Zeta Global at Bank of America Conference: Unified Marketing Strategy

On Thursday, 05 June 2025, Zeta Global Holdings Corp (NYSE:ZETA) presented at the Bank of America Global Technology Conference 2025. The company highlighted its innovative marketing technology platform, which unifies customer acquisition, growth, and retention. While Zeta Global reported strong growth amid economic uncertainties, it also emphasized the challenges competitors face in replicating its integrated approach.

Key Takeaways

• Zeta Global’s marketing platform integrates customer acquisition, growth, and retention.
• The company leverages identity-based marketing with data from Disqus and LiveIntent.
• Despite macroeconomic uncertainties, Zeta Global closed three major contracts recently.
• The "OneZeta" model offers a unified platform for media buying, CDP, and marketing automation.
• Zeta Global focuses on international expansion and enhancing AI capabilities for better ROI.

Company Overview and Differentiation

• Zeta Global specializes in helping enterprises acquire, grow, and retain customers through a converged marketing platform.
• Its key differentiator is identity-based marketing on the open web, similar to Facebook and Google.
• The company’s network reaches about 90% of the US adult population monthly, using data cultivated over several years.

Demand Environment and Growth

• Zeta Global experienced strong performance in April, closing three of its largest contracts amid macroeconomic volatility.
• Consumer behavior patterns remain stable, with strong demand even in retail categories.
• The company’s ROI-driven solutions continue to attract marketers despite economic uncertainties.

Data Assets and Quality

• Zeta Global’s data comes primarily from Disqus and LiveIntent, covering 90% of the US adult population.
• Data is validated through partnerships with credit bureaus, ensuring compliance and transparency.
• Approximately 80% of the data is sourced from its own network, with the rest from partners.

AI Strategy and Tech Stack

• Zeta Global uses AI to enhance productivity, improve impressions, and enable one-to-one personalization.
• The tech stack includes modern frameworks like Snowflake and a proprietary AI framework compatible with leading LLM models.
• Streaming data capabilities allow real-time actions based on consumer intent.

OneZeta Model and Sales Motion

• The "OneZeta" model integrates media buying, CDP, and marketing automation.
• Only 15% of customers use multiple use cases, indicating potential for significant revenue growth.
• The model supports multiple channels, including email, display, video, social, and CTV.

Future Investments and Priorities

• Zeta Global aims to enhance generative capabilities for better ROI and focuses on international expansion.
• Potential acquisitions may enhance the data graph and service offerings for enterprises.

Q&A Highlights

• Zeta Global’s data asset is difficult to replicate due to the scale and network effects of Disqus and LiveIntent.
• The company’s consolidated identity view enables informed and personalized marketing.
• The tech stack supports real-time reactions to consumer behavior, enhancing marketing effectiveness.

In conclusion, for a detailed understanding of Zeta Global’s strategies and insights from the conference, refer to the full transcript below.

Full transcript - Bank of America Global Technology Conference 2025:

Koji Keta, Software Analyst, Bank of America: It’s Koji Keta. I am the software analyst one of the software analysts here at Bank of America. I’m absolutely thrilled to be closing out our tech conference with Zeta Global. We have three here. We have Matt Pfau, VP of Investor Relations, Nizh Gore.

What you are the chief data officer, and we have a special guest.

Vasirag Bali, VP of Data Cloud, Zeta Global: Vasirag Bali, VP of Data Cloud.

Koji Keta, Software Analyst, Bank of America: Yep. So thanks so much for being here, guys. I guess we should start it off with, you know, maybe for those in the room that are unfamiliar with Zeta Global and those in the webcast that may be unfamiliar with Zeta Global. What is Zeta Global? What do you guys do?

What is the opportunity that you’re going after?

Nizh Gore, Chief Data Officer, Zeta Global: Sure. Maybe I’ll start, Matt, you can chime in. Yep. So Zeta Global is a marketing technology company, and we help enterprises, mostly mid market to large fortune 100 enterprises, acquire, grow, and retain their customers, and these are mostly consumer facing. There are two things that we do that are very different than the way they’ve traditionally been done in the market.

