending the five hours in order to accomplish those things. So every part of everyone's life, we're trying to integrate sort of the agents as we look at it. We have -- even when I talk about the roles, like here's the expectations that we set out for every role. So you'll have, you'll be an orchestrator sort of an AI-led role that's out there. Every role we'll have a classification. It will be enhanced, that's in there, so it sort of augmented, you'll be in that sort of range where 30% to 50% of your sort of role should be accomplished by the agent, by the AI, by all of the aspects or you're aware, and these are probably more roles that have a higher level of, I don't know, sort of ethical judgment, things like that, so places in HR, things in legal, that you would have to go out. Not everything can get sort of moved into sort of the world of the agent, but everyone will know what their expectation, even as we've started to roll this out in our pilot programs as we go through. We've seen -- we were predicting sort of 50% sort of productivity against sort of the things that they accomplish every day. What we're seeing is there's a phenomenal amount of return against those, versus the investment of the tooling and technology against even the labor in order to sort of go implement it, that goes out, we're seeing 10x sort of return on that investment that goes into the AI side. And I actually think that, that's just the start as we look at it. If we look at areas where we think about sort of the use cases where we've applied it, if we think about -- one of the biggest challenges for our customers is -- I have to migrate or our potential customers, I have to migrate from something that does e-mail or data or whatever it is today, over to a new platform. That's the biggest barrier that goes into it. What we've done now is create the agents in order to help them sort of make that swap over. So every tooling set, we have a sort of a scripting language, everyone like even the Salesforce does. All of these people have those things. But now we have agents that can look at the actual code, the things that they've built within there and recreate them within sort of the Zeta platform. So we removed the friction of people moving over. So we're seeing faster on-boarding as we look at it, even as we think about our sales side of this house, their ability to go out and understand like the individuals that they're getting ready to speak to the customers that they're going to go talk to, they have agents in order to help them prepare for those meetings, that are out there. And then on the product innovation side, where Chris and Neej will talk about, our ability to produce product faster to code, to make enhancements to the platform have been greatly increased over the fact that we have this sort of a deployable set of agents that go into our larger sort of workforce that's out there. And truthfully, it's not only just about Zeta, as Steve said, sort of Zeta on Zeta is arguably my life in this thing. But the reality is, even as we look at sort of rolling this out to our customers, we're giving them the ability in order to adopt these technologies. So we provide them sort of foundational agents, which are focused in the areas where all customers use the platform most. We're giving them agents that they can go out there and use those things much quicker and reduce the amount of time that they're spending in sort of the mundane task and thinking more about sort of the strategic aspects of it, then, we sort of graduate them through the more strategic aspects of it when we think about like forecasting all the way out into the ability of our customers to leverage the platform to build agents that are more specific and meaningful to their organization. It's sort of the -- as we look at it, it's build the trust, understand the technology, understand that the value it brings and the things that it unlocks for you, unlock value and then ultimately start to think about how you sort of transform the organization overall. The other thing I mean, I think this is probably sort of a hot topic within the organization. We're in the process of sort of evolving the pricing strategy. I mean, I think it's always a question and probably an obviously, in your space, you'll think about how our organization is going to monetize sort of the AI aspects of it? So we're in the process now of saying, listen, it's not only a question about monetizing AI, but it's also a question is, if the AI creates better adoption of the platform, if the AI unlocks more value, how do we remove the friction of the things that are actually happening within that organization as they go to adapt new aspects of it, think about bringing new agents on, get into new parts of the platform. How do we sort of remove the friction, monetize everything and then ultimately sort of a sign of value for the base cost that we have within there. So probably, I'd argue within -- maybe after the first of the year, we'll be launching sort of a new pricing strategy that goes out and looks at all of those things. How do we create a place where if you could remove all of the friction related just of the procurement side alone, the marketer could go out there and go, "Hey, I've had a new idea on the strategy of what I want to do. Let me just go do it because I know the contracts are already in place and the pricing is already in place for these things. And I can take the next step and actually go do something that's going to have a meaningful outcome to the organization that's in there." And I think that even as people have looked at sort of pricing strategies, a lot of them have sort of attempted to unlock these things, but the reality is, is they still create the silos that will exist within pricing. People price on entitlements and all the other aspects of it. The other side, even as we think about it within the AI side, within the pricing side, within the unlock for the customers, at the end of the day, for us, this is what we're chasing. What we know is, is that if you come in and you buy technology from us or you come in and you leverage sort of strategy aspects of it, the further that we can expand you out within the organization, obviously, the greater value of the customer is to it. Obviously, the stickier it becomes, as we look at it, someone is in from more of the strategic marketing aspects of it. We try to get them the platform. Platform we try to get the strategic marketing aspects of it. What we know is, is that with these agents with AI, we can create a faster road map to their adoption of more of the platform. We can have more clients that are considered sort of OneZeta who think of us more broadly in the application of their organization versus having us sort of contained into, "Hey, that's just an e-mail provider for me."That's just sort of a data provider that's out there. So we use those agents not only to help them progress but also to help them sort of move through our value chain, our sort of way that we look at sort of the organizations to it. We're even using it in the integration of the new organization. It's interesting to go in and be able to talk to Marigold and be able to say, "Hey, listen, this is how we've applied sort of AI in our world, but oh, by the way, this is how we're going to apply it in order to look at ways to optimize your organization." Everything from the things that we've talked about to what capacity can we create within the base that we're sort of bringing on and the number of employees out there. How do we allow them to innovate or integrate or migrate better to our platforms that are on the side? How do we start to bring all of these things together. And because we built the tooling that we've used within our own organization, it becomes the application to their side and allows us to unlock sort of the value and the opportunity within their organization much faster than what it would have been if we went through the channels before of just sort of the -- have multiple meetings and go through and go through all of the process that you would have as you think of it actually happens within those organizations. So it's been -- as we look at it, it's really an opportunity for us. I like to think maybe it's -- maybe it's because I work here, one of those things. But I look at it in a very simple way. Zeta is an AI-native enterprise. Like we're not going out there and sort of allowing sort of the organization that are just creating sexy tech and all of the aspects of it. We're actually thinking about the application of it within every aspect of it, be it within the legal side, the HR side, the technical operations side, the product and innovation side, we're asking ourselves like can we be AI first in every one of those things? Can we actually control -- as we look at the aspects of the organization through this notion that we are as much as an AI organization has anyone else within there. And so we've spent a lot of time. We think it's a default engine for speed as we call it, in order to achieve all of the things that we want to achieve. And ultimately, what we do know is, because we spent not only the time to build the technology, but the time to apply the technology that's in there, what we know is, for sure, we're the best partner for the organizations that we engage with to not only help them say, "Hey, by the way, here's a great agent you can use, but now we're going to show you how to apply it to your organization so that you can be successful in those things." So it's a two part. As I look at it, I like to consider myself sort of the stake to Chris and Neej's sizzle that's out there, but we'll bring Neej up now to sort of talk about those aspects of it, and I appreciate it.

Good morning, ladies and gentlemen. My name is Neej Gore. I've met many of you. And with Zeta Live upon us, this is a revolutionary week for Zeta, our customers, our prospects and even our investors, as we talk about our strategy and showcase new products. But there's something bigger happening in the ecosystem. This is a revolutionary era for all marketing technology companies. And if you look back to the 1900s when we had catalog and direct mail, and forward to the era of loyalty and demographics and forward again to data-driven marketing to now to the Answers era, the company that controlled the unique data set around identity was set up to succeed. This has been a consistent theme across all the marketing eras that we've seen. Now at Zeta, this is some recent benchmark testing we've delivered. Our data is delivering the moat that's helping our customers win and helping us win. In the last three months, we've run testing. We've seen using our data, customers see a 30% to 40% increase in prospects, a 30% to 50% reduction in CPAs, a 10% to 20% increase in conversion rate and a 10% to 20% increase in lifetime value. So the Zeta data model is the one that moves from category -- from commodity to category leadership. This is very important in the era that we're in today. The data is providing a moat around the entire business. Why is the data providing moat around the entire business. The first thing is that the data provides context when you're engaging with customers. Our data gives our enterprises a view of a customer that exists outside of their four walls. They can be more strategic in the way that they actually communicate with those customers. Our data also provides confidence around ground truth outcomes, less hallucinations. We've seen it before. We know it to avoid, and our data also creates a compounding flywheel where signals are accelerating engagement that then accelerates signals back into our graph. And so from every experiment in AI, and Steve talked about how many POCs fail, we are turning that into an advantage for all of our customers. Back in December, I talked about why and how I consider a data asset to be valuable. First and foremost, size, scale and durability. Is the data asset comprehensive? Does it last over time? Second, act to compliance, do you meet the needs of the future laws and the current laws? Are you meeting compliance guidelines? And third and perhaps the most important here, do you have a seamless AI activation model? Are you creating an unfair advantage for your customers? We're going to come back to this. The Zeta Data Cloud sees about 245 million U.S. adults every single month, on top of which, we stitch in about 1 trillion signals across data at rest and data in motion to create AI-powered intense scores around interest, around intent, around what someone is trying to do next. This is comparable to the Walled Gardens. And with the addition of LiveIntent, it's only made our graph stronger. And that SuperGraph that exists today is really like no other in the ecosystem, around identities, around signals, around identifiers and into intent, we source data, and we cultivate it into a very, very durable format. Returning to what makes a graph durable and predictable and profitable, 245 million identities in the U.S. about 90% of the U.S. adults covered, and that graph has grown over the last four years through all the regulation that we've seen. Seamless activation model. We have over 2,500 NLP powered and LLM powered audiences built into the platform for our enterprises to take advantage of. And number three, we are ahead of the curve on compliance. But it's not just about being durable and predictable and profitable for Zeta. These are the exact same capabilities that drive the who, the what, the when, the where and the why for our customers. We want to make sure that they are durable and predictable and profitable as well. This is very important. So the combination of our SuperGraph, meeting our AI is really what unlocks the power of acquire, grow and retain and gives us a one-of-one advantage in the market. Now there's something very important about this slide, that I want you to take note of. The shift that's happening in marketing today is moving from data-driven to Answers driven. Answers is what marketers seek today and with Zeta, the age of Answers has arrived. Zeta Answers touch every part of our platform. The answer questions about strategy, about discovery, about experience delivery, about verticals like Steve talked about this morning to what's next. They're built into all the applications we run and when interacting with our AI, they create incredibly powerful outcomes. I'm going to take you through some of these that we're going to showcase at Zeta Live and with some videos as well here. So the first one I'm going to talk about is answers that craft strategy. We are releasing the Executive Intelligence Hub. Imagine if you had one single app that looked across all Zeta data to give you your opportunities as a CMO around acquire, grow and retain all in one place, refresh daily and keeping you up to speed. This takes days and hours out of the work that a CMO and their marketing team need to actually operationalize from strategic to tactical. Answer, is what drive commerce. We are launching our Commerce Cloud. Retail is obviously a very important category for Zeta. Our Commerce Cloud in partnership with Fiserv sees brand affinity, sees brand transactions across 90 million Americans and about 250 million to 300 million transactions every month. We also see product purchases over 800,000 product purchase categories. With this, we're able to create retail diagnostics. We're able to create real-time analytics. We're able to create 2,500 brand panels to measure longitudinally across whether marketing is working, and you can answer some of the questions like you see here on the right. What's driving my brand's performance? Show me my average sale price versus my competitors, did my target audience spend and how much did they spend? Spend is a very important part of our commerce strategy. A lot of times in retail, marketers don't even know what the first question to ask, should be. So we have actually used a new agentic capability in retail diagnostics to give marketers a view of their scorecard as it relates to themselves and their competitive set. Retail diagnostics, again, is built directly into the platform. It taps into that partnership that we have with Fiserv and it really promotes our identity graph to give a view of the consumer and a view of the buyer like the marketer has never seen before. With retail diagnostics, you can also interrogate the data, you can ask questions of the data. So you can enter the conversational world and then proceed and ask questions that might not be available in the UI. Measurement. Measurement is one of Zeta's superpower. Answers that measure everything, everywhere, all at once. The measurement model needs to cross over owned and paid. The world today is not built for the measurement models of last year. Consumers are fluid, they're operating across owned and paid channels. You want to be able to demonstrate that natively in one place, and the big key here is we can also measure across the social black boxes. This has been a thorn in the marketer side forever. So being able to combine social, owned and paid all into one view and give them the ability to see what's working and how to increment is very, very important. CPG. We've recently expanded our CPG catalog. We have coverage from 100% of major retailers. We're seeing over 800,000 products in the CPG catalog. And really, you can also tap into intelligent summaries now, you can see summarized views of what the intelligence is saying. And you also have the ability to, again, converse with the data. If you're a marketer and you have a question, you can drop into our assistant here and actually take note and ask a question of the data that you're seeing. So you have a consultant that's ready to work with you at any point of the day, 7-days a week. Answers that shape social influence. Tell me who you hang out with, and I'll tell you who you will become. This is the famous line. The way to target you is not just you, it's your circle. It's your colleagues, your friends, your family. Circles of influence actually answers around who you actually spend time with that create influence in your life. We've made this available to marketers directly in the platform as well. It's an entirely new way to think about targeting strategy. Answers around generative engine optimization. We've gotten so many questions this year about the future of search. What's happening? About 60% of search traffic never actually clicked out before LLMs, 60% of search traffic doesn't click out after LLMs. So that hasn't really changed, but the dynamic of people that do click out demonstrate much higher intent purchase. How can we help our brands have the best visibility within LLM context and then decide how to improve their visibility using Zeta Data. Zeta Data can inform the questions and the questions inform the GEO strategy that helps brands actually show up more and be more discoverable directly in LLM context. Answers to provide foresight. Last year, we released leading indicators. This is for a Fortune 100 tech company. Leading indicators essentially is like a time machine. It detects nuanced signals over time that increase in propensity leading to a conversion. So it's like a dynamic audience that gets built by the AI. This brand experienced a 97% increase in audience size 4.3x increase in CBR conversion rate and 4.2x increase in lower CPAs for their campaign. Now this year, we're actually expanding the time machine, and we're introducing Journey Pathing. Wouldn't it be great to know what parts of your marketing are actually driving incrementality, is an exposed population on a specific channel actually helping your marketing performance. Marketers can now showcase this through Journey Pathing directly in the platform and see exactly what's causing people to come to stores, what's causing people to buy online and what tactics are working the best, again, driven by Zeta AI. Answers that accelerate vertical dominance. In this new world, AI is the new UI. We are actually creating an entirely new interface around opportunity explorer, which many of you have seen in the demo, if you've attended one of our investor demos, and it really consolidates down the information and makes it more bespoke for brands across acquire, grow and retain. Easier to interact with, easier to pull insights out of and leverages AI directly that's built in the platform. Again, it consolidates the view across customers, prospects, competitors and the market now in a much easier interface. Steve alluded to our collaboration with Snowflake. We are expanding the capabilities of the Zeta Media Engine. This allows our retailers to not just collaborate with us through our platform, but also collaborate with their partners that may not be Zeta customers. They can actually use the ZME to combine the data in a privacy safe way and they can use that combined data to drive analytics. They can use that combined data to drive activation, to drive measurement, and we are powering this for retail categories. You can't be Zeta Global without being global. So we are very excited to launch the GEO Explorer. This gives a view of the first global ecosystems that we are building our capabilities for, and we have a lot of data across the world. We're starting to synthesize it into strategy. The U.K. is one of the first markets we're going to go after than Western Europe and then Latin America thereafter, and you're going to be able to see what Zeta's assets are in those markets and as we recreate the model that has worked so well in the U.S. in other markets. Now Answers at the beginning of this marketing revolution that I spoke of. And an example of that is audiences. For the longest time, when you select an audience in a DSP or in a system like LiveRamp, you just basically have to choose the audience segment and you market to it. Wouldn't it be great to know which members of that audience have a positive sentiment versus a negative sentiment. Now with Zeta's capabilities, you can highlight and isolate people for specific kinds of use cases around sentiment. Who likes your brand, who might churn. It's the next generation revolution of the audience capability that exists in the platform. And it's one example how answers are actually pushing this marketing revolution much further. But I'm going to close on one more point. With this revolution, the goal is not just to provide tools that shape Answers. The goal is to move this into a platform that delivers wisdom. So moving from this concept of answers underpinned by Zeta SuperGraph; Two, the concept of wisdom underpinned by the Zeta marketing platform and underpinned by a topic that's very near and dear to my heart and Chris's heart, which is Athena. So I'm so excited to welcome Chris Monberg, my partner for a long time to the stage, who's going to give us a preview of Athena and tell us more about the road map for Zeta Marketing Platform. Thanks, Chris.

