Today, my name is Scott Berg. I lead our enterprise software and SaaS research efforts here at Needham. Today with us, we have Zeta Global, Zeta Global, excuse me. This is my first time to have a fireside chat with you.
I know.
So I'm excited here. We're gonna have fun with this today. So, with us from the company, we have the company CFO, Chris Greiner, and we have Winnie from the IR team here. I have the typical, you know, set of questions that I'm gonna ask here. We will allocate time for questions from the audience here at the end. So if you have anything, feel free to ask. But with that, let's get started. And, you know, for those that might be new to Zeta, how about a brief overview of what the company does?
Sure. Well, thank you, Scott. Thank you, everyone. Happy New Year. Chris Greiner, company CFO. Winnie Shen runs our Data Cloud, which is awesome to have Winnie here. I'll kick things off, but it'll be pretty interactive between the two of us. First off, Zeta's primary customer is the Chief Marketing Officer for the largest brands in the world. We serve 13 different industry verticals. We're global, in nature, hence the name, but we're working with the Chief Marketing Officer who every single day is trying to figure out who as a brand do I wanna reach, how am I going to reach them, and then once I do, how do I get them to engage with my brand? And they do that primarily through three different use cases. They're looking to retain existing customers, grow their existing customers, and acquire new ones.
The three things about Zeta you should understand when you walk away from this meeting that totally separates us from anything our competitors can do are three different parts of our business. First, next to Meta, which is obviously a walled garden, Google, a walled garden, and Amazon, we are the only marketing cloud that has its own proprietary data set. Over 245 million U.S. adults have either opted in or given permission to Zeta to be able to understand what they're showing interest and intent for and market to directly. Second aspect is we can do all channels in terms of marketing. Think about where all of us are digitally in any single day. We can reach you through mobile. We can help a brand reach you through email.
We can help you reach through all programmatic channels from CTV to audio podcasting to display video and down the digital stack, even direct mail, and the third aspect is we can serve all three use cases. If you look at a Salesforce or an Adobe or a Braze or a Klaviyo, they can only help a brand with their customer retention use case, so only what that customer has within its four walls, they can help you understand better. Whereas Zeta can not only do that better, but we can help you understand what's happening outside your four walls, which is a very valuable business proposition. As a CMO and as a large brand global, you now want a single platform that drives this convergence of all three use cases, the ability to omnichannel market and have your own proprietary data that now you don't have to now buy from all these different independent vendors, but you can now blend with your own data. And we'll match, call it 95% of what's in Zeta's Data Cloud to what's in a customer's data set.
Okay. So probably a good question for Winnie, given your data background here, is, you know, Chris already highlighted a little bit on kind of the differences in the data there. But, you know, the Identity Graph is obviously a big part of what you all do. But how do you think about maybe, you know, ROI or use of that proprietary information and data? Because some customers can purchase that from other places and kinda bring it in in like a third-party nature.
Yeah. I think it's kind of four core pillars where it really does start with identity. So as Chris mentioned, having our own proprietary authenticated deterministic identity graph, that really sets the foundation of all the intelligence that we can glean of individuals. We reach and those 245 million profiles and 525 million globally, we enrich with more than 5,000 attributes and signals, both data at rest as well as data in motion signals. So we can deeply understand who these individuals are. And as Chris mentioned, we have our owned omnichannel capability. So we know where to reach them and in what moment. Because our identity graph is deterministic, we can do that one-to-one measurement. In an AI-first environment, those are core elements from identity to intelligence to activation to measurement is core and what makes our AI particularly accurate as well as adaptive and accountable as well.
Okay. So we're gonna talk about my favorite part of the marketing space this year is, as you know, as I'm sure you both know, I'm enamored with the space and how you, the vendors like Zeta are infusing some of the AI technologies out there. The company introduced Athena at its fall customer conference, the super intelligent agent that orchestrates data decisioning and execution across the enterprise. But I guess from a high level, how does Athena or how will it help your customers?
Yeah. It definitely starts with efficiencies that we can bring to customers. So, one thing that we're able to do is we look for those really high-tech workflow moments that we can create more efficiencies and effectiveness. So as simple as, leveraging our simulator where a marketer can upload their media brief, and then within seconds they'll get AI-recommended audiences, channels, flighting dates, and also predict what that outcome looks like. But then you can also pair that with our simulator, which basically looks at, yes, this was in your media brief, but is these the most optimized channels in which you want to be able to engage? And then we've even created something on the data cloud side called Audience Cards where anyone that's seen a demo, there's a really robust amount of information that comes in our Customer Pulse. We synthesize down to an executive-level summary that has high-impact use cases that very simply be able to surface the types of intelligence on different audience segments. So now we are taking hours and hours of work. And imagine just with one specific, like, task that takes hours of time, we're reducing that down to minutes. And so you can imagine the initial efficiencies and effectiveness that we're creating with it.
