ZoomInfo Technologies Inc. (GTM) Earnings Call Transcript & Summary

Good morning, everyone. My name is Brian Peterson. I'm the Application Software Analyst here at Raymond James. Very happy to have ZoomInfo with us today, Cameron Hyzer, the CFO; Jerry Sisitsky, Head of Investor Relations. This is a pretty open format. We're going to do a fireside chat. So if you guys raise your hand, any questions, happy to make this interactive. But Cameron, maybe to kick things off, maybe spend a minute or two on ZoomInfo and how you guys are really innovating in the market.

Sure. So we provide a platform to go-to-market teams, think of sales teams, marketing teams that provides data and software to really help them sell more effectively and efficiently. We provide data about the companies that they're selling to, the people that work at those companies and then signals about those companies that help them think about whether a company might be in market or not. So it's an exciting business. We're $1.2 [ billion ], $1.3 [ billion ] in revenue. So definitely the largest kind of player in our space. And the interesting thing that we announced earlier in February is that we're rolling out our Copilot platform. So if you think about the ZoomInfo platform, historically, it was very much a pull system. You logged in, you can set filters or searches to find companies of the people that work at those companies, automate some of the workflows around signals that were coming in. But you really need to be a pretty sophisticated user to really get the full value out of the system, if you think about billions of kind of data points and signals, hundreds of millions of companies and hundreds of million people that work at those companies. And so our AI platform will essentially create a profile for you as a company, what's your value proposition, who do you sell for, creates about -- a profile about you specifically as a seller. And then against all of those companies that are out there in the signals, it connects all the dots that are in the system that can then push to you what are the most important things for you to be working on, what should you prioritize, where are the places that you're going to be most effective and gives you the real insight into why this is the most important, which can help you create a [ call scripts ], bullet points on why you should reach out to someone, what are the most important things that are going to resonate with them, where you can go with that or e-mail or whatever else. So really helping folks prioritize their time and go after the best opportunities that they can.

And maybe, just to kick things off, on the differentiation and the accuracy and how you kind of get to the data that's maybe better than your competitors, so spend a couple of minutes on the moat that you have and how you get to some of that data.

Yes, totally. So we've always prided ourselves and really focused on generating the highest-quality data that we can for folks. When you think about the different types of data, whether that's company data, contact or people that work at those companies or signals, we're aggregating data from a multitude of sources. And many of those are proprietary sources. So if you think about the contact data in particular, we're bringing in data from our contributory network. That's a freemium offering, where people get limited access to ZoomInfo in exchange for the contact information in their e-mail systems. We also have a contributory network from our customers. We're there providing information that helps us triangulate when people have moved jobs or started at new companies, et cetera. . And so that contributory data really creates an opportunity for us to drive quality that no one else can. And it's an interesting problem because in order to drive quality, you need a really robust contributory network. In order to have a really robust contributory network, you need to be providing quality to those customers or freemium users. So that chicken-and-egg problem helps us to really drive that. And then certainly, off of that data as well as all the company data that we're aggregating those signals that we're providing are really what's important to folks and being able to provide timely signals of when did someone just hire a new controller, as an example, is a great time for certain types of vendors to reach out to that particular company. Having those signals that we're able to drive quality against is really important. And so a, the sources of data, in particular, the proprietary sources, are really helpful. And then we've developed a machine learning engine in the back -- background that's basically taking all of the evidence points that we get, and we call it an evidence-based algorithm, where it's looking at the quality of the source that that's coming from, the frequency that we're seeing something, the recency that we see something in order to really drive that quality at scale. And then we're backing that up with a team of researchers that are constantly sampling the database and providing ground truth back to our data scientists in order to continue to tune that system as well. So overall, we probably spend over $50 million a year on the quality of the data. Very little of that is actually purchasing data. It's much more about maintaining that system, all the infrastructure, all the research behind it and the data scientists that we're using to drive that.

And so when the customers are using that, right, like obviously, this is much more accurate data, like what do they typically see in terms of like an ROI? Or like what are the use cases that would -- you're coming in and you're ramping up? Like what are the customers able to do?

Yes. So we recently put out a customer impact survey. And we have customers that will tell us that they're able to sell 20%, 30% more, based on having higher quality that they can focus on. It obviously reduces a lot of time that they spend on road tasks, whether that's researching companies or just trying to land with the right person. So it's a real value to those users. And if you think about it, our pricing model is such that there's a base fee and then we scale up with users, but our typical user might be spending $2,000 or $3,000 on the system per year. Your average enterprise sales guy probably has a $0.5 million to $1 million quota. So even just being 1% better is -- fully pays for the system. And frankly, it does mean that having higher-quality data is really important because if you went and found lower-quality data, you might run into more blind corners or it'll not be as useful. If you're only getting 5% or 10% better out of something that's cheaper, you're losing out on a ton of value that you could have had with the ZoomInfo system, where you might have double the improvement or double the lift that you'd get from something else.