Neej is a smooth operator. And my goodness, this screen is beautiful. Nate, you got to get a picture, so I can show my kids. So I'm going to walk you through a little bit of where we've been today. The effort that we put into our AI foundation wasn't an accident. I've been writing about it and working on it for a long time. After that, we'll talk about where we are today with impossible products, and as Steve mentioned these earlier, the way marketers work with our platform is fundamentally different. It's something we couldn't have imagined 10 years ago. It's something that's very real today. And last, we'll talk about where we are going. I'm going to introduce to something that we call Gen UI which I think is probably the most exciting thing to happen to software since it moved to the cloud. So every line of code we write, every idea, every integration. It's not just a tool we're building. They are new standards and we really drive ourselves to it and hold ourselves to it. In fact, 8 years ago, when I joined Zeta, we wrote out our ethos, how we want to build software and where we think it's going. And it has underpinned every single feature we have built during that time. Let's talk about how we built this foundation. So Neej said, wisdom is the destination of every revolution. Revolution start with frustration. They start with limitations. They start with being held back. And enterprise software has been a big part of that. It just -- it makes us conform to it. And you guys all use software in your day-to-day lives and you kind of have to learn the software and wish it worked differently. And that's a great paradox is that marketing clouds are supposed to fix that. They're supposed to make it easier to do things, but they're too slow. Too dumb. I don't know if I can say that, but marketing clouds are kind of dumb. And they don't help you to your job any better. Zeta uniquely has built this wisdom up, and I want to take you through this path of how we built this wisdom. This wisdom it wasn't born out of obedience. We weren't trying to be like everybody else. It was built and broken and built again in the forge of what Zeta is and what I've been doing in my career since 2013. So as we say, we don't need another tool. We need standards for answers in action. And Neej and I have been at Zeta since 2017. If you fast forward to 2019, we shared, it was the end of 2019. We shared a long-term vision. I'm going to play this for you because I think it will come full circle in a second. This is an exert from our town hall where I fumbled with a demo, I built probably over a couple of bottles of wine over the course of a few weeks. And -- this is just a... [Presentation]

So you can see me talking to my phone there. We knew something. We knew that marketing was going to be conversational. We knew that Answers, Intelligence and Answers and action was going to come together, had to. We also knew it required a different foundation. Fast forward to a big day for us and for many of you, we IPO-ed in 2021. And we had so much conviction that we hung our literal banner of data plus AI equals intent. This was still a little bit early. It was 18 months later that ChatGPT came out. And all of our competitors, many of my friends in Silicon Valley, they're standing around and saying, "Oh, crap, what do we do?" We've building the old way. Now we have to conform to something new, and we don't know how to do it. Not Zeta. Our wisdom had brought us to where we were, we had anticipated this and fortune favors the prepared. So in 2025, we're focused on AI impact, and you've heard a lot about this today. Steve talked about the replacement cycle. We need to onboard our customers faster. This is a big deal. People are worried about migrating off these behemoths of old marketing technology. We'll show you examples of that. Transformative operations through AI is what everybody is talking about, how that's culturally apparent is a hard thing to figure out. You actually have to get deep into what Matt was talking about, so that you can get margin expansion, which is a key goal of every CFO that you guys talked to. Next, you'll hear me and others talk about developer experience. And that's a term that people talk about when they're talking about AI, changing the way engineers work. I'm very proud of the work that [indiscernible] and Patrick and others have done on the team. We've become a bit of the model ground in Silicon Valley. If you want to learn how to use AI to change the way you work, you come talk to us. If you're a vendor that's creating AI tools to help engineers work faster, you partner with us. And last and most importantly, we talk about customer outcomes through AI-powered marketing. These aligned to -- we call them our GTM objectives, but they're not really go to market. These are align of things that happen at Zeta. We've got a align, amplify, ascent and Neej talked about Athena. Athena is a super intelligent agent. It's an expansion of our Zoe vision, the one that you saw me share from the end of 2019, beginning of 2020. It's going to broader purview on what you can do in marketing. It's personalized and it helps with personal and team productivity. So I want to dive in a little bit into what Athena's foundation is. Neej spoke about the SuperGraph. And in every revolution, there are visionaries, but there's also architects. And we've been building the SuperGraph and breaking it down and building again in the forge of Zeta for many, many years. It's not simple. We've got the experts. What we have today is truly special. It brings answers, identity and data together. Next, I want to talk about AI infrastructure. Now this is the deterministic foundation, which complements the highly probabilistic world of AI perfectly. People ask questions. Infact I've had the question from a few of you on calls before, like, "Oh, couldn't somebody just go build this with AI and some vibe-coding"? And the answer is no, because this deterministic foundation, again, was built in our forge. It takes a lot of understanding of how to build technology that comes back to an individual and route that through LLM, MCPs so that the application can work. And third, contextual intelligence. This is the crown jewel in a lot of ways. This is what creates memory. This is what creates personalization, this is what make sure that we don't have generic agents. Instead, we've got an extension of the humans that are using it. So foundations don't create a revolution. But what you do with a foundation, what you build on top of that foundation can. And I'm very excited, although I'm an engineer, so I never look excited. Very excited to share something with you right now. This will be the first glimpse of Athena that anybody has seen. Tomorrow morning, David Steinberg will unveil it, and the world will know about Athena. We'll have Roman demoing it live if you want to see it. I have got a recording from Roman, it's a little bit quiet because it's baby who sleeps, he's got a brand-new baby. But it takes about 3 minutes. I hope that you enjoy it as much as I do. For me as a technologist anticipating this being in the forge and building towards the future, I believe that we're finally there. [Presentation]