In fact, Scott, Winnie mentioned the demo as a company, one of the calling cards of how we engage with you as investors is we don't just want you to have to hear things from us. We want you to be able to see, touch, feel it. On Thursday, this week, we have a product and data demo we do virtually. We do these two to four times a quarter. This will be the last one before we go quiet, where we do a live Athena demo. So if you're, you know, reach out to me directly after this if you're interested, but just know that that's out there if you wanna experience it for yourself.
It'll be on my calendar.
[crosstalk]That's for sure.
So, but so I think that's really interesting, taking high-touch workflow hours and hours, could be days or weeks sometimes, you know, boiling it down to minutes or maybe hours in that week-long timeframe. But I know you have some customers out there in beta today. What's the ROI kinda look like? What are you hearing from customers on, you know, are they seeing that exact type of benefit or has there maybe been a different scale or range there?
Yeah. I think we actually had a, a quote from one of our clients, TKO, that talks about how much a reduced manual time they are spending in all of this media planning, all of these audience creations and buildings, that they are now reducing down to these very few minutes. And I think there's a couple of things that are particularly unique about Athena. One, it starts with what you asked about with, like, what differentiates our data, right? So all of Athena is leveraging our Data Cloud, our proprietary Identity Graph and signals using our contextual intelligence. On top of that, Athena is not only just explaining to you what you're seeing, so not just telling you, oh, here's the metrics that you're looking at, but taking that interpretive layer of what is actually happening, what are the recommendations that we're making?
So whether it's reinvesting certain dollars in your budgets here or there, or optimizing against certain channels, or even making hypotheses around what does this non-intuitive signal actually relate back to the brand that creates completely net new opportunities. And the third thing that I think is particularly powerful is that the continuity in which, and hopefully you guys will be able to see this demo, and some of you guys are meeting us today have seen some of it already, is that continuity from moving from one job to the next. So a customer is able to glean intelligence through Athena to surface some kind of nugget of information. You can then build an audience coming from that intelligence. You can then launch a campaign against the audience that you wanna target. You can then get your performance reporting. You can optimize, and you can also iterate upon that all within one flow where you don't need to re-enter information. You don't need to move from tool to tool, and that continuity is really critical and what makes that AI particularly powerful because that context persists and it was used and reused across all of those jobs and all of those moments over time.
So lots of value. Last time I checked, if you're saving your customers hours or weeks consistently, you probably should be able to, you know, price and monetize the solution. It's early. GA is not for a couple more months. How do you think about the monetizing, you know, what the value of Athena brings?
Yeah. Currently, there is not a distinct SKU for Athena. And by the way, there wasn't for Zoe, which was the Zeta Opportunity Engine that preceded Athena. Athena's design point today is to take the seams out of the workload, to remove friction so that the customer can utilize more of the platform. Our number one path to ARPU expansion is use case adoption. So when a customer is using one or more of our, I should say two or more of our use cases, acquire, grow, or retain, the revenue per customer is called three to five times greater than when they're just using one.
So what Athena was intended to do is not only drive all channels across the platform, which is where we've built a very strong sales motion and have had one for years, but to now get into that next frontier and frankly wallet share unlock, which is how do I go from customer retention to customer growth to customer acquisition in a totally seamless way. And when you see the Athena demo in every screen presented to the customer, not only are they seeing, here's who I could better reach in my existing customer set known to me in my four walls, but here are the prospects that are in market right now, whether it's for my brand or a competitor's brand that I should also be engaging with, with the exact same strategy. And that's a capability only Zeta can offer to its customers. It's pretty intuitive as to why that would be important.
And you guys have shown a lot of success expanding. So, any sort of acceleration to that or removing that friction will be, you know, super interesting to track. Last week the company had a press release, you know, some incremental details on the OpenAI partnership. You announced it on the last quarter call. So.
Yep.
You know, from high level, not new. But what are some of the nuances from that press release that, you know, folks here should consider in terms of how that partnership might benefit you?