One is that we believe that marketing is converging. In the last ten years, CMOs have made significant investments in companies like Snowflake and Databricks. They’ve brought all their data into one place. The reason that’s great is because you can apply the AI to one canonical view of the data. Zeta believes that because you’ve done that and you’ve made those investments, it is the best for the organization to be able to acquire new customers, to grow customer value, and to retain them from one singular platform.

And that’s also what we’re seeing from CMOs around The US and around the world. The second thing that is disruptive in the way we operate is that we bring identity based marketing to the open web. So you’ve all seen platforms like Facebook and Google and Amazon do really well. In those platforms, you are always identified as a person. You’re logged in.

You action it within the platform, you receive marketing, you make purchases, and then they optimize your workflow the next time they see you on the platform. In a very similar way, our system relies on identity based marketing using a dataset that Zeta has cultivated over over several years. We own and operate large enterprises that service consumers and and publishers across the Internet. And through that, we’re able to see a large swath of The US population and global population. We see about 90% of The US adult population on our network every month in a similar way to how Facebook or Google see the population on their networks, and we can use that to synthesize intent and identity around what someone is about to do next.

And we can use that to help our marketers, the enterprises that we service, be better with acquisition, growth, and retention. So this model has traditionally never existed in Martech and AdTech. And I know in the investment community, you guys like to think along the lanes of Martech and AdTech. But if you look at this from the view of a customer of ours, the CMO, they’re very much thinking about convergence and how they can do more out of one platform across all of those lanes.

Koji Keta, Software Analyst, Bank of America: So you mentioned marketing and advertising. I think these are two demand environments that are hotly debated right now, you know, for better or worse. Sure. So you guys have been growing pretty well. And so how how are you seeing the demand environment today specifically to Zeta?

Nizh Gore, Chief Data Officer, Zeta Global: Yeah. So I’ll I’ll I’ll comment and Matt chime in, please. So I think that there’s two things that are happening that are divergent. So we’ve all been hearing that consumer sentiment is all over the board. Yeah.

Right? In surveys and published reports on consumer sentiment. That’s led to people thinking there’s a pretty unstable macro right now. And and generally, they think there’s an unstable macro, then one of the first budgets that gets cut is marketing. And that’s pretty straightforward and and and makes sense.

What we see actually is something different. Consumer behavior patterns haven’t really shifted. Demand, even in categories like retail, are especially up. They haven’t changed. And our customers are still engaging with us to drive more and more opportunity than they have historically.

April was one of our strongest months. It was a month that was tepid with macro volatility from the external perspective. And in the last ninety days, we’ve closed three of our largest contracts in the history of Zeta. So there’s still tremendous opportunity this year, and I think what you guys see from a macro perspective, what gets represented is not really representative of the way that our customers are viewing the current landscape to operate. And we also signed three of

Matt Pfau, VP of Investor Relations, Zeta Global: our largest deals ever in the past ninety days. And even if you look at from a vertical perspective, some of the ones that people might think would be more impacted by tariffs are macro sensitive, for example, auto. We’ve seen good momentum in that sector to start the year and have signed more business in there post the liberation day.

Koji Keta, Software Analyst, Bank of America: So it seems like there’s a and you guys see it, the divergence between sentiment and actual transactions. Activity. Activity. Activity. Why do you think that’s happening right now?

I mean, why is consumer sentiment bad? I mean, I think it’s Yeah. Clear, but but why why do people keep spending? You know, you you put out your economic index. Right?

Nizh Gore, Chief Data Officer, Zeta Global: Economic index. Yeah. So we put out the economic index as to how we see the view of The US economy every month. I think sentiment is down because there’s a lot of news that goes back and forth. Right?

For better or worse, one day it’s x, the next day it’s y, the third day it’s back to x. And so that makes consumers feel uneasy, but spending patterns have not shifted. The job market’s strong, you know, relatively strong, and activity around consumers and their behaviors with, you know, merchants has continued to persist through this time. So I think the underlying economic indicators that we track are actually still very healthy. Regardless of

Matt Pfau, VP of Investor Relations, Zeta Global: the macro environment, marketers’ job doesn’t change. They need to acquire, grow, and retain. Yeah. And all of our products are return on investment based. And so as long as marketers are getting that return, they’re gonna continue to spend with us.