I was hoping for a clap or something, right? Thank you. And obviously, thanks to -- I've got quite a few more slides. And thanks to the team that worked on this, this adaptive fabric that we've built, the core of our foundation is what makes this possible. And it really is magic for the marketers that see it. We've had a couple of beta customers come in and look at it. Their eyes get big, and they start to understand how they can drive more cross-channel marketing in a more effective and intelligent way. This unlocks OneZeta in a way that we never had before. So next, I'm going to go through impossible products. These are the products inside of Athena powered by Athena and that foundation. I'll go through them pretty quickly. But the way I've set it up is we went through the data life of the marketer, maybe it's a week or a month in life of the marketer. It starts with data, it goes into planning, forecasting, creative and measurement. And we asked ourselves, how would they work if they weren't conforming to technology? How would they work if the system was more intelligent? And on the right side, you'll see how we're setting the new standard. We'll talk about moving from the legacy to the new way. So starting with the data foundation, fragmented to foundational. Every marketer you talk to, and you may not talk to that many on a given day, I do. Their data is fragmented. It doesn't all have to be consolidated in one place, but it needs to be accessible for these federated services. I want to walk you through the story or I want to talk you through a retail CTO that needed faster on-boarding. This is a real skip. And they wanted 50% faster on-boarding. We delivered far in excess of that. Some of our agents were 5x faster. Overall, we're closer to 80% faster than what he was expecting for a timeline. So this is the new data standard, and it starts with connected data. Every company does. We do that for them. We have agents that help do that. We've got connectors that do it. Then it goes to a workflow. This is a line and it has job cards, each job card has an assistant. This assistant takes a screenshot from Salesforce Marketing Cloud. Just a screenshot. It quickly analyzes it. It converts it to Zeta and our taxonomy of thousands and thousands of audiences and attributes, and then it builds it for them. What's important here is that it puts the human in the center. We start with humans, we have AI, automate and then we end with a human, and it enriches with data cloud. Next, I want to move from data to planning. We work with a lot of planners and strategists that want to look bright. Sometimes they want to have a excel sheets, sometimes they want to move directly to activation. In the old days, they had a hypothesis. It was built with a lot of good intention, but what they needed were data-driven answers. We work at a travel brand. They've got a strategist, and that strategist is majorly overwhelmed. They have to do a lot of media plans on any given week or any given day. Their goal was, they just needed to work faster across our portfolio of products and they couldn't keep doing it in excel anymore. So this is introducing. We're a little bit behind on this. Here we go. The new decision standard. AI Studio has the ability to build your own model, your own workflows, your own agents. Here is a media workflow that very quickly takes some instructions to put together a budget and a plan, and you'll see this in the demo tomorrow, it creates the steps for you along the way. It has context of what your goal is, has context of the brand. And for each piece of their journey, this workflow that's automated, they're able to generate a media plan. This is something that would typically take weeks for a strategist to do. If they're trying to cheat it, maybe they've got a template they use, and they do it in days. Now we can do it in moments. This is real ROI. Moving from planning to forecasting. Once you have a plan, you need confidence it's going to work. And that confidence was rooted in strategy, the big capital S word, a lot of people use, but it didn't have the data it needed. We've built simulator which I'll show you in a minute, that helps people understand what's going to happen before a dollar has been spent. We have an e-mail CMO that was working in one channel, and they said, "Well, I want to use other channels. I just don't know what's going to happen. We don't have any experience with it. We don't have any data. Zeta was able to help them do that driving channel adoption. This is the new proof standard. So starting with the goal, which are aligned to the business, you can go through and change your methodology, add new data inputs like linear TV, which data doesn't run. This is part of the forecasting model and you get the outcomes. Once you activate that, it can be pushed into the next step or you can look to create campaigns, export or generate a proposal deck again, creating transparency around AI is a big goal of ours. And so you have to have things like the auction funnel and the bidding effectiveness and even understand audience insights and overlaps, if you're going to build that trust with your customers. Next, moving from forecasting to creative. You need campaign managers. They're going to build these plans out once they have confidence. Every single company we work with is understaffed on their campaign team. Those poor people, oftentimes are 24 years old and -- they are working 16 hours a day, day after day after day, making changes to campaigns. We want to help them with efficiency there. So this is the new creative standard. We've talked a bit about the workflow tool. Very similar. I want to do a win-back campaign for Black Friday. It will go through and build the steps for you, but it will also go through and help you understand what the campaign should look like. Inside of our campaign builder, you can interact with it. It's hooked up to your digital asset manager, your CMS or even [ Sigma ], which we're hearing more and more about hot tip there, and it brings in brand certified content. This just saves time. It's got an e-mail today. And with a click of a button, you can extend that one creative to other channels. Again, all of this is in an editor and human in the loop is so important. This drives cross-channel adoption. And for Zeta, that drives revenue. The final step in this is measurement. And we talk about moving from static to adaptive. Measurement is not the destination. It should be a feedback loop, but the whole industry feels like it's the report card they get at the end of the semester. We have a retail CFO that was on the phone with the CMO, reached out and said, we need help hitting our numbers. What can you guys do now to boost revenue in quarter, and we had an answer for it. This is the optimization standard, and it's the way all measurement should work. This is Performance Adviser, it gives you recommendations that are aligned to your business goals. And this is AI working in the background constantly looking for new recommendations based off the tactics you have. It gives you methodology. It tells you why it's creating the recommendation, and it tells you what it should do in the future. You simply apply it and then you can see the impact of it as soon as it is live. These selected recommendations stack up which becomes a very hard problem to solve that humans can't do on their own. They need sophisticated eye to drive it. So tomorrow, for those of you that are able to make Zeta Live, we will be introducing more impossible products. And I am incredibly proud of the work the team has done. Please introduce yourselves. There will be a floor full of bright people from my team and Neej's team to be more than happy to take you through questions, answers, how people are using it. Yes. So introduce yourself. Last chapter is new horizons, Gen UI, as I said, and we like to think about this as software-on-demand. So for over 20 years, we've been conforming to technology. This next era really flips it on its head, and this is the paradox should an individual adapt to software or should software adapt to the individual. And it's not meant to be rhetorical. It's meant to actually reflect where most of us are sitting and working today, the way we write our notes, the way we reclaim knowledge from the notes that we create. So in the old days, make it akin to people had screw drivers and hammers. They had the tools in front of them and they conformed to work in that way. As we look forward, I think it's more like Tony Stark and his Iron Man lab, and you have AI building AI. You have AI building software. You have AI building products, and it becomes a real extension of you. And well, it's [ grandiose ] and a great picture. I don't think we're far from it. I'm going to take you through a very recent use case. This is a global travel and hospitality brand, although we started with hospitality with them. They gave us an RFP and it almost read. I can still remember the first paragraph. It almost read, we're a global hospitality brand. We want to be able to track our properties across the globe, and we want to be able to market to lagging properties. It sounds pretty simple. And they kind of have a white-labeled software that hotels use around the world. So great. We can solve that. In fact, [ Old ] Marketing Clouds can solve that, too. Here's the way it would typically go. You build reports manually, you'd monitor them manually, like with eyes on reports. You'd have to go select audiences that you think are in Geneva or wherever the hotel is and you develop creatives manually, you can figure channel tactics and build more reports and monitor those manually. That's the way software has been. But we have this adaptive fabric. You saw evidence of it in the video earlier. We got all this infrastructure and all this context of those goals, it knows how to link it up to technology. When you bring those together, you do get to the world of UI on demand. This is Generative UI. Let's look at an example of it driven by Athena. So this is the prompt, going and create an app and right out the RFP, you can copy and paste in there, maybe a little color about what you want, like a heat map to go over the map. On the right, you'll see it mapping capabilities to the platform. On the left, it's churning away. An AI Shield down to the bottom is scanning code. It's making sure it's ready for deployment, and you get an app that's built just for you. This is actually what they wanted. They wanted a heat map that shows how occupancy rates are going. They want to be able to scan these things. And then they want to create a campaign to market those people, select their strategies that were recommended by Athena, select their audiences that recommended by Athena and select their channels that were recommended by Athena. They want to run those campaigns, and they want to see performance go up into the right. They want to see their occupancy rates solved for. This is a new era in all enterprise software. And all us are going to experience this in the next 10 years. Zeta is a pioneer because of the work that we've done in our forge a building and breaking and building again. But one app is not a revolution. I think an ecosystem of apps, they're all connected, they're all share one brain that know what the other apps are doing this starts to get to that Tony Stark vision, where they can work together to build something much greater. So I want to introduce Agentic Workspaces. This is the new interface standard. And -- we have a bunch of apps we call them agentic apps that are already in the platform, but people can build their own like you just saw. Say you want a retention app that's really focused on your job, your retention marketer, people we work with all the time. Let's create a unit interface that meets just your needs. Let's talk to it via Athena. If you want a logistics app or a warehousing apps, just talk to Athena and build one. Maybe you also want to look at your data guard rails or do an audit of that data and that retention app, we'll then build it, bring it into a workspace, look at them side by side. Maybe you have other concerns as a business like, "Oh, we've got a calendar of other campaigns I don't know about, but people will put them in there. Look at them again side by side. This is like the Bloomberg terminal for marketing. Maybe we should call it the David Steinberg terminal for marketing. I'm sure he would like that. This creates intelligence across your entire business, both inside and outside of marketing in one view. So as I've talked about, One AI platform with a solid foundation creates infinite possibilities. In this line, when software adapts to people, imagination becomes a limit is something I deeply believe in, all powered by Athena. So in closing, a good friend, Neej said that AI revolution is here, and I agree with him. While every revolution does start with frustration, it starts with a paradox. It ends with pretty infinite possibility. Our hard earned wisdom, the time we put into this going back from me to 2013, it hasn't shifted much, it's been built in that forge. It brought us Athena, which is such an exciting moment for all of us. But tomorrow, with our customers, we will imagine the impossible. So next, you get a break. I appreciate everybody's time today. Thank you very much. I think it's a short break. There's coffee in the back and probably the music will go on or the lights will dim when it's time to come back. Thank you. [Break]

Excellent. Well, welcome back, everyone. Thanks for taking the time with us today, and thank you for your attention on everything that's been going on. It's a hard act to follow that Athena demo and really to spend some time talking about it. I think we're supposed to be having the intra pages up. Okay. Well, I'd like to introduce my panel, Marc Brodherson from McKinsey. Courtney from Publicis Sapient, Sudarshan from Bounteous. So the topic today is really on how marketing and advertising are converging. One of the things when we look out there, CMOs are really stuck saying, what is it I'm supposed to do with the advances in AI? And we have been talking to the CMOs and saying, what is it you really need? What do you really want? And it comes down to a couple of simple things. First and foremost, the CMO has to be able to produce profitable customers. That is what the CFO is looking for, that's what their boards are looking for, and that's what the CEO is looking for. With that, the CMO is having to look at a different way of managing their business. Historically, we've had divisions between advertising and marketing, which are really artifacts of how we bought media, how we've worked with agencies and how we are managing the touch point with our customers. But today, that ability, the need for that is changed and the ability to bring it all together into managing a series of touch points has really made a difference. When we're talking today, one of the things I just want to get out with the group is, what are you seeing from CMOs? What are you seeing as their needs? What are you seeing shifting? And Marc, what are your thoughts on that?

Well, first, thank you for having me. Second, I just smile because we've talked about this for years, right? I always say, start with the consumer. I talk to my kids. They have no idea what the difference is. I say I work in marketing and advertising. Isn't that the same thing, right? And if you look consumer back, of course, they don't understand. The brand is talking to them, right? And at sort of a self-imposed distinction. That's created a lot of problems, both for consumer experience and for companies themselves. But quickly, look, I think -- there's not a CMO I speak to who disagrees with this. They may not articulate it as simply as the convergence of marketing and advertising, but they're all feeling it. I think the smartest ones that we're talking to are viewing it as the solution of that convergence or the Holy Grail is a decision layer above it. And that's what can blur the difference, right? It's which customer am I speaking to? What am I trying to say to them and what's the economic impact that I think I'm going to have with what I'm saying to them? Right? And therefore, the channel I'm going through really doesn't matter.

Exactly. And I think one of those big things there is about managing across touch points. Courtney, Publicis Sapient, you have a great view across the industry. What are you seeing both from a Holdco perspective and a Sapient perspective?

Yes. I mean I can agree that we've been talking about this for years. I've worked on both the media side, the marketing side and the agency side. So I've seen all perspectives. And for a while, we've been talking to our clients about we need to bring together understanding how a consumer views your brand and not just here's media, here's marketing. Here's an e-mail -- here's maybe a website -- and what we're seeing is that CMOs more and more are talking about this. And they're thinking about how do we bring these things together because what's happened in the past is everything was stood up in silos, right? Like media companies, they stood up their own little team here, their own little technology, their own little data. And then our e-mail platform at the same. And then our website did the same. So now how do we bring these all together. We have different processes. We have different orgs. We have different ways of working, and we have different platforms. So CMOs are really looking to us at Publicis Sapient to say, all right, how do we reconfigure all of this that we put the customer at the center. And they're calling it all sorts of different things. Some CMOs are calling it E2E like end-to-end customer life cycle. Some CMOs are talking about it and like, "Oh, the full customer life cycle." And some of them here at Publicis Sapient, we call it [ Pesos ], which sounds terrible, but it means the same thing. So whatever you're hearing in the market, everyone has their own name for it. This convergence is very real.

Courtney, do you mind defining Pesos?

Yes. Yes. So sorry, it's paid, earned, social and owned. So it talks to the different silos of an organization where they do marketing or advertising, and made an acronym of it. So it's not like a Spanish Dish or something like that. Just in case you were wondering.

In marketing, we like to make up different acronyms.

We love acronyms.

Sudarshan, Bounteous has a very unique perspective as a digital transformation firm. What are your thoughts? And what are you seeing?

First of all, thank you, Ed, for inviting me to this panel, looking forward to this conversation. I absolutely echo Marc's and Courtney's comments on that. This convergence is very real. But I think we need to sort of frame it in the context of what's happening now with, with AI enabling multiple touch points across our clients' life cycle, whether you look at it from the perspective of -- from the perspective of third-party data or first-party data and the entire value chain of having our customer life cycle and journey mapping through that. The marketer today needs to operate like an orchestrator of a growth operating system, where it goes beyond just driving brand value for your clients, but actually impacting profitable customer journeys for the firm. To give you an example with -- for example, one of our clients, Wawa. I think what we're trying to do with them is to move them -- move their end customers from just coming to the store for a morning coffee to actually making it a ritual where they come in for dinner. And that means looking at it from multiple touch points. And it's not just about -- it's not just about where in the life cycle they are but about having unique insights using all the -- all the data that's available to drive that convergence between marketing, advertising and ensuring value for your clients in a way that is profitable for you. That's the difference, and that's happening now largely because of the availability of tools like AI, and that is something that is going to impact significantly how market does evolve over the next few years.

Sudarshan, you had a great point there, that evolution of marketing. We hear about the AI revolution. Do you think that this will actually increase the maturity of CMOs and being able to deliver profitable customers to their businesses?

I think it's it sort of has to happen. If it doesn't happen, if the CMOs who don't embrace it, are not going to be relevant anymore. In fact, when I talked to a lot of my clients, it's not just the CMO, it's about breaking silos in the organization across technology, across data, product, CFOs, all trying to drive towards the same profitable customers. And it's about moving from marketing viewed as just experience or brand or advertising to actually contributing to revenue growth per customer. In fact, if I look at three or four years from now, I think the ones that will matter are journeys where you can individually customize and say this customer is somebody that I want to focus on because I can drive profitable growth through this customer. It's personalization at scale and the tools that we have today enable us to do that and marketers who don't embrace that won't be relevant anymore.