Yeah. I think there are, so first off, with any partnership to go from something to something much bigger, it takes a step one. This is a step one of what we anticipate to be many steps. Second off, I think it is a very strong testament to the capabilities of Zeta's platform that OpenAI and obviously, you know, we're obviously hugely impressed with OpenAI's capabilities to partner with each other. For us, the relationship began with talking at a strategic level with their chief strategy officer.
It then quickly led to, let's look at each other's products and capabilities, which then led to Zeta embedding their conversational tool, the actual spoken language conversational tool into Athena, which has now led to, and you saw this in the press release, their chief commercial officer getting to know Zeta much better from a joint go-to-market perspective. So I think that's an important element as well that you, and that in my experience comes from the most healthy of partnerships. It starts with a relationship building, it goes into technology, and then it goes into go-to-market. Doesn't leapfrog any of those steps, and then third, Winnie mentioned it. This was the first time we've been able to, whether it's for our own reasons, or the customers, where we've had a customer be willing to put their name publicly out there, as a testimonial to the platform I n this case, their early adoption. They're an early adopter. TKO, which is the UFC and WWE now, conglomerate use of Athena.
Again, super interesting to track. That's why I kinda really like the spaces here in particular.
Yep.
Let's move to a recent acquisition of yours, LiveIntent. Let's start on that side, right? I know it's an area you're still redefining. You know, how should, you know, I guess investors think about the long-term role of that within the platform? Seems like this last year in general was pretty positive on that, but you did have a couple changes at the end there.
Yeah. LiveIntent brought to us a new channel. So that's our Publisher Cloud. If any of you are subscribers to the New York Times and maybe you get a recipe of the day, LiveIntent is powering the largest digital publishers of newsletters that hit your inbox globally. Eight out of the 10 largest publishers globally, from Uber to Groupon to you name it, Washington Post, New York Times, Washington Post, are using LiveIntent to power those interactions to serve those targeted ads. Zeta now coming in has been able to add to that value, which is, as a brand, if you're advertising in it inside one of those digital newsletters, you were only paying when any of us opened it. But most, for the most part, we were all seeing the same banner ad at the top.
Whether it was the recipe of the day, we might all see kind of a, you know, Ooni, you know, pizza oven. Today, through Zeta's Data Cloud that's now been integrated in all of those digital newsletters that are hitting all of our inboxes every day, content at the top, the banner, the advertisers totally customized to what you've shown interest and intent for, not just through your past digital email interactions, but what you've searched on, where you've recently visited, even actual SKUs you purchased recently. So it's informing a much higher return on investment channel now through our publisher channel.
Sticking on the acquisition theme, let's touch on your recent acquisition of Marigold.
Yep.
You know, from the fall here, just recently closed at the end of '23, end of December. You all are really excited about how the company, you know, how Zeta can cross-sell, you know, items from the existing Zeta platform into the Marigold customer base. I, I guess, but what can happen on the reverse of that? What from the Marigold product set is interesting to you that you can take to, you know, the Zeta customer base? 'Cause there's a fair amount of overlap in what I'd say core kind of marketing automation.
Yeah. This is the first time from an M&A perspective we acquired a competitor. So if you look at the Forrester Wave, which does a really nice comprehensive view of marketing software automation where, you know, we have been and we moved even further up into the right in the most recent wave, whereas our competitors have been kind of steadily moving backwards. But Marigold would be found on that wave. They're like a fifth, sixth place type vendor. This was the first time that we haven't, that we've gone after a competitor and looked to consolidate around a, you know, our platform. From a Marigold perspective, what's incremental in their product portfolio that we did not have before is a loyalty offering, which goes very, very nicely into our Data Cloud, right?
When you have D ata cloud the size of ours, you can append that Data Cloud to a customer's data, you can create some very interesting loyalty use cases. But the bigger value unlock is moving Marigold customers over time to Zeta's best of breed platform. Remember, Marigold is only serving customer retention as a use case. The bigger unlock there is the 30 to 50 large enterprises that they're working with today. These are the Starbucks of the world, the Yum! Brands, the Citibank, the American Airlines, right in our sweet spot of customer to begin to sell them growth use cases and customer acquisition use cases. Dollars they're spending anyway. And what we've seen from other patterns within our enterprise customers, that is the natural progression of use case adoption. The hardest, if you will, use case to close initially is customer retention. They typically come from RFPs, whereas the others, you can go through the sales process without an RFP, and we've proven to be able to do that quite effectively.
Okay. So along with the acquisition, you all guided to at least $190 million worth of Marigold revenue.
Yep.
This year in calendar 2026, fiscal 2026. How does that compare to Marigold's performance in 2025? And what are the key factors investors should consider when thinking about this guidance, like, I don't know, seasonality of revenues, et cetera, going into the year?