Nizh Gore, Chief Data Officer, Zeta Global: Yep. There there’s a great quote by the famous race car driver, Senna, where he said something to the effect of it’s really hard to pass 15 cars on a sunny day, but we can certainly do it when it’s raining. And if you look at Zeta’s track record and what happened during COVID, which is also a time of great macro uncertainty, we actually accelerated out of COVID. Yeah. We took market share from our competitors.

And in those times, marketers looked to ROI delivering solutions more closely, and we are more aligned with those kinds of capabilities with them.

Koji Keta, Software Analyst, Bank of America: Glad to hear you’re a Senna fan. I am too. And he he did it. I I know he did that in a in a rainy race many, many years ago. Okay.

We got the data guys from Zeta Global here. I think that’s fantastic. I think the data aspect of of Zeta Global is not only one of your key differentiators, but also one of the key debates out there in the investment community. And so talk to us a little bit about what is the data that you guys have. Sure.

How do you gather that data, and how do you make sure that the data quality is strong but also compliant with the regulations that are out there?

Nizh Gore, Chief Data Officer, Zeta Global: So let let’s start with the last question first. So we try to stay ahead of compliance in The US. Obviously, there was a short report last November. We held a full day data summit in December where we went point by point and talked about our data asset. The reality is is that we work with highly regulated industries like banking and telecom.

We would never pass these long info sec processes if they felt these customers felt there was something incorrect about the way we appropriated data and brought data into our environment. So truthfully, we weren’t as transparent as we could have been with the investment community. We tried to correct that from December moving forward. But from a customer perspective, we had no disruptions from the short report, and we feel like our business from that perspective has never been stronger than it is today. I will say on the data, I’ll go into it in some detail.

So we own two at scale networks and they interact with consumers every single day. So one is called Disqus. Disqus is the largest commenting platform online. So imagine your favorite website, you scroll at the bottom, whether it’s a commerce site or or a publishing site, and you can you can leave a comment, you can upvote, you can downvote, you can respond to a poll. Discuss provides small to medium sized publishers and some large with engagement tools that keep visitors on-site.

The value exchange there is that the publishers are generally able to monetize their traffic at higher rates, and Disqus gets access to the opt in data that comes through those sites. On the flip side, we own LiveIntent. LiveIntent is the largest ad exchange serving the largest publishers in the world. Think publishers like the New York Times, the Wall Street Journal, Groupon, Sam’s Club. So I use the word publisher broadly.

And LiveIntent helps those publishers monetize their emails. So when you get an email from that publisher, the ad units that are placed in those emails are being powered by LiveIntent. And through that, we also get permission to use that type of data for graph building. And we’re not the only kind of company that uses open web data of these formats for graph building, namely Google does it, Facebook does it, Amazon does it, data does it too. So those are our two types of data that we bring in.

From the two networks we bring in, We constitute three types of data from that. We constitute identity data, so the the representation of a person. We have about 200 to 245,000,000 of those in The US. It’s about 90% of The US adult population, so it’s a mature at scale graph. On top of that, we layer in signals.

Signals are what are you doing now and what do you plan to do next? So we use our LLMs internally to generate a view of your next best action that you plan to take. And we also have identifiers. We wanna find you across different channels. Let’s say we wanna send you a CTV ad, we wanna send you an email, we wanna send you an SMS, we wanna send you a direct mail.

How would we do that? So that’s the asset and how it comes together. That gets basically brought into our platform and it helps our customers again know more about their customers and it also helps them acquire customers at scale through our platform. But they have to do it through our platform.

Koji Keta, Software Analyst, Bank of America: So I’ve covered marketing and advertising technology vendors for a long time. And whenever I talk with customers and partners, they always tell me you’re only good as your last ROI, essentially. So how do you maintain or how do you think about maintaining that data asset lead for the next, call it, five to ten years?

Nizh Gore, Chief Data Officer, Zeta Global: Yeah. So I I think there’s two things. So the first is that these assets that I mentioned are growing. So they’re seeing more and more traffic that’s in The US and worldwide. There also are not a lot of these kinds of assets available.