I think that's a daring item, an important item. I think you're hitting at the heart of CMO tenure. One of the big things here behind that is the idea of creating, I think what you're saying almost a customer supply chain that the CMO needs to be in charge of a customer supply chain and they have to act as a general manager to produce that customer profit. Marc, Mckinsey has really delved into that with a couple of white papers and other things out of the last few years. Your thoughts on that?

Well, first of all, I was going to jump in when you said Peso, the McKinsey term has become the customer supply chain, which shows we're not marketers, and that's across a lot of industries. But I do think it's very resonant and it's evocative for a lot of CMOs to say, "Oh, okay, and I'll get into the work, but that I should actually start operating more like a P&L owner and thinking myself like that, which gets to -- you can't think about profitable and growth in the same sentence, if you don't have some form of even a synthetic P&L. But yes, I mean, as you know, we've done for the last three or four years, this research into what was first the CEO-CMO, dynamic and now the triangle, the CEO, the CFO, the CMO. And I would start with I said my kids don't understand the difference between marketing and advertising and say most CEOs and CFOs don't either. And like one of the first findings was just a pure communication gap. But you have a CEO who ultimately wants durable profitable growth. If you really boil it down and apologies of CFOs out there, the CFO is thinking unit economics, which is really hard for marketing and advertising to translate its language to, and so CMOs are struggling to communicate back to them and also get what they need, which is you need to be able to move your money around fluidly, be able to prove incrementality, and drive closed-loop measurement to show that it actually worked and there's ROI, right? So the couple of things I would say, the latest round, we did another 100 interviews or so I think it came down to three things for the CMO. The first was actually an org implication, which is what we call single custody of the customer. You look at C-suites for all publicly traded consumer companies. C-suites that have only one role that touches is responsible for the customer and the customer experience. On average, those companies are growing to 2.3x faster, I think, than companies that have sort of diffused responsibility at the C level. The second is what you said, Ed, right, is thinking like yourself, a CMO as a General Manager. One of the big shifts has been there is what AI is going to enable us to do, I think, is this -- I predict a bold prediction other than like maybe live sports and news. The CPM will be gone in five years, and you'll talk about LTV and CAC everywhere, and that allows to think that way. So those are really like the two big fundamental shifts that we see happening.

I think there's a common theme that I'm hearing here really is the CMO's role is going to change. What they have to deliver is going to be discussed differently. CFOs, yet, they'll look at the advertising, but they really want to see the numbers first. The advertising is nice. When you take a look at this, that's going to change the demand that CMOs have for tools and capabilities. Courtney, your thoughts on that?

Yes. No, absolutely. I think you want to think about it in a couple of ways. Marketing now, there's two words I like to describe it. It's becoming unified and it's becoming precise. And you need the tools and enablement to do so. If you're breaking down those silos, not only do you need to get your data in a common place but you also then need to be able to activate it, and I think Marc talked about a decision layer of some sort, commonly, and you need to be there in the moment when the consumer wants it. It doesn't matter what channel, right? It just doesn't. You just need to reach them. And then you need to measure. You need to prove that growth. And what we're seeing in today's market, and we did a lot of research on this at Publicis Sapient, is that there's a little bit of white space in that area, right? Like I said there were silos. We stood up a DSP over here. We stood up a CDP over here. We stood up a CRM over here. And there's very little organizations out there that can bridge that gap. Now I know we're at Zeta's Investor Day. So it sounds a little like -- but I do have proven research that Zeta is one of the few companies that operate in this space. And we've talked to customers, and it's well recognized in the industry that because of the capabilities of Zeta between identity and data, CRM, e-mail, DSP activation and then the measurement, you can actually look at that full marketing pesos view with the platform, which makes it super attractive as CMOs are looking to bring their teams together and work within this space.

So Courtney, on that topic, what you're saying is a real major shift instead of just a dashboard saying, how did I do you're going to have a view that says, how am I doing and what do I do in the marketplace? Does that mean the CMO is going to change your role in buying technology? Are they going to be the actual decision maker as opposed to influencer?

I think so. I've seen it in organizations. It's about 50-50 right now, I want to say, and I see that pendulum swinging a bit. And because -- the reason why I see that pendulum swinging is because they are now responsible for that P&L like we just talked about, they're responsible for that revenue previously the role of the CMO was like [indiscernible] position, drive as many people as you can into the funnel. We don't really know what's working, who knows? But we'll worry about that later. But now with the precision I talked about, we can understand what is causing that revenue, which marketing touch point is which gives the CMO way more influence and what tools they want to buy to activate that.

And Sudarshan, given that you serve across the corporation, what's your thoughts?

I think, Marc referred to as customer supply chain. Yes. We call it growth operating system, and that is the CMO's role today has evolved or should evolve. And like I go back and saying, if it doesn't, they won't exist to becoming an orchestrator of that system across the firm. Example, we -- one of our clients, what we're talking to them about is not just conversions, but how to triple the EBITDA in half the time. And this is with the CMO because that's really the conversation that they're driving, and I'm talking about a Fortune 100 firm, and all of this revolves around having your content experience, data analytics and underlying technology stack work together. The only way if that doesn't happen and if they can't orchestrate this across all of this and drive profitable growth, then they just won't be relevant anymore. So from my CMOs that we talk to today, it's all about having -- delivering that business impact and not just about more conversions or driving more towards the digital channel. Yes, that's one of the things that we'll have to do as part of the toolkit. But how do you do it, has fundamentally changed. And again, that's where firms like Zeta come in and firms like Bounteous come in, where you need that underlying platform to be able to generate those activation insights. But then you also need consultants who bring in the strategy, the experience, transformation and an understanding of all the digital technologies that drive this transformation. And that's where Bounteous and Zeta are exploring some opportunities today.

Marc, when you are out there in the marketplace and looking at this marketing operating system, the customer supply chain, what do you see the conversations coming from the CMO -- do they see themselves as generating demand for these tools? Are they turning to their CIOs? Or where do they play in the space?

It's a great question. I would say, again, it depends. 50-50, although I would say the momentum is shifting. We've had probably like 3 or 4 engagements in over the last year, 1.5 years, which are -- CMOs bringing us in specifically to be the objective voice who says, paying for me a proper McKinsey style and was Board level narrative of why this needs to change. What fundamental shifts I need. And by the way, that is budget and that's tools, and I think that is always at the heart. But a lot of it is word changes, data governance, all of the surrounding pieces that -- the tools are great, but they don't work unless the company is set up to actually take advantage of them and implement them, bringing in the merchandising group, bringing in, there's -- you can't do this, at the scale and the ambition we're talking about without some fundamental changes around technology. And I think that puts the CMO in a much better position actually than a CIO or CDO because they can talk in that holistic way about everything that needs to change and the total outcomes, whether that's measurement, profitability, that when you have just a CIO leading that, you talk a different terms. You are talking to CIO? And I think as we get our CEOs and CFOs more knowledgeable about what we're talking about here in terms of not just top line, but actual enterprise value creation, that holistic perspective is really starting to take more and more of a front seat.

Excellent. So behind all of this, what I'm really hearing here is the CMO has -- CMO must change your role. Some are already on that journey. Others are recognizing it. It sounds like they also want a marketing platform and marketing operating system built by and for marketers to really be able to manage the production of a profitable client, a profitable customer. Do you think that demand is going to be durable? Courtney?

Yes. I mean, I do. It's almost like asking me like, do I think the Internet is durable in 1998? Like I absolutely think it's going to be durable. The most incredible thing that's happening right now is we are witnessing and watching a change in the industry, and it's happening before our eyes, and it's not going back. It's not going back to the way it was. AI agents, they're going to continue to evolve. The role of the CMO is going to continue to evolve. It's becoming more and more important that the CMO not only has the seat at the table, but has a very large voice at the table. And I'm going to tell you why. The reason is as things become more agentic, people are going to crave more human connection. And the person that can give that both things to them is the CMO. It's not the CIO. It's not the CEO, it's the CMO. So I do think it's durable, and we're going to see the CMO taking a much larger seat at the table.

And so working off with that for a second, and I'll open this to the full group. What I'm hearing here is all revenue in this ecosystem, will be originating with the CMO flowing to their agency, their partners and everything else. So it really is a key role as we look at the financial dynamics here. Thoughts on that?

Just adding to what -- I mean, Courtney said -- this is relevant what you're saying. The reason it's durable is the economics. And it's not -- it's -- every time there's a shift, there's some going to the high [ territory ], some going to durable. The ones that go to durable territory are the ones that have positive economics. And AI is driving positive economics for the CMOs in driving profitable customers. And that's why it's durable.

I agree with that. I was going to say in my first year, McKinsey right, you do the sort of industry analysis, which is driven by customer shifts, technology shifts, regulatory shifts. I think you have all of those coming together right now, which as we really are at something that I think is going to be the new normal pretty quickly, right? Like we've talked about the CFO. I mean the financial implications of this and the benefits are already becoming clear. AI models are just getting cheaper and more productive, which means you're going to start to see even a larger percent of decisions being made, model based decision. It's a metric I would -- I think you guys are starting to track, I think, I would keep an eye out on the street for that versus rules-based decisions, outcomes-based pricing, like this is enabling a lot of things on the finance side. Obviously, you have the platforms and the privacy like the cookie thing is one thing. But just in general, we're moving more and more to Walled Gardens, other forms of privacy deprecation. And then lastly, I think we're talking today about how AI is transforming the current marketing system. Chris was up here talking about GEO. I mean there's also AI transforming the entire consumer journey itself and where they're going to encounter brands, how they're going to make purchases, et cetera, and that just opens up a whole new marketing challenge. How the hell do I get my brand into a black box that is internally more complicated than the Google search algorithm ever was? And I think companies that have that durable identity and the closed-loop measurement capability and the multichannel distribution all in one, are the only ones we're going to be able to help solve that.

Excellent. I couldn't ask for better close. I want to thank my panel for joining us today and thank you. I'm very excited today to have Adam Potashnick, the CEO of Brainlabs North America. And before I jump in and ask Adam, a little more about Brainlabs, I was going to ask a little more about Adam, I want to start broadly by saying that Brain Labs is an independent advertising agency. And independent agencies and large agencies are a very fast-growing segment of Zeta's. Now as a guy who's been in advertising for 26 years. This makes perfect sense to me. Zeta offers a state-of-the-art data powered enterprise platform for marketers and agencies are enterprises, they to acquire, retain and grow customers, for their chief customer, a CMO. Advertising is a subset of marketing and [ ad visions] are part of a CMO's organization. So it makes perfect sense. And that brings me to dive a little deeper here with Adam on this topic. So Adam, you're the CEO of Brainlabs, North America. But prior to Brianlabs, why don't you tell everyone what you were doing?

Well, thank you so much for having me, Jed. It's a pleasure to be here. For 20-plus years, I worked within WPP, one of the world's largest holding companies in the advertising ecosystem. Inside of WPP, I worked inside of the media arm called Group M within one of their Opcos, which was Mediacom. I was their Chief Operating Officer. Prior to that, their Chief Revenue Officer. Chief Growth Officer, and I ran many of their largest global clients for close to 20-plus years.

And you did that all before you are 17 as well. Now why don't you tell everyone a little bit of Brainlabs. Please.

Sure. So as Jed mentioned, Brainlabs is a global independent media agency, the independent or in the space of media agency has grown quite significantly over the last 10 to 15 years. Brainlabs was born out of the being a digital-first media agency. We are -- we take a very scientific method to how we manage media dollars and campaigns. We have our own technology that we've built with our 80 plus engineers and our proprietary technology helps us do campaigns, smarter, faster with more agility, and we're seeing tremendous growth, not only around the world but here in the U.S.

And so is that your superpower the combination of your science and technology with your service offering?

Look our superpower is certainly our ability to test and learn and then scale, campaigns that are working most effectively as quickly as possible, but our superpower is not building massive enterprise-level AI platforms or technology. That's where we look to partner with the likes of Zeta, to be able to bring that to our clients and be able to deliver exceptional performance and results.

Segue into Zeta. So we've been partners now for about a year. And before partnering with Zeta, where there are other technology, data fuel platforms and companies that you thought of diving in deeper with besides data?

When I first arrived at Brainlab's about 2.5 years ago, there were certainly conversations that have started, but nothing came to fruition in regard to let's start a partnership. A formal partnership with an outside technology partner prior to our formal partnership we now have with Zeta.

And how does Zeta, I mean you've mentioned that you're a technology-driven company, you're a science-driven company. How does Zeta complement this?