So it might -- always -- it's interesting because your go-to-market motion is so sophisticated, but like what would you say in terms of kind of drinking your own Kool-Aid and like using your own platform for your own go-to-market motion? Like, what have you guys seen there?

Yes. I mean we get a ton of value out of it, and we're probably the most sophisticated users of the ZoomInfo platform. But it is a big driver of why we are really efficient. We have a super-high LTV to CAC, and it really helps drive us. So even if you just take one example, for instance, we probably get a little more than half of our business on the new side from inbound people that come to our website. If you come to our website, we'll have someone call you back, oftentimes, in 30 to 90 seconds. They'll call you back, they'll know who you are, where you work. It will be the -- we'll automatically enrich all of your data in real-time for that person so that we're actually choosing the best SCR to convert you to a demo. And then they'll have the calendar up of the best account executives to be able to give you that demo that are most likely to convert you to a lead. And we're doing that all in the background in real-time by taking -- if you just put your e-mail address in, we know who you are, we know what company is, we know where you are. We know all of these things that we're able to effectively pick the right person to reach out to you, and that helps drive better prioritization as well as better close rates.

And you guys have developed some advanced functionality, and some of that's been organic, and some of that's through M&A. Like what are you doing in terms of the product investments? And where are you seeing the most interest in terms of that advanced functionality?

Yes. So advanced functionality continues to grow. It's roughly 1/3 of our total revenue or ARR at this point. And there are some really interesting pieces of that, particularly on the operations OS side. We've seen a lot of traction of late as well as the marketing OS. And so operations OS is really providing data cubes to customers so that they can ingest bigger parts of the data into -- maybe they're trying to automate a workflow or they're trying to enrich or cleanse their CRM system. Those operations teams are really data thirsty. And then there are tools wrapped around that, that helps them route data leads. It helps cleanse, it helps pull other data pieces in as well. So that's been a place where we've seen a lot of traction. The marketing OS is really exciting as well, where we're building audiences for B2B marketing teams to really find where can they be more surgical with their marketing spend, whether that's on social or ads or e-mail campaigns or whatever else. And obviously, having really high-quality data about your addressable market and where you go is super helpful for them as well.

And obviously, AI, a huge topic in your conversation, you mentioned in the opener, but where are you guys investing in there? And how do you think about that long-term monetization angle for ZoomInfo?

Yes. So we are significantly investing this year. It's probably a few hundred basis points of investment between the teams that are developing it and the infrastructure to train the models and make things work. So it's an exciting aspect for us and the beta users. I think we have tens of thousands of beta users at this point that are also helping to train the models, but they're really excited about what it can potentially provide to them. . And so that is really where we're focusing on getting people to that next level of the platform. It should help to improve engagement even more. If you think about a system that's just showing up, giving you what are the best things to focus on today, like that's an easy way for salespeople to really move the ball forward in everything that they're doing. And certainly, we're currently testing pricing and packaging options. So I think that we're not quite ready to put out there what we think potential price uplift would be. But think that there's certainly the opportunity to monetize that through a price uplift, and we'll work through with our customers to migrate folks to that over the next 2 to 3 years.

And what are you seeing in the current demand environment? I know people tend to focus on kind of net new versus the existing customer base, but we'd love to get an update on what you guys are seeing there in early 2024.

Yes. So we've been working through. And I think as many people know, more significant part of our customer base were software and technology companies than a lot of other folks, and so that's been a market that's been really hit hard over the past 12 to 18 months. I think of kind of peak negativity in terms of layoffs as having occurred kind of the end of Q1 of 2023. So we're just now lapping that time frame when a lot of our customers were reducing staff sizes. And as a result, the renewals that we've gone through this year over the past 3 or 4 quarters have been challenging. I think Q1, particularly in the technology space, we're going to continue to see some downsell pressure with respect to that. But overall, it's still an uncertain world out there for a lot of sales teams. And so we've had the downsell pressure from primarily technology, but upsells are harder to come by when people aren't leaning in or investing or knowing where they're going. So I think there's like some level of stability kind of coming in on the downsell side, but we still don't see necessarily the upsell investment yet. Certainly, we view the AI platform is kind of helping to be a catalyst for that. we're going to roll it out for general availability towards the middle of the year. So it may not have a huge impact this year, but certainly will provide a foundation for us to continue to drive growth with our customers around that. And then ideally, as the environment stabilizes a little or people start thinking about investing in growth anymore and obviously, when you're coming out of a cycle that tends to be the case, that will be an attractive setup for us once we start to see that.

So can you look at -- if you look at the business maybe by customer size, kind of enterprise, mid-market and SMB, however you want to split it, what are you seeing in terms of demand there? And like I'm curious, how pricing environment may look as you kind of look at those 3 cohorts?