So, you know, we’ll get the question sometimes as to like, well, why hasn’t Salesforce gone out and replicated your model? Why hasn’t Adobe replicated your model? It’s not so straightforward. You you would need to have at scale assets that were, you know, kind of integrated into your business operation and you have to own and operate them to do what we’re doing. This has been in the works for us for ten years now.

Right? So it’s not an overnight thing. Our goal is to continue to keep the graphs healthy, continue to provide publishers with disproportionate value so that the graph stays up to date, expand into geographies where we’re currently not. There’s a lot more we could be doing in Western Europe. There’s a lot more we could be doing in Latin America.

We’re looking at those things right now. And then as new assets come up that we think are interesting, if there’s an opportunity to acquire them into our graph, we will we’ll we’ll take those 10 types of actions as well.

Koji Keta, Software Analyst, Bank of America: As you move more internationally, are the data privacy and regulations different?

Nizh Gore, Chief Data Officer, Zeta Global: Oh, they are. Yeah.

Koji Keta, Software Analyst, Bank of America: Yeah. How do we think about that?

Nizh Gore, Chief Data Officer, Zeta Global: They’ll be different and the types of capabilities that we can launch will be different in different geographies. But, you know, you’re as good as your your your, you know, your your delta between you and your next best competitor. So, you know, we feel like, you know, there there are models that are gonna look a lot like The US and they’re gonna be models that are gonna look very different than The US, but they can still be significantly better than what’s offered in those markets currently. And what, know, Germany is a good example of a place where you’re gonna find something that’s very different, but we can still build to a level that’s even better than what’s currently available there.

Koji Keta, Software Analyst, Bank of America: So you mentioned two two primary assets discussed, and LiveIntent is kind of your what’s the right word? Not demand the generators of your data.

Nizh Gore, Chief Data Officer, Zeta Global: They’re scaled. Scale. We also license some data. Like, we partner with the credit bureaus. We bring in that data to validate and verify our datasets as well.

So there is some licensed data. The major about 80% of our data is coming from our own network, and then about 20% would be topped off from from partners.

Koji Keta, Software Analyst, Bank of America: Are these two, Discuss and LiveIntent, enough to drive, you know, ten years of data differentiation, or are you guys gonna come out with new ways to get data?

Nizh Gore, Chief Data Officer, Zeta Global: I’d I’d say they’re enough to drive differentiation because they are at scale and growing, and they have a maturity level right now that is very, very large. But I think, as I mentioned, if there are assets that come and become available that we think are interesting that plug into our model and help us service enterprises, we will certainly take a look at those along the way.

Vasirag Bali, VP of Data Cloud, Zeta Global: Okay. And also our identity graph at the core is what the unlock is because it connects all these disparate data points into a unified view of consumers, helping brands see really outside their four walls, right? So brands really typically only see what the interactions that’s within their four walls. We’re able to through identity connect whatever signal we see from our networks or from our partners or from any of the channels that we interact with and be able to bring that view. And then on top, the LLMs and the AI that we have and drive those answers that help drive the marketing decisions that help bring more profitable customers for for our clients.

Nizh Gore, Chief Data Officer, Zeta Global: Okay. Okay.

Koji Keta, Software Analyst, Bank of America: So you guys kinda have, you know, I think I wrote a note before, like, three pronged approach to to attacking the market, CDP, marketing automation, and execution. Right? So how do we think about the differentiation of Zeta within those three prongs? What is the key, you know, hook Yeah. That that makes you guys different?

Nizh Gore, Chief Data Officer, Zeta Global: So we have two sales motions today. Yeah. One is that you’re start or we I say historically, we’ve had two sales motions. You start with Zeta by buying media. Media means you’re looking for new customers, and that’s usually a share of strip from vendors like Trade Desk or Quantcast.

It’s usually in concert with the agency that you’re working with. So the agency will come to Zeta and will become a subordinate of of the agency to help drive ROI. You could also come to us and you could say, I want a CDP or I want a marketing automation suite. That’s typically called owned media. And in that lane, we’re competing with Salesforce, Adobe, and there’s a litany of smaller players that we see from time to time.