So Zeta is built on its identity graph, it's technology, data and AI-powered tools and applications within the Zeta platform. We do not have that. So without Zeta, we cannot serve some of our clients or pitch new clients without this partnership. The partnership with Zeta makes us just as competitive, if not more competitive with many of the holding companies as well as many of the independent agencies out there in the marketplace.

So diving more into that, do you utilize data more for a differentiation with the Indies? Or can you now compete with some of these huge holdcos who have invested hundreds of millions, if not billions inside some data graph or something they try to put together. Is it more an Indie difference maker or allows you to play bigger?

The answer is both. There is no one in the marketplace we cannot compete with even after they've spent billions of dollars in acquiring large-scale data companies, there is no one we cannot compete with because we have Zeta in our corner and Zeta as a partner, we can compete with anyone in the marketplace.

And who are some of your bigger clients?

So some of our bigger clients are Capital One is our largest client here in the U.S., which is one of, if not the most data-driven marketers on the planet. We also serve as Walmart in Canada. Bells, which is a large-scale retailer. We also service certain parts of the Microsoft business, AT&T, LEGO, Pepsi and many others.

Yes, that is quite a list. And as you got to know Zeta and began the partnership about -- as we talked about, about 1 year ago, Zeta helped you with a new business pitch. That was one of your first intros into the power of the platform. Who was that with? And can you talk a little bit about that?

Sure. So in the initial conversations with Zeta, I wanted a superpower. I wanted a data technology in my corner that can help us compete with both the holding companies as well as the other independents. And so working seamlessly with the Zeta team allowed us to do that. They provided us with complete access. There was nothing that was sacred, and we couldn't access because of our partnership, they gave us access to all applications and all data sets within their platform. It allowed for us to be fully transparent with all the brands that we were pitching to say we have a partnership with Zeta. And by having that partnership, we can bring you this audience intelligence as well as this activation of your media that could drive you better results, in each and every case of having those pitch meetings and conversations in which we were up against both large and small agencies we performed exceptionally well, and we went deeper and deeper into the Zeta platform and the CMOs and the marketers that we met with all were very pleased with what Zeta had to offer.

Got it. So that's a great example of the acquired part of how we help enterprises and an agency as an enterprise with how you plugged into Zeta. Integrated with Zeta's platform, so you could utilize the intelligence of our platform to help you play bigger and bring on new customers. Now from that, what about the retain and grow aspect of the drive of an enterprise? How are you utilizing Zeta right now to retain your existing customers and drive their business ahead?

So because at Brainlabs and like many other independent agencies, we are not going to invest our capital in the data sets that data has already built into their platform, and that they allow for us to access on a daily basis. We have our own logins, we log in, we provide to all of our clients, audience intelligence and deep insights that are required for us to be able to support them strategically, but also help identify new audiences to help them grow. With certain clients that we have such -- in the retail space, it's very important for us to understand location-based data. The location-based data that we found within the Zeta platform is second to none. It's allowing for us to drive new footfall, new customers, new store traffic to many of our clients that have physical retail brick-and-mortar locations, and we're seeing massive success with your place, data your GEO-based data inside of your platform?

Yes, for the companies that still have many, many brick-and-mortar locations, that can be a real struggle when they just have no idea who walks into that location whether they've made a purchase or not, if they're not a loyalty customer, if they're not logging into your website. So that's something that Zeta has been able to help your retail customers with understanding. Did they see advertising? Do they walk into a certain locations. Did they take action and that then can feed the CRM and feed that marketing funnel as with Adam's referring to. Now tell me now we've had the success with helping Brainlabs to win and be the best Brainlabs can be in pitches. And then we've had some success as well with driving the growth and the intelligence for our existing customers, what do you think is next for Zeta at Brainlabs. How do you see the partnership in the future?

Yes. So alongside Zeta, we have one of the deepest partnerships with Google as well as with Meta in the industry. Now well, Google and Meta bring to us and the partnership that we have, we find that data is the perfect complement to what we're already doing with both Google and Meta. So the differentiation that I find and that the team finds within the partnership with Zeta is just that it's such an open, flexible, easy to work with platform. And the way that we work with the Zeta team really is customized around our agency, around our clients and around our business. It's not a one-size-fits-all for everything that we have to service and to do for our clients. I mean, we've started with one very large retailer here in the U.S., which is Bells. They have both Bells and Bells, Florida. The store traffic and the ROI are doing exceptional and month-over-month, the revenue or the insertion orders that we're sending over the data continues to go. And this has been for over a year. Following that success in those case studies, we've also been able to add another client, which is United Parks. With United Parks, who owned SeaWorld and many other amusement destinations. We're driving inbound tourism from the U.K. to Orlando to drive visitation and to drive people to the parks to buy tickets. We're seeing massive success in the early stages of that campaign as well. We're in other client conversations, active conversations both new and organic to see how we can leverage the platform and maximize the ROI for our clients.

Excellent. Look, I think Adam really pointed out how he looks at his business just as any enterprise would. He's looking to acquire customers. He's looking to retain those and grow those customers. And the idea of Zeta sitting alongside Google and meta to make the whole agency smarter and work better in order to accomplish this is a big part and a big foundation to this partnership that is again, been about a year, and we look forward to the future. And this is just an example of how Zeta partners with independent agencies and in reality in holdcos alike. So I want to thank you very much, Adam, for joining us on stage. I hope that was helpful for all of you. Thank you.

Well, thank you, Jed, and Adam. A lot of great content covered so far today. Let's see if I can keep the ball rolling. I'm going to step you through a series of metrics that we believe prove the durability, predictability and profitability of our growth, starting with how durable our growth has been. I began the day discussing our track record as a public company of growing greater than 20% every year in which we've been public. The actual compound growth rate of our business over that period of time has been 28%. That's even after you adjust for the help of the biennial political candidate revenue contribution. And as you can see in recent years, the growth trajectory is pointing upwards. Underpinning that growth has been expansions in total scaled customer count and superscale customers. In fact, we've compounded growth since going public at 13% in total scaled customers and 22% in super scaled customers. But that only tells part of the story. That's because when we work with global enterprises and agencies like you just heard from Adam, we'll count those as one scaled customer. On the brand dimension, as depicted on the iceberg, that's a different growth vector. In fact, just since our Investor Day 2 years ago, we've grown total brand count by 45%, to upwards of 850 unique brands. And each one of these brands meet the definition of a skilled customer. So for context, 850-plus brands equates to 567 scaled customers, which, as you can see, has been growing 33% itself over the last 2 years. But not all of the growth has simply come from agencies. In fact, over that same 2-year period, enterprises on a compound growth rate basis, have added 18% more brands and agencies, 40% more brands. But keep in mind, just the consolidation of our 5 agency holdco partners, they support over 15,000 brands. So we're barely 1% penetrated into that opportunity. And the addition of brands by enterprises and agencies has a positive effect on ARPU growth, obviously. But you can also see here how durable ARPU itself has been, and we have three ways in which we can expand ARPU growth. First through channel expansion. We think of that as an up sell motion. Examples of channels on Zeta platform include email, mobile, social, display, video, Connected TV, audio, the list goes on. We can sell incremental use cases. Examples of Zeta's use cases include customer retention, customer growth and customer acquisition. We think of that as a cross-sell motion. And as you're going to increasingly hear from us, we can drive AI adoption, which drives more usage. And we'll go into each of these now in more detail. First, starting with channel expansion. In late 2021, we made a complete shift in our go-to-market model. We went to a hunter-farmer sales model. And when we did that, we then made it available to all sellers on the platform to sell all channels. Prior to that, we were siloed. And as you've seen in our product demos, Zeta knows which channels, individuals in our data cloud prefer and are most responsive to, which then allows our customers to build hyper personalized omnichannel journeys, which are sellers have become very adept at selling and their progress is hard to miss. The fastest-growing customer cohort are now those customers using four or more channels who constitute greater than 50% of revenue on our platform. And the more channels customers use the higher their net revenue retention rate. And we continue to add channels on the platform with room to expand. Here, you're seeing the total channel breakdown for all of our skilled customers. Email, continues to serve as that strong activate foundation. But yet there's very strong diversification across programmatic channels as well. The addition of Marigold will only add to high margin e-mail footprint. Adding incremental use cases is also a powerful tool for ARPU expansion. In fact, it is the biggest opportunity as you've heard from Steve Gerber, in our existing customer space. We call that our OneZeta sales motion. Back in 2024, when we initially created the OneZeta sales motion, we did so to a very narrow subset of customers. And it was only this year that we began to gradually widen that net. And you're starting to see a really exciting inflection point. But what I would argue is the most important element is how much runway is in front of us, greater than 80% -- of our total scaled customers today, all 567 still just use one of our customer retention, growth and acquisition use cases. But when we do see that jump from the first to the second, ARPU triples. It goes from an average of 1.5 million per scale customer to 4.5 million per scale customer. And then the third leg of the ARPU expansion tool is driving AI adoption, which creates incremental usage. The inflection point here was in 2024, late time, early '25. We actually took our internal learning and development teams that were focused on training our sellers. And we turned them into a customer facing organization. So we're rather than only relying on Zeta Live once a year to bring all of our existing customers and prospects together to learn about our products, train on our products, we began to take ourselves on the road. And what we're seeing is rapid adoption. Here are three of our top-tier users of our generative AI. We're not talking about Machine Learning or Natural Language Processing. Those capabilities have been embedded and induced by our customers since prior to going public in 2021. This is about how they're creating pulling intelligence out of the platform, building agents, linking multiple agents together to create automated workflows. And what we're observing when that happens is that it spins our flywheel faster. A time to a faster audience spins the flywheel. A higher ROI audience spins the flywheel. More agents linked together performing autonomous work, spins the flywheel, which drives ARPU higher exactly as you're seeing with these customers over the last several quarters. So we looked at durable growth trends in customer count and brand count, for channel expansion, for use case expansion, even adoption of AI dreading usage. But now let's transition to how predictable Zeta's growth has been. As an investor, you can underwrite predictability when there's a track record of execution. When we first went public, we immediately published our first long-term model, Zeta 2025. And on each one of those elements, we exceeded our goals. So now I want to look into what creates the ability for us to set these goals like Zeta 2028 in this case and then continually over-deliver. We believe at Zeta, balance and diversification are key ingredients to predictability as opposed to how concentration can create lumpiness. It's why we strive to keep a balance of our sales team between hunters and farmers. Hunters are focused on closing pilots, proof of concepts and RFPs. They're charged with driving new customer revenue, whereas our farmers are charged with driving existing customer growth through ARPU expansion, which comes on the back of great customer outcomes. And it's led to very organic balanced growth. Since 2021 through 2024, we've averaged 12 points of our growth from existing customers, 15 points of growth from new customer revenue and 2 from M&A. So now let's drill into each, focusing first on that existing customer growth vector. One of the big takeaways I hope you get from today is the longer Zeta's customers are with us, the bigger they become. Historically, we've shown you 3 cohorts. Those customers that have been on the platform less than a year, most oftentimes closed through pilots, 1 to 3 years and greater than 3 years. Here, we've added another cohort, customers that have been on the platform now for 5 or more years. And they follow the same pattern as their predecessors. Each year, they're spending more. But more importantly, they serve as the foundation of spend on the platform. Almost 60% of Zeta's revenue now comes from customers with us 5 or more years. So now combine that cohort with a cohort of 3 to 5 years, and you have greater than 3/4 of Zeta's revenue with a track record of generating high net revenue retention. In fact, that cohort generates greater than 115% net revenue retention over the last several years, and that's just an average. Last year was higher. So zooming out, 76% of Zeta's revenue, our longest tenured customers who keep spending more, who we can predictably rely on generating at least 115% net retention in the beginning of each year. Our new customer sales engine is not just highly predictable, it's very productive. What we're seeing from our hunter sales team is each year on average of expanding their sales by at least $300,000, to at the end of last year, an average of $1.4 million per hunter. Now keep in mind, most of the deals these individuals are closing are between $50,000 and $150,000, pilots and proof of concepts. So the average number of deals closed per year is more than 1 per month. Now to put this even in more perspective, for 2023 and 2024, as you're seeing here, new customer revenue contribution was 16 points of our growth. We've also talked about our improving revenue visibility. Obviously, the planned acquisition of Marigold's Enterprise Software Business is only going to help. And we're looking at the organic part of Zeta. And I'm removing the seasonal nature of political candidate revenue and advocacy revenue, which is more consumption-based. As you can see, not only is the trend working its way up, but the amount that our recurring revenue base grew in 2024 was 35% year-over-year. I think there's a perception that most of Zeta's growth has come on the shoulders of our consumption part of the business. Now against that same benchmark, consumption has grown at a healthy 23% rate. But you can see, the recurring part of our business has been a very strong contributor. So we discussed predictability from a few different vantage points. The contribution from our existing customer base has been strong. It's predictable, and we wake up with a net revenue retention rate for about 3/4 of our business of 115% each year. A very productive and predictable new customer contribution and more and more visibility, not just because of a growing recurring revenue base, but the addition of Marigold to come. So now let's focus on profitability. Every year since we've been public, we've expanded adjusted EBITDA margins and free cash flow margins year-over-year. In fact, we've grown free cash flow dollars the fastest relative to revenue and adjusted EBITDA. So now let's look at the building blocks that has enabled us to do that. From a cost of revenue perspective, our biggest lever is positive mix shift, and we're excited to see what's unfolding with the agency customers in particular. Since we really started to rapidly scale with them at the beginning of 2024, late 2023, not only have we added a substantial amount of revenue from expanding brand relationships there, but you can see that's been on the shoulders of those agencies wanting to use Zeta's direct channels. Direct channel mix for our agency holdco customers has gone from 45% to now north of 60%. Not only do we see positive mix shift continuing, but the addition of Marigold's Enterprise Software Business, which is high-margin e-mail, should only be a further tailwind. In fact, if you look historically at their cost of revenue profile, it's been sub-30%, whereas Zeta for the last couple of years has hovered between 38% and 40%. Now shifting gears from COGS to operating expenses. We've maintained discipline. You heard this throughout Matt's presentation and even Neej and Chris' in terms of the addition of headcount relative to the addition of revenue. From 2022 to 2024, we've added 15% more heads. By the way, the vast majority of those came in this form of our centers in India, which grew 17%. But against those benchmarks, revenue grew 30%. And what you heard from Matt is we're not just focused on bending that curve, but breaking that curve so that we can grow without needing to add people. We're also focused on the sales and marketing front on building a high-performance culture and high productivity culture. We're not afraid to continually adapt and evolve our go-to-market. You heard me talk about our shift to a hunter-farmer model several years ago. A year after that, in 2022, we fully verticalized our sales team, creating specialty sellers. We changed our hiring habits. We started to hire much more experienced, longer tenured sales reps. We even changed our internal management systems, going to a process now where every single day, we understand what are the habits and what are the activities of our sellers so that we can win faster and fail faster. And clearly, it's having a positive outcome. Pipeline per seller, the value of the total value of their pipeline is up over 50% year-over-year. The total contract value of the deals they're winning is up over 50% year-to-year. And their average deal sizes are up 50% year-to-year. So what is the really big point? The levers that we have visibility to right now in COGS and in operating expense, we now believe we can get to a structural adjusted EBITDA margin of at least 30% by 2030. And we see ourselves arriving there through between 1 point and 5 points of positive mix shift affecting cost of revenue, getting another 3 to 5 points of productivity from our sales and marketing part of our portfolio. Now by the way, in the last 2 years, we've averaged around 340 basis points. And then in G&A, where we do the most amount of scrutiny of where we need to add or where we can subtract, we're targeting 4 to 6 points or getting effectively, our G&A structure between 8% and 10% of revenue. And more and more of our adjusted EBITDA will drop to free cash flow. As compared to our Zeta 2028 model of at least 65% conversion, we now see a clear pathway to at least 70% conversion. We've created a whole new growth, or I should say, shrinking trajectory in CapEx and intangibles that should stick. The eventuality of working through our working capital headwinds that as we've seen this rapid growth with agencies as part of their normal payment cycles creates a working capital deficit for us, we see that normalizing. An interesting data point, year-to-date 2025, our cash conversion has averaged 58% from adjusted EBITDA. If we just had a neutral working capital position, that conversion would be 80%. So we're even being conservative in this session. We're still assuming a headwind. So as we bring all of this together, throughout the day, you've heard about the durability of our data, of our competitiveness and what I've covered, our growth rates. You've heard about the predictability of the types of outcomes that we can drive for our customers as well as Zeta's revenues and our margin expansion. And you've heard about our focus on profitable growth. So if you carry forward our revenue growth model of at least 20% organic revenue growth every year through 2030, you carry forward the adjusted EBITDA margin goal of at least 30%, you've got a Rule of 50 business there. But if you extrapolate the 70% free cash flow conversion rate, that's north of Rule of 40, as my friend, DJ would always remind me on a free cash flow margin basis. So with that, let me wrap, hand the stage over to David to bring all of what you've heard together, and I look forward to connecting with you during the Q&A session after that. David?

