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

Good afternoon. My name is Brent Bracelin, co-head of technology here at Piper Sandler. Thank you all for joining us this afternoon. Really pleased to have Cameron, CFO of ZoomInfo, here with us. Cameron, welcome to Nashville, and thanks for coming.

Thank you very much.

So we're between 2 ferns. Should we start out with some jokes here or no?

That's really up to you. I'm not good with the jokes.

Well, let's not focus on that and focus a little bit about the software market and the trends that we've seen over the last couple of years. If I look at the Cloud 100, it's been tough. Valuations were high 2 years ago. They're a lot lower now. We've seen industry growth rates basically cut in half over the last 2 years. But there is some signs we're getting closer to some stabilization. There's some slight evidence of maybe we can even talk, God forbid, about accelerating growth a year from now. So let's take a step back and think about your business, the slowdown in your business. How did we get here? And what's the path forward?

Yes. So our business is obviously an interesting one because we serve such a like massive market, and we're still very lightly penetrated. But it also means that our early adopters became a very big part of our business very early. So software and technology firms were really a big part of the early adoption curve. And for -- I know many of you have heard the story of ZoomInfo. But like that was really where DiscoverOrg got its start and was focused on high-quality data. When we merged with ZoomInfo or acquired ZoomInfo in 2019, we really exploded the TAM, and we're able to serve customers outside of software. But coming into this year, software is still close to 40% of our revenue. And certainly, where you see a lot of firms that are de-prioritizing new sales and focusing on efficiency, where they have -- really to examine their operating model and think about a lot more profitability, that's been a tough road for us. We're kind of the tail end of that starting point, where a lot of companies are -- their growth rates have come in a lot. So I think that dynamic is one that we're continuing to deal with. I think we're focusing on getting through this next set of renewals. I kind of think of peak negativity for a lot of our customers as being kind of February, March of this year of 2023. So as we're kind of moving through and coming up on lapping peak negativity, I think that gives us a more solid base where we've cleared out a lot of the underbrush, potentially overbuying historically and so forth, and cleared that out where we can have a more solid foundation to grow with those customers going forward.

So as you think about the layoffs, we started to see some of the software folks, given it was 40% of the business, less now, layoffs started a year ago. You started to see those layoffs. They really picked up momentum in Q4 and then obviously into, let's say, maybe peak layoffs hitting in Q1. How long does it take for those renewals? It's a little bit of a lagged process. So you have to really kind of get through the renewal before we start to see the business stabilize?

Yes. Most of our contracts are annual contracts. We do have a pretty solid amount of 2- and 3-year contracts as well. So really lapping that set of peak negativity for our annual contracts is a big piece. This year, for whatever reason, is also a bigger year for multi-annual contracts. So we'll have a number of the 2- and 3-year contracts also renew in the third and fourth quarter of this year as well. And so between all of the annual contracts obviously lapping and then having a good reset point for those -- for a good portion of our multi-annual contracts, I think that gives us a much better spot. Obviously, there's still a small tail of contracts that will renew after that. But getting through that big bulk this year is the primary hurdle that we need to get through.

So outside this exposure to software, going through some pains now, we'll get through those renewals. So maybe a year from now, we'll be talking about a little bit of a different opportunity set. Let's take a step back though. That's kind of where we're at today. Maybe walk me through how did you become the gold standard in software? Like what was it unique to the product that you became the gold standard in software? And more importantly, can you replicate that gold standard outside of software?

The real value that we're providing to customers is really high-quality data and insights about their customers, their prospects and the triggers or signals about those companies. With those high-quality data and insights, you can really drive a better motion. And so I think that's really what kind of propelled us to be that standard for software companies. And by the way, we're still not totally penetrated into the software universe. I think there's still a lot of opportunity there. Realistically, that same dynamic is true outside of software. If you can get good quality insights about your customers and prospects, you'll be able to drive a better motion. I think one of the things that's a little different about non-software versus software is there's more inertia in non-software. I think if you think about your average software company, maybe it was founded in 2013 or 2005 or sometime in the last 20 years the Internet existed. There's a lot more tools and capabilities. And frankly, you're probably a younger company. So when you're developing your go-to-market motions, you're looking for some of the tools like ours. If you are a, I don't know, a box manufacturer in Cleveland, like you very well could have founded your company in 1953 and you're 70 years old. That means you have had some level of success. You're developing the motions that you're kind of going to market with. In the '50s and '60s and '70s, the Internet didn't exist. You came up with new and novel ways, whether it's hiring people that already had a book. Maybe you joined a country club to meet people. Maybe you're going to a particular conference or set of conferences. Like those things are all well and good and have worked for you. But when we get in front of folks, particularly when they're going through some level of change, maybe you're a family-run business and the father's handing the business over to his daughter or you're hiring a new set of salespeople or you're moving into an adjacency, like all of a sudden that inertia that you've been kind of working with historically, there's some impetus for change. And when people see our system, the common refrain is, wow, I never knew something like this existed. And it's really obvious how you're going to be able to generate more sales, justify the cost and really drive value. And that's why our sales cycles for new customers continue to be less than 30 days. They continue to...