Our new model is called OneZeta, and it’s much more aligned with where the modern CMO is going. And the modern CMO is asking the question, how do I acquire, grow, and retain from one place? How do I use my one set of data to inform all of those decisions? I mean, if you could tell me, and and I’m sure in your own experience, the amount of times that I I have an American Express card. The amount of times they get marketed in American Express card, again, is like ridiculous right now.

Right? And because they don’t understand, their acquisition group does not understand that I’m already a customer on the growth and retention side. This is a problem for virtually every company that’s not doing it the right way, and we can help solve that problem. And that’s the kind of problem that we’re looking to solve right now for for enterprises. Okay.

But but the one Zeta model we’re very excited about because there is tremendous revenue leverage that gets created when one of our customers moves from one use case to a second use case. Historically, we’ve always talked about channel expansion. I’m using data for email, and now I’m using data for SMS, and now I’m using data for website personalization. That’s not use case expansion. That’s channel expansion.

Use cases, I’m using data to grow, and now I’m using them to acquire. Only 15 of our customers today are using us for multiple use cases. And the revenue leverage you can create from moving from grow to acquire can be five to 10 x. An example of that would be look at t mobile as an example. T mobile probably spends, this is just my guess, but somewhere between 30 to $50,000,000 on software every year, and their media budget is about $3,000,000,000 a year.

So your ability to to to tackle use cases is gonna give you disproportionate lever revenue leverage, and this is a key area of focus. We brought in a chief growth officer. He was the partner at McKinsey responsible for their marketing practice. His name’s Ed C. He is leading this one data approach right now.

Matt Pfau, VP of Investor Relations, Zeta Global: And besides the fact we can do multiple use cases, even if you look within each one of those use cases, we’re doing multiple channels within there, which some of those competitors that niche mentioned won’t do. So for example, we can acquire customers through email, display and video, social, CTV. A lot of the other competitors are just doing one or two of those channels.

Nizh Gore, Chief Data Officer, Zeta Global: Okay. Okay.

Koji Keta, Software Analyst, Bank of America: Sticking with the data theme, can’t have that without AI. So you guys are, you know, attacking it in your own way with with having your own AI strategy, but also customers use you for AI. So let’s tackle those both. You know, what is your AI strategy? How is that potentially driving more monetization?

And then how are your customers using your data for

Nizh Gore, Chief Data Officer, Zeta Global: So I will I’ll give an example and of of something we’re doing internally that’s representative of how we think of AI. This is for our internal uses. So the gap and I’ve been in marketing for twenty five plus years now. The gap is probably RFP for their marketing automation stack, like five times in the last ten years, which shows you they’re not happy with their current solution. They’ve never switched.

Right? The switching cost of moving from their current solution to something new would just be too high. And and that’s because they have thousands of email templates to move over. They probably have hundreds of marketing workflows to move over. There is a tremendous amount of work in switching costs that’s required to change from what you’re currently doing to a new system.

That’s contrasted by this idea that we’re right in the middle of a replacement cycle, where CMOs are looking for new solutions. So as an example, we have a tool called Compass internally, and it reduces your onboarding time by about two thirds because we use generative AI, take all of the heavy lifting off of things like rebuilding templates, moving experiential workflows, moving your data model over from your previous system to the Zeta system. And this has been in beta for us for probably six months. It’s moving into production. We were already using it internally.

Now it’s gonna be exposed to customers directly. It’s a huge step forward in accelerating the replacement cycle. And I think if you’re thinking about changing, this is gonna be a lever that that really pushes you to do that in in whereas in a past world, you may have said this is gonna be too much work for our team. That’s one. On the customer side, we we look at generative in three lanes.

We look at this idea of productivity gains. So can you help a marketer do more with the time that they have? We look at impressions. Can you help a marketer understand data and visualizations in a way that they couldn’t do without a data analyst previously? And we look at personalization.

Can you actually get to the reality of one to one personalization? One message for one person, one channel for one person. This is where generative is gonna go. We have tools that are all oriented towards this. Yesterday, we had a really prominent announcement.