I've been told you have to push the button very hard. So I started yesterday. Well, maybe I went too far. Okay. So we got here -- I got here Sunday evening, Monday morning, I did Bloomberg at 7:00 a.m., which was early L.A. time. Then we ended up closing the New York Stock Exchange, Monday, rang the bell. Tuesday, we did our global town hall yesterday. I have not seen that much excitement in our business since its founding. Then I had to fly to Dallas to give a speech yesterday, have dinner, got back at 1 in the morning. And then at 8:00 a.m., I was at the breakfast for our Customer Advisory Board. So simultaneously to this meeting, we have our CAB meeting, which I was just so blown away. We have some of the biggest brands in the world are in the room helping to make our business better. We have 138 current projects that have come out of our Customer Advisory Board meetings that we're already building products for consumers. I will say Chris is very difficult to follow when he's talking about Rule of 50, Rule of 50, Rule of 50, but I've been relegated today to brand and M&A and long-term strategy. So what Chris tells me to do, I deliver on. What I would say is the move from Zeta who to why Zeta has happened. When we walk into a room, I no longer have to spend the first 50 minutes of the hour explaining who we are. I now get to spend the full hour explaining why they should be choosing us over our competitors. The next evolution, which we're really hoping to get to, I believe, over the next year, I don't think this is a 5- or 10-year journey, is Zeta now. Our pipeline going into Zeta Live is already at a record high. And last year, Zeta Live was the single biggest pipeline creator and business creator in the history of our company. My goal is to dwarf that this year. And as we grow into next year, the question is, how do we get people saying, I must have Zeta now. Now must-have Zeta is a little more aspirational. That's more like a must have Microsoft or must have other brands of its type, but it is what we aspire to. If you look at Zeta Live this year, it is really changing the game for us as a business if you look at our website use, you look at our demo requests, you look at how we're rated. We put out on news, I think, 2 days ago, we were rated #1 in AI integration from a marketing perspective by 3 separate rating sources all at one time, including Forrester. 240% attendance this year. To be totally transparent, just to be clear, we've got fire marshal approval for 1,200 people. We have over 2,000 non-Zeta employees registered. I don't know how the hell we didn't shut it down earlier. But we then have the seventh floor, which you guys will have access to at some point, where we're going to be able to park people. So now what we're doing is we're going to livestream it to our offices in New York City, and we'll rotate employees in and out and try to make that work. Our RFP volume is through the roof, and the positive sentiment of our company is at an all-time high. When you think about the evolution of our business, we always think about M&A, right? We've been in business for 17 years. As I always like to joke, we've bought 17 companies in 17 years. It's highly probable there will be an 18. Our strategy, though, continues to be incredibly disciplined and very, very focused. We will continue to look at the 5 main criteria and then look at how Marigold fits into that. So one, can we fully integrate Marigold into our platform in the first year? The answer is absolutely yes. I actually believe we can do most of it within 6 months. Two, will it be accretive from day 1? We have already told you we've paid approximately 10x forward EBITDA to purchase it, well under 2x revenue. That is the definition of our current valuation of accretive. Process clear synergies. We believe that we can cross-sell the heck out of this group. You've got over 100 global enterprises, including more than 40 Fortune 500 companies and 20 of the 100 largest advertisers in North America, all on one use case. How do we get Ed See in there, as you saw Ed speak, and make these One Zeta customers. Just a little side note, most of the One Zeta customers we've created thus far started on the use case of retain. We find it's easier to go from retain to activate and monetize at least at this stage of One Zeta than it is to go from activate the other way. We're going to crack the code on all of it. But the thing I like about Marigold is 100% of their customers today are on retain, which also is nice because it's almost all subscription revenue at very low cost of goods sold. So that will help us with our long-term visibility into our business and give us even greater views into that. Although we get a lot about visibility into the business, I don't know at what point we will start to get credit for understanding our business. We have been public for 16 quarters. We have beat our guidance 16 quarters and raised our guidance 16 quarters in a row. Maybe we'll have to get to 20 or 30 before people say, oh, these guys actually know what they're talking about, but we'll get there eventually. We think we can grow this business at or above our organic growth rate. That's really important. The business itself is right out of our playbook, where we're going to take sell-through, we're going to combine it with LiveIntent and discuss into building the premier publishing cloud in the world. Let's be clear, in a post-OpenAI, post-Gemini world, publishers need traffic and they need monetization help. And our Publisher Cloud is going to deliver both. We pick up Selligent in Europe and EMEA, where for the first time, we will have a meaningful presence there. Our data cloud already exists there as native to the European environment, and we'll be able to merge the data cloud in with Selligent very, very rapidly. And then, of course, you've got Cheetah Digital, which is one of the premier marketing automation platforms out there. Merging that into the Zeta Marketing Platform is going to allow it to scale very, very quickly. For the fourth quarter, we're going to do nothing to just satisfy the customers. We got to make sure everybody comes out of this very, very happy. And then access to world-class people, we're picking up some of the world's best talent in sales, engineering and management, and we're very, very excited about that. To remind you, about a year ago, we told you we would do all of this with LiveIntent, and we have. So from a credibility perspective, I think we integrated all of LiveIntent within 90 days. I'm not sure we'll be able to do that quite for this. But I think we'll have everything done, integrated within 6 months, although Gerber might kill me for that. This is the future of our company. I will tell you that this, to me, is the single biggest thing we've ever done. I got the full demonstration about a month ago, and I literally got chills at how good it was. I will tell you that when I saw this product, I -- and not to belittle Zeta -- I thought this would be a Meta product. This would be a Google product. But we are the ones who cracked the code. This is truly conversational artificial intelligence in a platform that can then control the full ZMP on an integrated basis today. Tomorrow, this can be our clients' full ERP and operating system. We believe this can integrate into anything that they're doing, not just from a marketing and a business intelligence perspective, but from a product development perspective for them, from how do they make their businesses better and how does this truly become the operating system of our clients' lives and businesses. Now to be clear, that is not today. But tomorrow, we're going to be doing a full rollout. I have been bullied into doing this at the open of the conference. So I'm going to do a live demo of it, which I've never done before. So I'll try to channel my best Steve Jobs tomorrow when we open, but I'm going to open, and I'm going to begin a very deep conversation with Athena, who's going to tell me some really interesting stuff. And then at 11:00 tomorrow, Chris, Neej and [ Nate ] are going to do a deep dive. It is unbelievable. I really encourage you all to see that. When you think about it, why are we uniquely positioned to do this? Because if you take our data, it cannot be replicated. So the data informs Athena in ways that no other algorithm can be informed. I will go out on a limb here. Those of you who know me know I enjoy doing that. And I will tell you within 5 to 7 years, I believe most artificial intelligence will be ubiquitous. I like to remind people that then think I'm crazy that 100 years ago, there were 3,000 companies in America that sold cars. And no, I was not old enough to have been there. But today, there are 4 or 5 companies in this country that sell cars. We're going to have a very similar situation, I think, in large language models and algorithms. The difference is going to be the proprietary data you feed into it. So when our clients access Athena, they're accessing the consumer data platform that houses their first-party data, merge with our first-party data, merge with the vast majority of data from the open web. Zero data exhaust, all of the intelligence will live inside of the platform, and Athena will effectively, day 1, become your data scientist and your ability to activate seamlessly in a fully conversational way. It's really exciting to me, and I'm excited for everybody to see it tomorrow. We are pacing well ahead of our 2028 goal. You can certainly do the math on it. And from a mathematical perspective, I won't pretend to give anybody in this room math advice. My assumption is you all can do it better than me. But the faster we grow earlier in the plan, the more you would have to decelerate to only get to the $2.2 billion in 2028. So as Chris already started talking about, we're thinking about 2030. We're thinking about how do we get to a 30% operating margin, not just a 25% operating margin. We're thinking about how do we take our free cash flow conversion rate from where it is to greater than 70%. These are all things that we're very focused on as it relates to operating the business and something we're very, very proud of. So the replacement cycle is accelerating. We are seeing more RFPs than we have ever seen, ever. A lot of that is going from Zeta who to why Zeta. Hopefully, we'll get to Zeta now. But a lot of it is also just you're looking at the technology that's out there. Think about this. Salesforce bought ExactTarget 10, 12 years ago. At the time, it was their primary secondary hustle. Then they bought Slack. And now all of a sudden, ExactTarget is the side hustle to the side hustle. You're not seeing investment dollars into infrastructure flow into the large marketing clouds, and that's Salesforce, that's Adobe, that's Oracle. When you look at our business, everything we do is purpose-built to be the world's greatest marketing platform. So we're really seeing in this replacement cycle, a lot of the enterprises that have been on those competitors for 5, 7, 10 years are like, they're moving, and we're seeing that happen faster. We are the leading AI-powered marketing cloud. And when you plug Marigold -- say that 3 times fast -- Marigold Enterprise in, it's going to accelerate it. We really feel that the ability to take their customers, make them One Zeta, migrate them onto our platform and grow them on all use cases is going to be a meaningful driver to growth. Our innovation is better, creating better outcomes and sharper differentiation. To be clear, the other thing we really get out of Marigold, which we've talked about a lot on the last call, I'm talking about a little less today, but is the loyalty program. When you think about the loyalty program, I was -- as I said, just at the CAB meeting, 3 CMOs of 3 Fortune 500 customers literally came up to me and said, we love the loyalty idea because we do it internally, and we're just not doing it well. To me, that's great, but the more valuable thing is training the algorithms. Today, for every dollar a client spends on the Zeta Marketing Platform, we return between $5 and $7 in revenue. I have not been shy about my aspiration to get that to $10. We're already 100% better than our competitors. I want to be 300% better than our competitors. I think the loyalty data, the ability to get SKU-level data into the models will make us that much better. Our growth is durable, it's profitable. And guys, for the love of God, it is predictable. 16 quarters in a row of beating guidance and raising guidance. At some point, you have to give us credibility for being predictable, although Marigold certainly will help, hopefully, with that, as we meaningfully increase our percentage of subscription versus utilization, and we are pacing well ahead of our 2028 targets. With that, I believe we're moving to a Q&A session, Chris? Excellent. I have to leave.