So we will publish as part of our guidance, what you should expect from the at least $190 million, which we guided 2026 Marigold standalone revenues to. We'll give you the quarterly breakout of that, and we'll continue to report on its performance against that quarterly breakout. But I think there's a couple of important elements and why we added the at least. So first off, you gotta learn from every experience. We are being conservative. That's why it has the at least behind it. What we've come to know through the diligence of the acquisition and the early integration process are a couple of dynamics that we allowed for. This business was not growing, whereas Zeta's business has been consistently growing well north of 20%. This was not a growing business. They didn't have the platform. They had some customer attrition.
Large customers that when we looked in due diligence that they were about to lose, we were winning. A very large sportswear company, others that we knew we had to allow for some attrition. There were also customers using their portfolio. The way that we came to acquire this business is it was originally presented to Zeta. This wasn't a process as would you like to buy the full Marigold portfolio, which was running a separate marketing platform for small, medium-sized businesses and a separate marketing platform for enterprises. We were not interested in the small, medium business platform. We're focused on large enterprises. So we said no initially. They came back and asked if we would be willing to carve out the enterprise piece, which we said yes, and obviously it progressed to a closed acquisition from there.
What we came to find is that there were small to mid-sized customers on the enterprise platform, not a good fit that we are going to let roll off. And there were other products within their portfolio that don't make sense for us to continue to support. They don't have scale, and we're not doing it today. So when I talk about at least 190, all of that we've built into our assumption. Now, if any one of those turns out to be better, that's upside. But I wanna make that clear, and I appreciate the question being asked around like why that 190 was important.
Okay, so we'll see all that. This is closure on the fourth quarter call. I think it'll be super interesting.
Yep.
So, okay. Now I know you and David have discussed how the acquisition will not negatively impact your expected kind of near-term organic growth rates.
Right.
We'll get the first year out of the way thinking about 2027 to 2028. And I know you're not guiding to that, but you're, you know, your intermediate term goal and even your implied 30/30 goal kind of hovers around this 20% organic growth profile. But how do you, you guys are really confident that you're gonna be able to take this customer base that you said is not growing and be able to grow those revenues in kind of in line-ish or better, right, around that growth rate?
Yeah.
Why the confidence level on that? Because I think a lot of us in this room have probably seen acquisitions like this that's kind of really difficult to take something that's standing still and get it to run in a short timeframe.
Yeah. You know, it's the hard part of selling they did already. So if you think about it, it would've taken us three to five years to acquire the 50 plus large enterprise customers that they have installed today. Just a fact of life. A lot of these come through the RFP process. The belief in why we can cross-sell is through the patterns that we've seen unfold on our existing customer set who started in retention and have gone to grow and acquire. That is the faster path to use case adoption. It is a slower path when we start in customer acquisition and we have to work the other way.
That's because when you start with data at its core, whether it's the customer's data or the customer's data's merged with our data, it unlocks very valuable insights almost out of the gate around here's how you can further grow wallet share with customer A or here's customer Z that's out there that you don't even know about. We can unlock data insights faster when we start with data around customer growth and customer acquisition use cases. As I mentioned earlier, when a customer uses more than one use case with Zeta, their average revenue of spend is three to five times greater. It's the biggest unlock we have, frankly, right now on the wallet share opportunity, which we have. Our customers consistently spend $100 billion a year in marketing. We're like 1.5% of that spend.
Okay. Outside of Athena, it's probably the number one question I get is trying to, you know, understand that, right? Different dynamic. All right. Let's talk about kind of recent results in some of your sales strategies. The company added its highest number of million-dollar-plus, you know, net new scale customers, you know, since the first quarter in 2024, in the last quarter in Q3. I guess what's resonating best with these large customers to continue expanding and moving into that? Is that purely, you know, just within this use case expansion, or is it, I don't know, something new? You know, help us understand that.
Yeah, sure. Core is definitely the use case and the channel expansion, but I'll also say the timeliness and the adaptability of our intelligence is particularly powerful. And I think maybe I'll give you guys three examples from client examples. One was from an advocacy meeting I had right before the holidays, and two other ones are meetings that I'm having tomorrow to actually pitch an AG platform partnership. So one, on the advocacy side, there's a lot of things happening in the macro environment, right? So for this meeting, we wanted to showcase the level of intelligence that we can provide at a very localized level. So there was a Georgia special election in 2025, and there was much higher turnout in that special election than the last one in 2021. So we wanted to understand what were those shifts.