I’m not sure if you guys saw it, but we announced something called the Answers Framework. And I’ll contrast this with what something I heard at the Snowflake Conference this this week in San Francisco. So with the Answers Framework that we’ve launched is the intersection between intelligence and action. So when you can make it easy for a marketer to create intelligence, interpret intelligence, and then act on it into a marketing workflow, you really solved a lot of their problem. You know, Zuckerberg talked about how in Facebook, I think it was in the New York Times, he had written about how you’re gonna tell us your outcome and your budget, and our agents are gonna do the rest for you and deliver against that.

Now that’s in one channel, but that’s alluding to the same idea where you can make it very easy for a marketer to take action on something that we think they should do. That’s where our systems are pointed. Most of the other capabilities that exist and it’s Snowflakes conference, I they have a new agentic framework through Cortex. They’re talking about the interpretation of data. You can ask questions of your data, which I think is great and it’s a great start.

But moving that question into something that you can actually do with it is still very challenging for the marketers. So that’s the piece that you really have to to master, and that’s the piece that we’re unlocking with the Answers framework. It’s being released in some of our tools as of yesterday when we announced it. And then a litany of tools within our platform will get that between now and Zeta Live and into the future. Zeta Live is our conference in October.

Vasirag Bali, VP of Data Cloud, Zeta Global: I would also add that as we’re getting more data, first party and third party into our universe, that data is all feeding the models and AI that helps reduce as Nish said, the time to impactful value for our clients. And that drives consumption, right? The more that you shorten that time to impactful or ROI positive impact that the more they’re doing with us, the more they expand use cases and channels, and that drives the consumption up.

Koji Keta, Software Analyst, Bank of America: Is it okay if I get technical on the tech stack for you guys in data? And so I think with data and AI, you know, lots of buzzwords get thrown out here and there. But I wanted to dig in on what the stack looks like. Like, is there anything specific about the data stack, the technology stack that makes you guys differentiated? You know?

Is it the the database structure or the search functionality within it, the the plug ins, the APIs, whatever it may be? I’ll let you take this first. Know? Sure. Go as technical as you want.

Right? Sure. It’s happy to under would love to understand it. So I think one of the

Vasirag Bali, VP of Data Cloud, Zeta Global: main advantages data was built on on on modern frameworks. That, you know, foundations like Snowflake that are sort of modern database systems where, as opposed to sort of the older models where a lot of the bigger legacy competitors are built on. So it’s a modern data platform. On top, we have our own AI framework and then genetic framework that’s plugging into all the leading LLM models and then some of our own internal ones that are training specifically. And then obviously the fuel for all of this is our data cloud and all the data that we feed in that completes the view of each profile of customer or, you know, prospect that feeds into the data.

So I would say modern bottom stack proprietary and plugged into all the leading LLM AI on top and then fueling them all the amount of data, the unique data that we have that we can feed this all through.

Nizh Gore, Chief Data Officer, Zeta Global: I would also add that our systems are built for streaming data, and a lot of legacy systems are built for batch data. And that’s important because if you want to have first mover advantage to talk to a consumer when they demonstrate its intent, you need to be able to stream that data in, you need to be able to understand what it means, and then take action on it immediately. Right? So streaming data at the scale that we operate is nontrivial. And you need to understand data pipelines and have built out robust data pipelines requiring, you know, years of development to to do that kind of thing.

Vasirag Bali, VP of Data Cloud, Zeta Global: And then our identity also, again, the streaming and having the identity at the core, we’re able to stitch together what’s happening across all your channel investments. So you’re, as you’re running campaigns on CTV or social, or all that stuff is coming in, getting stitched into the profile in real time. And then you can react based on those and adjust your tactics. So that, these are the foundations of getting to autonomous marketing.

Koji Keta, Software Analyst, Bank of America: So you mentioned two things there that I actually wanted to ask about was streaming data and then the customer journey across different channels. And so I guess, specifically on streaming data, you know, what type of technology do you use for streaming data? Is it Kafka? Yeah. We have version of version of Kafka?