All right. Well, first, thank you. I know this is a huge, huge time commitment of yours, and it's our privilege to be able to do this with you. So we've left 30 minutes. There's a countdown clock back there. If I'll kind of give us 10 minutes and 5 minutes, just you can get a sense of getting questions in. Matt Pfau is going to be running around with a microphone. So let's go ahead and get started or Matt's got to choose favorites.

Great. I guess I didn't know I was getting the first question. Scott Berg, Needham. Thanks for the time today. And of course, tomorrow, this is a great event. Lots of questions to choose from. Steve, I wanted to pick up one of your slides on there. You talked about a 4x ARPU kind of growth opportunity. Your customers, after they stay with you for 3, 4, 5 years, are already spending 2, 3x what they initially spend with you. How does the AI functionality that you're talking about today, whether it's with Athena or other applications kind of bend that opportunity? Does 4 go to 5? Does it go to 6? How do we start thinking about that? Because my guess is that 4x opportunity does not properly embed what you're starting to see from the new innovation you're bringing to the market.

So it's a great question, and it was obviously a big part of what we were talking about of the predictable growth trajectory. And so there is some AI that's already baked into that, that again goes back to the notion that provable results unlock scale. But there's 2 dimensions really to your question. So one is time and the other is value. So I believe that as we establish the interface standard, that's going to compress time. Once we also have the interface standard combined with the decision standard, that's what expands the addressable market for us. We also, on top of that, have One Zeta moving from motion to model. And Ed, who is right behind me, is turning that into more of a repeatable playbook. And we're already seeing greater than 4x movement for certainly the opportunities that I showed in the case studies. Ed, anything to add?

I think as you think about that and moving into the model perspective, it is going to become an accelerant and bend that curve even more. So the discussion with customers will make a significant difference to them on what they're going to be able to do and how much of their budget will be able to impact. Next question.

Thank you, Arjun Bhatia with William Blair. I appreciate all the insights today. I think it was very encouraging to hear some of the pipeline trends. I think even you mentioned 15 points of growth on average coming from new customers, all great data points. I think one of the things that I remember is a critical point in your kind of customer journey is when customers are in pilot and can you get them successful to come out of that pilot phase because then you can get into the 3-, 4-, 5-year tenure phase, where they exponentially kind of increase their spend. I'm curious if AI or some of the new product developments that you've talked about today will help change that success rate of those pilots and if there's any data that you track that you can share with us that maybe talks to the success of customers moving out of the pilot phase into production.

Neej and Jed, maybe you want to take that, and then anybody else can jump in.

Sure. So I think that the value of Zeta data is a well-known quantity now amongst our customers and prospects. So the operationalizing that data through AI is becoming easier and easier for us, as you've noticed in Chris' presentation and my presentation. So certainly, the performance, we expect to continue to improve. The moat around the data as a differentiating asset continues to build. And we're seeing that with the pilots that are coming from Jed's team and Pam's team as well. So it's kind of like a self-fulfilling thing at this point where the data is empowering the AI, which is actually creating more data for us along the way. Jed?

Yes. So we're seeing it in 2 ways. The easiest on-ramp is utilizing Zeta data for a customer. We're just utilizing Zeta data. And then we create the opportunity to bring in the clients' data and enrich that data, and then we become even stickier. So that's really how we're seeing that on-ramp to the opportunity is beginning with our data, less friction, easier, faster for the client to test the underlying intelligence of our platform and realize ROI, and then incomes their data, and we double down and supersize that.

Arjun, to be very specific, yes, I believe that the AI will help us increase the percentage of pilots we convert to full-time customers, and we are seeing that trend happening now. So with the pilot, one of the hardest parts is the onboarding, getting it started. By way of example, statistically, we can now onboard a client using our automated AI platform 5x faster than it used to take us to onboard a client. Those types of solution sets and speed to market impress the client, really help with the return on investment day 1, whereas it used to take a lot more discovery. As a pilot would run, the algorithms would get smarter over time. Today, because the algorithms are so much better, we're able to deliver superior return on investment to a pilot as a percentage of return on investment than we would have even a year or 2 ago, and we're seeing that help us convert more pilots to full-time customers.

Awesome. Matt, next question.

Awesome. Elizabeth Porter from Morgan Stanley. I wanted to ask again on Athena. Clearly, your enthusiasm for the product shows through. So first, just vision for how it gets monetized. Is this embedded in the platform and drives more usage? Or is it a broader replatforming that has some sort of amplification on the platform fee? And then the second part is, just as we make it a lot easier to get more of this technology into the hands of users, what does it mean in terms of broadening the addressable customer base? And second, the shift from agencies to in-house as you can just do more as an in-house, making this technology a lot easier.

I'll take the first part. And Chris, Steve will take the second part. So the answer is day 1, it's about getting it into everybody's hands, Elizabeth. How do we get all of our clients using Athena? And when you see the demo, you're going to see it's going to actually -- today, it's in beta with internal use. We'll have clients using it this quarter. I'm hoping it's production ready to go out to everybody by Q1. It's just going to be added to the platform. So it's going to drive meaningful increment in usage initially as they want to add modules to it. So as it moves from marketing to business intelligence, to more ERP functionality, we will charge for those modules. So day 1, remove friction, create additional productivity for the client because they'll be able to replace the vast majority of their internal data scientists. And the vast majority of the people that are hands on keyboard activating will all be replaceable by Athena. Down the road, I believe it will be a meaningful ability for us to sell those modules as they move into new business cases. Steve?

Part of ubiquity and ubiquity is core to all of the standards that we've talked about establishing. Core to that is the partner ecosystem. So we view, as you saw today, agencies and SIs as partners. We don't view them as competitors. One of the benefits of Athena is that it can move laterally as well. So not just at the enterprise where that becomes the center of gravity, but also into their partner ecosystem so that everyone is using the same standard. And that's how the different tools connect instead of compete. So we see it as an amplifier, not a replacement.

Next question?

Great to have the leadership team on stage. My question is on data. And specifically, you talked about Snowflake a couple of times. When you look at your large enterprise customers, talk to us about what they're doing with their data estates. What are the use cases that naturally belong within Zeta? What are the use cases that do not belong within Zeta and belong as part of a broader data strategy with Snowflake and Databricks? And where do the 2 converge?

Maybe Neej and Pam, do you want to take that from some of our retained customers' perspective?

Sure. Sure. So Snowflake is interesting because in the last 10 years and Databricks as well, enterprises have tried to really containerize their data in one place to make it economical. What's happened because of that is that now their CIOs and marketing teams are looking for ways to monetize. So enterprises are different in their configurations. Some people consider the golden record to live inside of Snowflake. Some enterprises consider the golden record to live outside of Snowflake. We can support both models, and we do. And when we layer on top of Snowflake, what we're doing is we're essentially adding the application layer to make that data valuable in production. So you can acquire, you can grow, you can retain. Snowflake as a container doesn't do anything for the enterprise natively, but it gives you an environment where now you can apply the AI, you can do something more interesting and you can achieve better ROI. One product that I called out today is the Zeta Media Engine. That is a co-developed effort with Snowflake, and it allows customers that are on Snowflake to collaborate with their partners, collaborate with Zeta in a tax-free manner and move data into an activation workflow in a cleanroom so you don't have to actually exchange any PII with us. So that is a very powerful product, and it's a very powerful and on-ramp into Zeta across media use cases, and we're seeing more and more adoption across that product with the most sophisticated enterprises. The largest hotel chains in the world want to operationalize with us in that way, the largest airlines. So it's becoming more of a standard for us to deploy as well.

Yes. And there are certainly many use cases outside of the media engine. So customers are storing their transactional data, any of their website visit data, even store visit data, loyalty data, all of those things really to try to get customers to be more engaged in any channel, but also to do repeat purchases or repeat transactions. Whether that's travel and hospitality, retail, telco, we work with all industries. So many of our customers are storing a vast amount of data in Snowflake. And again, it can range everything from customer data to transactional data. And then combined with our data assets, as Neej mentioned, makes it more powerful and the decisioning easier and faster so that we can be more accurate in who to target when and what channel.

Awesome. Thank you, Pam. Matt. Next question.

Thank you, guys. I appreciate all the color today. DJ Hynes from Canaccord. I'm going to ask questions of the 2 Chrises. Chris, I'll start with the finance question. You made the case that the replacement cycle is accelerating, then you gave us some very Zeta-specific data points, right, 50% increase in deals per rep, 50% increase in -- I think it was deal size. Is the takeaway that you want us to have from the finance part that the business is accelerating as well? Maybe I'll start there, and I can ask Chris.

The broader trend would say yes, right? I don't want to get into where third quarter is. We've got early November to do that. But the underlying metrics, if you look at it as backwards as '21, '22, '23, '24, whether it's our scaled customer count, our brand expansion, our use case adoption, all of those metrics, which eventually make their way to revenue. Those are improving.

Okay. And then, Chris, on the tech side, you made a comment, and I'm paraphrasing, something along the lines of like you can't [ bytecode ], this stuff, right? Intuitively, it makes sense to me, but it's like the unknowable bear thesis that's afflicting the category today. So maybe to go like a layer deeper, like what can you [ bytecode, ] what can't you? And what gives you confidence in kind of the durability of the platform?

Sure. So this is a tricky question because you have to go like 4 layers deep in order to really get to the marrow of what's preventing people from building enterprise software at scale using [ bytecoding ]. I'm going to start with the tools that we use at Zeta and our engineering team. AI-driven tooling for engineers is here, and it works incredibly well. Automated QA testing, digging into an issue. We're seeing massive performance gains. Quite literally, something is solved in 2 minutes. It might have taken a team of engineers hours and hours to figure out before. So AI tooling is here. When it comes to building enterprise-level platforms, where the broader industry is nowhere close. You can't use one of these coding environments to build something that has trust and security and deployment and scaling all in it. So we will see organizations come out with really jaw-dropping applications that they built in a night, but they're vaporware. They're this thick. For them to go through and productize that, if they're lucky, they've got a robust adaptive fabric, like I talked about earlier, that data foundation that serves all of it, and that data foundation really needs to culminate from years of wisdom. An identity graph. I've been in this for a long time, built a lot of identity graphs. Getting it right is not something you do in a single shot. And AI today is still very single shot oriented. You can evolve it slowly, but it's not going to scale at an enterprise level business. SMBs, if you're a 4-person start-up, eat your heart out, but we all know that 4-person start-up is going to get something that gets product market fit into market, and then they're going to go after build it afterwards.