Yes. So in the enterprise, I think particularly if you look at the upper end of enterprise, that's continued to be pretty stable. We do see a net upsell for those customers. And obviously, it's very rare to churn off enterprise customers. So at the high end of the market, particularly where you have people investing in their operations teams, operations OS looking to build AI models and pump high-quality data into those; like that's a positive. We don't see a ton of [ seat ] expansion to the extent that we used to, but that obviously should come over time. . Lower end of enterprise and as you get into mid-market, that's where we've seen a lot of the downsell pressure. You have a lot of kind of technology companies and formerly high-growth companies in that boat. I think the kind of thing that we look at that is probably a little bit of a positive as people that downsold in their prior transaction with us, they're actually downselling less. They're starting to see more stability as we got through Q4, that was not true earlier in the year. So I think that's a little bit of a positive. And certainly, there's lots of opportunity once we reach to that foundation level to then grow with those customers as they come back. And on the small business side, I'd say that there's a little bit more churn than we've seen in the past, just based on more companies shutting down. But our overall churn levels haven't increased that much. It increased a point or two in the macroeconomic environment that we're seeing. So again, I think the fact that our customers are staying with us, continuing to invest naturally, downshifting how much they can invest, particularly if their headcount is down or they're taking out seats, and then creating that opportunity to grow back with them in the future is important.

So I know there's been a lot of like early investors kind of in the technology vertical. But if you kind of think outside of tech, what has the adoption been there? And what is the opportunity to kind of modernize how some of these other industries go to market?

Yes. I think there's a ton of opportunity. At this point, our outside of technology business is over half the business at this point. So -- and there's -- it's a much bigger part of the economy than half. So our penetration rates are much lower in terms of where we go. The really interesting thing for us is that, that is a place where the inertia around sales teams has been to just keep doing what they've been doing for really decades. When you think about someone's sales motion, like they haven't changed that much if you go back to the [ '50s ] and [ '60s ], and people would gather information from potential clients over at 3 [ martini ] lunch, maybe that's more football games and dinners now. But in reality, that's a big part of what a lot of people do. And so shifting that mindset to using high-quality data and signals to enhance that motion, help prioritize where you should spend your time and really drive value for those salespeople is something that we focus on. And really, when you -- when someone is interested in that, when there's changing over leadership, maybe it's a small business where a father has passed the business onto his daughter, those sort of opportunities are really right for someone -- they're thinking about where they can change their business. And it's part of the reason why our sales cycles are really short, particularly on the new side. Often less than 30 days that once they see the system and they realize the most often that quote that you'll hear, we record a lot of our sales calls and transcribe them, one of the most often quote is, "Wow, I never knew something like this existed." So when you're able to deliver that value, you convert them into a customer very quickly and then help them sophisticate over time to really get that value out of the system.

I know we have a question from the audience.

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I'll just repeat for the webcast, maybe horizontal versus vertical and how do you think about certain areas where there's expertise needed versus like the broader horizontal opportunity?

Yes. So I think that in reality, having a horizontal platform has served us really well. There are always niches of data that people are going to want to avail themselves. You mentioned definitive health care, certainly, if you want to know how many knee surgeries are done in Cleveland in a particular year by different hospitals, like that's not something that we get to. And so one of the things that we're developing and is going to be a big part of the Copilot is actually the ability for -- to import other data in. We're actually starting with more intent-based kind of signals. So I think we've -- if you think about -- there are websites out there that have intent specific to a particular thing. You think about like G2 as an example. G2, they have reviews of different software platforms and other things, and they actually generate a fair amount of intent if people are going looking at different things. Being able to actually integrate that into the platform as another intent signal that we'd be able to offer is something that we're excited about, and I think customers are along the same line, you could import definitive information in. So you could -- we have really great information on all the administrators at the Mayo Clinic, but if you want to figure out more detail, associate that with the same company, I think that's a really exciting opportunity because ultimately, we're always looking to add more data. But on the like really deep in a particular vertical, no matter what it is, whether it's health care or fleet management or financial services, like we're not going to cover everything. So being able to bring in more and more of those niche providers is something we're excited about.

I think what was really interesting about the fourth quarter call, like you came up on the customers that you brought back that maybe that left and they're coming back. So like maybe talk about the value and kind of what went on from them to kind of say, "Hey, we're going off and then we're coming back." I'd love some examples there.