So, outside of people moving into Georgia, what was that shift that was creating that turnout? What we were able to identify is one, we could identify those voters from 2021 to 2025, those special election voters. And then we looked at their insights and intelligence on them, and that we found that these are actually military members who care deeply about immigration. So, one, timely nature of the things that are happening in the macro environment that we're able to glean intelligence from and help that particular client get in front of and influence and know the issues that matter to them. The other example is an agency platform partnership meeting that I'm having tomorrow. Two very different brands that they want us to touch on.
One is on the. It's a grocery retailer that is very localized that is really trying to drive higher transactions and higher basket size. So one, getting more people to buy from their stores, and then two, get them to buy more. In the lack of them having that information, we actually have data on our side on how much people are spending as well as what's in their basket for thousands of retailers through new data sets that we've brought in. So we're actually able to benchmark what the baseline looks like today for that particular brand, compare it to competitors in those same markets so that we can drive strategies and be able to tell them, here's how we're gonna grow that transaction and that average basket size. The other type of client is actually an EDU client.
So very different, very different types of clients that they have. And this EDU client is trying to drive more traditional. That's like more like the 18 to 21 that are kind of continuing their education that didn't finish up their college degree. And then we're also looking for non-traditional. So people that wanna continue their education a little bit older, maybe a lot of other things going on in their particular lifestyles. One of the core challenges that they're having is that they get great amounts of impressions as well as people that apply. The challenge that they're having is people will attrition off of actually enrolling into that school. We've actually done work previously where we look at what we've called like aged leads. So there was a client of ours, we took leads that they had from 2022.
We ran it against our database and saw that they had about 25% of those leads that didn't end up enrolling were still interested in EDU. So what that told us is that in that moment in 2022, it wasn't the right moment, whether it was a financial situation or they're growing families and it was just not the right moment for them then, they still have interest and intent. Those are leads that client has already paid for and invested in that we could help them recapture. So very different use cases, but all the things that are consistent is to leverage our data in very different adaptive ways and with really real-time types of intelligence for them.
You know, it's interesting, just from a pure math perspective, back in 2020, when we were preparing to go public in 2021, we created these cohorts of a 100,000 to a million and a million plus, the super scaled customer being the million plus, which we have called 180, as of the end of last quarter, and you talked about its growth. It's been so interesting to see how our business has evolved since then in terms of its scale to where now those million plus customers are like approaching 90% of our total revenue. So they've almost become yesterday's 100,000 to a million category, whereas the super scaled customer of tomorrow is probably a $10 million customer, right? So, it's just interesting to see how that has unfolded over time.
We'll wait for those disclosures to come.
[crosstalk]Right.
That's $1 million customers. I'm looking forward to that. Off-script question: when you just talked about in that first customer example working with agencies.
Mm-hmm.
When I was at the NRF conference yesterday, spent a lot of time at the different marketing, you know, kind of software vendors that were there. And one of the comments that I got from someone is a lot of these new AI technologies that you all are bringing and others, it can fundamentally shift how brands work with agencies and the software vendor in this kind of equation. A lot of the agencies do a lot of this manual work. It might shift a little bit of kind of the reliance or the importance of that ecosystem more to a software vendor like Zeta than the marketing ad agencies. How do you think about something like that? I mean, that could likely even put you in a premier spot, you know, the company as well.
Yeah, absolutely. So we are able to reduce a lot of that manual work that then unlocks the bandwidth of those individuals to focus on more strategic ways and how that agency can actually drive value for those brands. So instead of being the one that has to take the media plan, plan out all of the flighting and QAing and all of that variable manual labor, they can now focus on more strategic opportunities, leveraging our intelligence so that they create bigger and secure relationships with those end clients as well.
Last question for me, 'cause I already saw Corey's hand go up and back. As on the financial side, 'cause of course we have the CFO here, your 28 targets and kind of 30 targets all imply, as I mentioned earlier, kind of around 20% organic growth, you know, through that period. But you also talk about just even a margins of 30% and 70% Free Cash Flow conversion margins there. Is that profiles, you know, super interesting, but the level of profitability relative to that growth rate's not something that we see in our space, especially considering that you all are still growing about twice as fast as the average public software company today is. How do you drive that level of profitability in your model and still grow 20%? 'Cause that would be a little bit of an anomaly on the positive side of it.