Let's also be clear, DJ, to get through a large enterprises, data security audit, their procurement team, getting to the level of enterprise-grade solutions that are necessary to these large companies, no large language model is even in the ballpark. So I do think -- there's been a lot of talk about it over the last week. I think it's massively overstated as it relates to just enterprise software, not just Zeta. The other thing I would say that is a meaningful differentiator to Zeta is our data cloud. None of the large language models have any deterministic data. Now, they might have some small data sets on the people who are logging in and paying them to use their product, but that's not going to help them in the enterprise ecosystem. That's not to say that OpenAI, Claude and the others aren't building incredible businesses, they are. They're just not even remotely in the ballpark to be building enterprise-grade software that could get into a large enterprise. I mean, could you imagine the largest banks turning that over to a large language model, the largest airlines, the largest hotels, the largest automotive manufacturers. They have built their businesses and are not going to trust it to a non-enterprise-grade product.

Awesome. Next question, Matt.

Terry Tillman, Truist Securities. It's a 2-part question, sorry in advance. Pricing strategy, you've alluded to this several times. And I know with some agentic capabilities, that's going to naturally be a kind of a pricing dynamic that's different. But you talked about into next year, there is some pricing strategy kind of evolution going on. I'd be curious if part of that is to further accelerate One Zeta or maybe it's to capture more of this point in time replacement cycle that seems like it's a big deal right now? And then the second part of this question is, what do you think of all the things that's going on Athena? And you have a bunch of new things you're going to be talking about Commerce Cloud, [indiscernible]. What do you think is the biggest single unlock for that second use case? Because that's the real revenue uplift when you start getting into that as you talked about earlier, Chris.

Maybe Matt and then I want to give Nate a chance to give a perspective, but then feel free to close it out maybe.

Very good. So on the pricing strategy, I mean, as I said, we're still in the process of sort of refining. But what we do know as we look at sort of our customer base and we think about the adoption path that are going on and even as you talk about sort of capturing more of the One Zeta sort of aspects to it, is ultimately, we're trying to create a strategy that removes all of the friction related to the adoption. How do they have the ability at any point in time as their strategy changes to be able to go into the next feature of the tool, the next capability, the next channel without having to go back through procurement prices, go back through negotiation, go back through all of the aspects that really prevent them from sort of moving forward. So we're looking at mechanisms that creates fungibility of what they spend with us in order to give them opportunity to really explore and use every aspect of it, from the AI to a new channel to a new set of features to help define sort of the strategies that they're going to sort of leverage in those things. So we're in that process now. We're actually working very closely with our customers and sort of talking to them about what it would look like within their world because as much as we can go in and launch those strategies out there, it's a little bit about how they also buy. So we're working with them in order to understand those aspects of it to make sure that we're going to end up in a place that doesn't necessarily create more friction when we're trying to remove all of the friction from that process. That's out.

David, do you want to...

Let me jump in. I'll let Nate talk about Athena because he's really, really good at that. When you see the demo of Athena tomorrow, Terry...

They got us a little bit of a sneak peek, but not the full.

I heard that. I was surprised, but that's okay. When you see the deep dive tomorrow, which was supposed to be tomorrow, that's fine, you're going to see Athena seamlessly move through multiple use cases in a conversational manner. So when you think about the ability to move from 1 use case to 2 and 3, I have never seen us or, quite frankly, the market develop a product that removes the friction, to use Matt's vernacular as well as Athena does. So effectively, you could be a single-use case activation client using multiple channels. And Athena could literally ask you, hey, have you thought about the fact these customers are likely to churn, we can help you save them literally in real time. Nate, did you want to add to that?

Yes. Just to compound on what David has articulated and Chris, as we -- tomorrow, we'll really start to see the journey around the application of Athena, where apps have been built on our SuperGraph and data platform. Now when we think through moving forward, what that looks like, we want to really evangelize the developer community that's really the unique data set that we have and start to build applications, more applications at the top of it for the marketing jobs to be done and as well as adjacent industries. And so we have OpenAI tomorrow, who will be speaking as well on our panel and comparing those to my friends at that business, that's where we truly believe is going to be the step change as we move forward as well.

Thanks, Nate. Thanks, everybody. So we're about 9 minutes, probably 2 to 4 questions, if we keep them to single part questions.

Jackson Ader at KeyBanc Capital Markets. The One Zeta strategy kind of began with -- had some restrictions on it, right, on who could sell it, who you were actually targeting. It seems like the 50% slide, right, like 50% pipeline up, 50 -- up above 50%. Are there any limitations still on the One Zeta? Or is it like everybody can sell it now to everybody? Or is there still some sort of like strategic rollout that we should be waiting on?

Steve?

So One Zeta has gone from a motion to a model. And when it was a motion, we wanted to ensure that we could perfect it. Testing, learning, scaling is core to anything that's data-driven. And as we're moving from data driven to answer driven, we're able to expand the aperture. The other thing that we did was structural. And when I talked earlier about the notion of growth being not just predictable but structural, it's not just how the platform is operating, it's how we are operating. So the notion of an operating model is purposeful. And a big part of perfecting it with a smaller population was so that we had the beginning of a model that recruiting Ed See out of McKinsey would be an amplifier to take it to another level. So I'm going to tee it back to my partner, Ed, to talk about how we are taking this to the next level and how each and every case study that I walked through today is a now example, not a yesterday example. And those are not in isolation. Those are all repeatable. Ed?

Absolutely. I think one of the big things, as Steve was mentioning, was moving from motion to model. What we're doing with One Zeta is really opening up the CMO TAMs. Beforehand, we've been working deeper down the organization with semi-fungible budgets from CRM, CDP to performance media. Now we're beginning to say, how do we address the CMO's need, as you heard on the panel before. And that's really saying, how do we help CMOs be able to recognize pockets of opportunity, reach those pockets of opportunity, deliver relevance to those pockets of opportunity and make sure that they can actually see and track the results. This idea of being able to tie all those pieces together to manage a customer journey and to manage a customer from end to end is what we're now able to do, and we're taking that to the CMOs. So we've broadened the TAM. We've broadened the folks that we're talking to and we'll continue to make sure that we're going to help marketers be able to take advantage of our precision scale across all touch points.

And to be clear, all of our sales reps can now sell this.

Yes.

Just to be crystal.

Matt, next question?

Madeline Brooks from Bank of America. A quick pointed question for you, Chris. You mentioned NRR of about 115% for 75% of the business. Can you just give us a refresher on the other 25% and trends that you're seeing there?

Yes. The -- so just to kind of create context, the customers that are greater than 3 years on our platform, that's the 76% that has a multiyear average of greater than 115%, where we see the lowest net revenue retention is our less than 1-year customer. A lot of that is driven by the pilots and proof of concept. So when we are between, call it, $50,000 in spend and, call it, $300,000, somewhere in that range, that's where there's the most call it a flame out of a pilot. It could happen for a multitude of reasons. It could be customers didn't really set aside the budget that we expected to go much broader post the 3- to 5-month pilot phase. But that's where we get the most turnover. So as you would expect, as you look at that slide, you can almost draw a line up into the right in terms of where net revenue retention was. That -- call it that less than a year category. I don't want to be like decimal point precise, but probably somewhere between like 95% and 100% NRR. Sorry, I was doing Matt's job for him. Bad habit.

Matt Swanson from RBC. I guess when we talk about this process of moving from Zeta who to Zeta why to Zeta now, could you talk about the advantage of partnerships like a Snowflake and for companies to be able to say, maybe even also with the increasing business units to say, hey, I can standardize with these guys because there's some kind of shared...

Yes. So let me start by saying that when nobody knew who we were, it was really, really valuable to be able to say we're fully partnered with Snowflake and AWS and others. What's now happened is they've started selling our products as well. So as we've moved from why Zeta -- I'm sorry, from Zeta who to why Zeta -- I'm getting confused with all the different things we say here. We're seeing more sales inflow from Snowflake and AWS in particular. And I think a lot of that was the evolution of the brand. I also think it's one of the reasons we're seeing our pipeline at sort of record numbers. So I do think that, that's helped with that. I think it's also helping in the agency business, interestingly enough. So a number of our agency clients -- we go one brand at a time. They bring us in to solve a problem, and then we're able to expand there. Some just turn it on. It just depends on the agency. And the ones where you're sort of going brand to brand, we're seeing meaningful uptick as people are even in many cases, saying to the agency, we want to work with Zeta, can you make that happen. So I do think that the brand evolution is meaningfully driving the business.

I think it's also having, by the way, just because I -- as I look at our candidate funnel, and I'm like the constant like, gosh, do we need this many people, but it's actually helping a lot in recruiting. And maybe talk a little bit about our recent accolades that we've had with Forbes and others.

Yes. I always position it that when our clients are choosing us, they're also choosing the culture that we have, our collaborative innovative culture, being recognized by Great Places to Work as well as being on the Fortune top list for technology overall. It just is an accolade to -- and a testament to the environment they're creating for allowing our employees to do their best work, which at the end of the day, brings the client outcomes and successes. So the other side of that coin, yes, great products, great services, but it's all the team who gets it done and the culture that we provide in order to make that happen.

And to Chris' exact point, as the brand evolves, the level of people that we're able to get join our company as evidenced by Pam, and Ed and Nate -- see who else behind me. Well, you guys have been here a while. But as you look at the new people who are joining us, I won't speak for them, but 3 or 4 years ago, I don't think they would have made that decision. Thank you, Pam. She turned -- I wouldn't know. But the truth of the matter is we're seeing that in Chris' group in a meaningful way. We are bringing in engineering talent that I don't think we ever would have had access to. Chris, do you want to touch on that for just a second?

Yes. I mean we've always recruited the best from around the world, and you have to go out and get your tendrils into those communities. Now they're coming to us. They're showing up at our doorstep. They've heard about us, either they've worked with us as a partner in the past or they say, I want to get into AI, and they see Zeta as the battleground for their career to prove out that they can be pioneers. It's been absolutely exceptional, and a smaller group, I could talk about the last 2 weeks, people that have joined from the top companies in the world because we don't just tell, we show. And that's a big differentiator for Zeta. It's about rolling up your sleeves and doing the hard work.

All right. Let's do one more question and then we'll wrap it up, if there is one. Jason in the third row.

Jason, this has to be a good one. It's the last question.

That's a lot of pressure. Jason Kreyer from Craig-Hallum. I just want to ask about international. I mean you're acquiring Marigold, that's got more EMEA presence. You launched the GEO Explorer. So just how you think about international, that opportunity changing from just a few quarters ago?

Steve?

I'll let David take this one.

I was told not to talk too much today. So I was trying to be good. You're yielding the time.

Yielding the floor.

So listen, our platform operates globally. As you all know, the vast majority of our revenue currently is in the United States. One of the things we were very excited about with the Marigold acquisition was the acquisition of Selligent. They have a meaningful platform, sales team, operations and revenue in Europe today. So our plan is to merge our Data Cloud, which is already GDPR-compliant, already operates in Europe into what Selligent is doing and accelerate our growth, specifically into Europe over the next few years. So I think that we had always said, Jason, that we thought of international would come with some type of M&A. Quite frankly, it was sort of like when we first started looking at Marigold, they wanted us to buy the entire thing, which didn't work for us because we didn't want to be in the small to midsize business ecosystem, at least not for the very foreseeable -- the long future. But we were really excited about the enterprise businesses because you got Selligent, which perfectly plugged into Publisher Cloud. You've got the loyalty business, which we think game changing from an algorithm, data and deeper relationships with our clients. You've got Cheetah Digital, which is one of the premier platforms in marketing automation, one of the other very few firms in the Forrester report, which will merge into us. And then we were very excited about Selligent. Now I know Gerber was particularly excited because now he gets to go visit Europe more often than he was doing, and he's already planned out visiting all the offices, specifically in Southern Italy. But no, I'm teasing.

Just to build on it, though, I think it's an interesting point in time, particularly in Europe. 5 years ago, there was a divergence of forces. There was a divergence of buyer behavior in Europe specifically. We're now seeing a convergence of that. So we believe that the platform that we have, the assets that we have are hitting the market at scale at the right time.

It's also, I think, about to go through a very similar replacement cycle that were -- we saw start in the U.S. a year or 2 ago. The dominant platform in Europe, I mean, they say they have a cloud solution, but I haven't seen it yet. So it does appear as if a lot of what's going on in Europe continues to be on-premise behind the firewall which is very difficult to scale. So we think our cloud solution in partnership with Selligent is going to be a meaningful capability as we focus on growing in Europe.

Two final thoughts from me. First, lunch after this in the cafe. And then second is a thank you. Thank you to our team, to our customers and our partners who were so gracious to speak today, and then really to you all. It's an enormous investment of your time. You've got 1,000 things going on at once. So thank you, and we look forward to mingling with you over lunch. And see you tomorrow at Zeta Live. Bye-bye, everyone.