Yes. I mean I think that in a tougher economic environment, particularly in like smaller end of the spectrum, there's a little bit more impetus for someone to say, "Hey, can I try something cheaper and get similar value out of it?" I think the kind of consistent course that we get from customers that are coming back is that, "Yes, it was cheaper, but it wasn't anywhere near as good." And frankly, when it's not as good, you're going to send your salespeople down like dark alleyways, they're going to waste their time dealing with it, figuring it out. Frankly, it becomes a becomes an issue of just morale, if you give them a bunch of bad things to chase, if you -- like they can't get to the people on the platform, like it's frustrating for them. So not only does it waste their time and they're not able to get that value to get that same lift in terms of additional sales or what they're doing, but it's also like creates frustration for them. So I think that creates this opportunity where, I think, again, if you go back to that example of your average salesperson is selling $0.5 million or $1 million a year of quota, 1% of that is $5,000 to $10,000, our system is less than that. So obviously, even if it's cheaper, it's only $1,000 or $2,000 cheaper. Even if you're only getting 1% less, which, by the way, the quality of anything else you'll find, its way less than like 1%. But even if you're getting 1% less, you're actually losing out on that transaction because you're saving $1,000 or $2,000 and you're missing out on $5,000 or $10,000 worth of sales. So that dynamic very much comes across, especially once you're -- if your sellers are used to using high-quality data and you go to low-quality data, there's a real issue for them.

Maybe just like looking at the financials, like big opportunity in front of you, but how do you kind of think about the long-term growth [ algo ] when you look at kind of net new versus the NRR? I know the macro has been a little challenging. But how would you impact that?

Yes. So I think of the growth algorithm as you start with, obviously, churn. So we -- 1/3 of our business is still roughly small businesses. So with that mix of customers, our gross retention, 1 minus churn is around 90%. It's down a little now, but still right in that ZIP code. And then, you have a net upsell against that. And so historically, that net upsell has been 10%, 20%, maybe even pushing 25% in different years. In '23, what we saw is there was a lot of pressure, particularly from technology companies that we actually had a net downsell. So our net retention is 87% for the year. . So our real focus is actually turning that back around. Some of that will be based on macro improvement. Some of that will be -- we've washed out a bunch of the downsell potential of people, laying people off. And even if that's just lighter than it was before, that helps. And certainly, we're looking to catalyze that with the AI platform, providing a lot more value to our customers, improving their engagement with the system and frankly, opening up the system to people who are less of a power user and just getting more value naturally out of it. So our goal would be to bring net retention back into the hundreds. And so you bring net retention back into the hundreds, there's still a ton of opportunity on the new side. In our system, we'd be able to identify by name over 700,000 businesses that sell to other businesses that we're just constantly working through. We only have 35,000-plus customers right now. So there's a lot of opportunity to continue to drive that new. So new in '23 contributed about 18% to growth. So if you think about getting net retention back into the hundreds, new contributing something in the teens on a consistent basis really puts us in a position where getting back into teens growth or maybe even 20% growth in good times is an opportunity. Obviously, that's not going to happen in the short term. We're still facing a lot of downsell pressure in Q1. And 2024, I think there's uncertainty, generally, for a lot of folks. But over time, getting to that in the long term feels like the right goal for us.

And just remind us, like the margins are pretty good, but how are you thinking about that balance of like really driving leverage or investing back into the business? Like how do you balance the growth-versus-margin debate?

Yes. I mean, certainly, this year, we're investing heavily into the [ DII ] platform. I think, over time, particularly as we're able to bring that growth back to a more normalized level; there is plenty of operating leverage in our model. And so as the growth actually starts to improve, we'll be able to take advantage of that operating leverage. I do think we'll continue to reinvest a good portion of that back into the business, but keeping margins in the 40-ish percent, on an adjusted operating basis, ZIP code, feels like a great place for us to be and enables us to really invest heavily into functionality and data quality that can really drive value for our customers.

And maybe we'll wrap it up after this. But just as you're thinking of a very strong cash flow, how are you thinking about deploying that in terms of organic or M&A or buybacks? Or how are you balancing that?

Yes. So certainly, right now, we feel that we're trading below the intrinsic value of the stock. And because we do have really strong cash flow and cash that we've accumulated over time, we've really leaned into buying back stock. We bought back $400 million worth of stock in 2023, and we're continuing to buy back stock. We just authorized another $500 million buyback authorization. So it will continue to be opportunistic. We really view running the business is all about efficiency, and that's not just efficiency in how we build software or sell software, but also how we manage the balance sheet. And so when we're trading at lower levels, we're going to be more aggressive about buying back stock. When the stock appreciates a little bit more, we'll probably continue but at less aggressive levels. And we're still thinking about M&A, but realistically, the bar is really high when I can buy back the industry leader at 15x cash flow. So we're -- a really high bar for that. And frankly, there aren't specific functionality things or other things that we feel we're missing in the platform. So we're going to evaluate everything on -- it needs to be really accretive for our customers and also needs to be really accretive for our shareholders in terms of potential M&A.

Great. I think we'll wrap it up there. Cameron, thanks for the time.

Thank you.