It's interesting. I talked about this at Investor Day, and I continue to be a bit stumped as to why there's this belief that somehow there's a trade-off between growth and profitability. I think if you, there shouldn't be, and there isn't at Zeta, to be very clear. We every year, as part of our normal process of looking at the next year and the next year and next year ahead, we take our entire people population across the company and we segment them based upon their duties and responsibilities in terms of how close they are to creating code, which creates value, to how close they are to actually carrying a bag and closing a quota, which creates value. And then everybody in between, I wouldn't wanna be an in-between person because that is where value is frankly not created.
So we are constantly looking at the redistribution of resources, the redistribution of people. How do we create these barbells in the company that are really big at the end of creating code, really big at the end of selling and marketing, but in the middle we're ultra lean? That process, we're never going to perfect, but that's how we make the inroads we make on every single year, not only growing over 20% for six straight years, but also expanding Free Cash Flow margins over that six-year period. And it's that continued and rigorous redistribution where value is created.
And then, by the way, making sure that when we add somebody in coding, when we add somebody in quota carrying, they're being productive. That allows us to keep this cadence like we have to where I don't have to be the bad guy in the room as a CFO and say no to investments from R&D and no to investments from sales. They can almost have an, you know, open wallet, if you will, because A, it's a little bit hard to hire in both of those areas, but B, because we are being so relentless in getting rid of that middle layer.
All right. With that, we have a few minutes left. Happy to take audience Q and A. Corey, I guess you're first. Let's go for it.
Thanks for presenting today. Can you expand some more on this OpenAI relationship? So you said, if I caught it all, they took a look at your tech, you have a joint go-to-market program or perspective, but just expand, like, do they use your technology today in the go-to-market? Are there salespeople reselling your technology? What's, how deep do those two things go?
Yep, so just to reiterate the question for the webcast, for those that are listening, the question was on expanding on the OpenAI relationship in general.
Yeah. Thanks, Corey. Zeta is using OpenAI's technology today. It is not the other way yet. The reason why the go-to-market is important is because I think that is the next phase in the opportunity in the partnership, as both organizations are obviously have stated their intent on being more prominent in the enterprise space. This is a really interesting way for both companies to get to know each other's capabilities and then augment down the road an enterprise go-to-market motion. That is not today, but as I said in the beginning, I think the relationship announcement is a very important first step of many ahead that can lead to a bigger set of mutual financial interests. But there is mutual financial interest already today.
When you just talked about the data set being immediately in that, it's a very interesting thing. There's a time value that disappears very quickly of those 2.5 million profiles or individual. How do you keep that up? And are there blockages? There's all these privacy regulations. How are you able to have in real time these 2.5 million individuals and their buying patterns?
Yeah.
That's that.
I'm gonna take that.
Yes.
Yeah.[crosstalk] Continue in the future, but regulatory.
Yep. Absolutely.
The question was on keeping those 245 million profiles fresh.
Yep. Yeah. So we are actually breaking and creating new linkages all the time. So the growth of how many people we'll have in our graph on the U.S. side, limited in growth there 'cause we almost got full coverage. But the identifiers and where we can reach them and the intelligence that we glean, that's what we're changing in real time all the time. So the authentication that I talked about, the value of that is that when you log in or you are on LiveIntent and you click on that email, our digital identifiers firing along with the email that you were just sent or through our like network where you actually log into accounts.
That deterministic connection is broken and created all the time so that we are actually reaching that person in the digital forms that they're interested in and also being able to leverage that to understand the interest and intent of those individuals. That's in real time refreshing along with a lot of the other sources that help us understand what's the movements and shifts and behaviors of those individuals. To the point about like compliance and rules and regulations, since it is our proprietary Identity Graph, it creates a lot of opportunities for us. If anything were to change, we can make that change very quickly on our side to make those adaptations. I will also say on top of, in the U.S., on the email side specifically, it's opt out, but we actually have set created our database. I've actually been at the company like 16 years, but we actually have created our database so that you have to opt into our email communication. So we are basically future-proofing ahead of it, where we see if there's any compliance changes, it'll move more toward CPRA and CCPA.
Remember, there's a lot about you and all of us that really doesn't change. I mean, our demographic data, our firmographic data, I think you're speaking of is the data in motion. It's what we're reading about, physical locations we're visiting, what we're purchasing. That is what's actively changing in the graph. And that's what we are uniquely capable of creating a connection point between, here's what this person's searching on and here's what this person has purchased recently and connecting them that they are Chris Greiner.
That we probably have time for one more question if there's another one from the audience. All right. With that, I'll give everyone about two minutes left to fight the elevators. Thank you so much for joining us.
Thank you, Scott.