Nizh Gore, Chief Data Officer, Zeta Global: Yeah. We have a version of Kafka that’s been configured for streaming queues. There’s probably, you know, 10 different database and database structures that are used as Zeta. As an example, Snowflake’s really great for some things, but it’s not great for streaming. So you need to have other infrastructures in place that play nice with those kinds of technologies.

Maybe Snowflake would tell you differently, but that’s my opinion and our opinion at Zeta. Yeah. And then

Koji Keta, Software Analyst, Bank of America: on the customer journey side, I I remember when we did a demo with you guys in New York about a year ago, I’d like to say. Yeah. One of the things that I thought was very interesting about that demo was the ability to follow the customer across different channels, which is not something other vendors can easily do from what I gathered. And so what is it about the tech stack that enables you guys to be able to see? Yeah.

So we we have a

Nizh Gore, Chief Data Officer, Zeta Global: consolidated view of identity across our channels and external channels. So when you take an action on a website, when you click on an ad on the Internet, when you respond to an email, when you maybe receive a direct mail announcement, all of that can be stitched back to your profile. And we can I don’t like the word follow because it sounds creepy, but we can use that as to inform the way our models will work so that you can receive better marketing? Because at the end of the day, marketing comes down to two things. Where is someone addressable and where are they likely to respond?

Right? These are the two things you have to master if you wanna be a good marketer. And and Zeta is exceptional at understanding both of those those vectors. Yeah.

Koji Keta, Software Analyst, Bank of America: So may maybe to round out the conversation here in the last few minutes is that it sounds like you guys have a differentiated data asset. You have the ability to execute campaigns, and you have marketing capabilities too, which are three categories that feel very, very large, and there are players in there that are large. And so why is it so difficult for a vendor within one of those categories to do what you do?

Nizh Gore, Chief Data Officer, Zeta Global: I think there’s two things. So first of all, the marketing clouds have, in my view, lost some of their focus. You may have seen Salesforce and they’re reporting on their marketing cloud growth at like 4%, whereas we’re growing significantly faster than that. Because we’ve made investments that have set us up for this new modern age of marketing. But getting back to where I started, I think that where the CMO is today is they believe in convergence, meaning acquire, grow, and retain happening in one place because that’s the way they’ve organized their data.

It is hard for a marketing company to if they’re doing acquisition, to immediately get into grow and retain. Like, maybe tomorrow Salesforce will go out and buy I’m sorry. Maybe Trade Desk will go out and buy Braze, but I don’t see that happening this week. So you would have to make a transformational change to your business strategy to do it. That’s number one.

The second thing is building the kind of data asset that we have built over the years in the way that we’ve built it is hard to replicate. Not impossible, but it would take a company significant amount of time, especially in today’s privacy landscape to do this the right way. And so we we feel like we have a significant advantage there as well. And both of those things are contributing to the growth that you’re seeing in our in our quarterly updates.

Koji Keta, Software Analyst, Bank of America: Is the the two the two assets that you have that can drive your data or the two main ones discussed and and live intent, are are those very difficult to replace? Meaning Yeah. If someone wanted to get a data and asset, would have to find another place.

Nizh Gore, Chief Data Officer, Zeta Global: Yeah. The technology itself is maybe not as difficult. Anything can be built these days, but the network they’ve created would be very hard to replicate. Okay. Okay.

Just it’s it’s got tremendous scale. Okay.

Koji Keta, Software Analyst, Bank of America: I guess in the last last minute here, you know, as we think about the data asset for Zeta Global, what’s the the key investment priority for you guys to keep data differentiated for you guys over the

Nizh Gore, Chief Data Officer, Zeta Global: next few years? It has less to do with differentiating on the data side. It has more to do with differentiating on the outcome side. Okay. So it it has more to do with making sure that the generative capabilities we build can play nice with our data to generate better outcomes for customers, which inevitably is all they care about.

They want higher ROI, and so you need to have both of these components to be able to deliver against that. Awesome. Guys, we’re

Koji Keta, Software Analyst, Bank of America: out of time. Thank you so much for being here. We appreciate it. Happy to close out our tech conference with SADA Global. Thank you so much.

Nizh Gore, Chief Data Officer, Zeta Global: Thanks, Koji.

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