Even outside of software?

Even outside of software, they continue to be really strong. And frankly, our non-software business, it's almost 2/3 of our business now. It's an $800 million business. I think when I was here, before, it was less than that. So it's a real software business by itself, and it continues to grow pretty solidly. If you look at our like June results, outside of software is a 20-plus percent growth rate, whereas software is obviously feeling a lot more pressure and is actually down year-over-year.

So non-software, $800 million business, but it's a little bit different. And I think about different in that like not all of those non-software companies have inside sales teams. Like do you have to kind of have an inside sales team? Or are you convincing them to build the inside sales team? Like walk me through that.

You don't need to have an inside sales team. What you need to have is a focus on growth and finding new customers oftentimes. Because while the system can help people in any number of sales kind of use cases, the really obvious sales use case is prospecting. And every business has to do some prospecting. In some businesses, it's much more of a technology thing or maybe a really big company thing. You have SDRs or you specifically carved off the prospecting motion to a set of people. In a lot of businesses, the sales guy needs to prospect and generate their own pipeline. It's actually great for us because, ultimately, that means that those salespeople need tools to help them prospect. And that's where a lot of those customers end up being is that it's a salesperson that needs to generate their own pipeline or a team of people that need to generate their own pipeline. That's a really obvious use case for us to help them.

Data system empowering sales. Any sales environment is kind of the way to think about that?

Yes. I mean, I think it's any sales where it's a business selling to another business. Obviously, our value is really on the high-quality data about businesses themselves. But that B2B economy is a really massive economy with a lot of opportunity for us.

Software, clearly, the biggest vertical you had success with, got to 40% of the mix.

It's actually a lot more than that.

It was? What was it 2 years ago? What was the peak?

2 years ago, I think it was 46%. I actually think before that, there was a point at which it was well over 50%.

50%, wow. Okay. So you've diversified the business. But as you think about maybe that success and momentum, building critical mass, becoming the gold standard in software, does the go-to-market functions need to change in these different verticals? Are you trying to say, hey, let's really build critical mass in a specific vertical and change your own go-to-market approach with a vertical focus? Or is the horizontal approach working in non-tech?

Yes. So the horizontal approach continues to work realistically in our account management team. So those are the teams that are servicing existing customers and helping them to grow. We have started to specialize folks. So -- and it's just easier, particularly when we're up market and trying to have a conversation with the C-suite or higher-level decision-makers to be able to talk financial services or to be able to talk telecom. There's just slightly different nomenclature. And frankly, going to have a lot more success if you walk into AT&T and say, yes, I was talking to T-Mobile the other day, and here's how they use the system. Same for financial services, same frankly for software. So like that's where we've started to specialize teams to verticalize them so that they're -- can have those higher-level strategic conversations in a more natural way. Realistically, on the new side for new customers, A, most like -- most of our new sales come from the non-software vertical at this point. It used to be that -- and this was as late as like Q1 of '22, software was probably 30-plus percent contribution to new sales. Now it's below 15%. So like most of our sales, new sales, are coming from non-software companies. And in that environment, we actually have more generalist sales and we're routing leads to people based on who's the best person to close a particular deal at the kind of best value for us. So that means that if you're really good at financial services, you're probably going to get more financial services-like leads. But that doesn't mean that's all we're going to feed you. If you're good at financial services and telecom, then we're going to feed you both of those. And it's all based on the history in their performance so that ultimately, our best salespeople are getting the best leads for them to convert. And it actually allows our salespeople to kind of move up and motivate them as they go through it as well.

Sounds like you're using data to drive your own sales go-to-market [ strategies ]. There's a reoccurring theme here.

That has been a longtime theme that, frankly, we do use our own system. And in my mind, that helps us generate far better sales efficiency. Even at the lower levels that we're at today, where it's been impacted by the economic environment, still one of the most efficient like sales motions that you're going to find out there. And a lot of that comes from, frankly, being able to use the system an even more aggressive way than our customers do.

Totally makes sense. So let's pivot to where some of the investor debates are right now. And that's this idea that, yes, your growth rate has been hampered by outsized exposure to software. You're addressing that. But what about competition? And I think about competition in 2 vectors. One, this was a pretty fragmented market on the data side. 5 years ago, you consolidated the market. But it's been 3, 4 years. Are there new data competitors that you're kind of watching that present existential risk to that potential recovery a year from now? One vector. And then the second vector is large language models. Does that change the ability and change the competitor that you worry about competing against you in 2 years from now?

Yes. So on the data side, yes, I don't know that I would say we consolidated the market. Obviously, we made a couple of acquisitions, but there's always been lower-quality smaller companies that are offering, in our mind, what's a lower-quality solution at a much lower price. And realistically, there's always been that kind of noise at the low end of the market. I feel like it's a merry-go-round of who's the #2 player, whether it's Seamless.AI or RocketReach or Apollo or Lusha or Cognizant. Like some level, they're like fighting among themselves and taking like from each other. But there's just always this like set of #2 players that are down there. They grow to a certain size, and then they start to fizzle out. And so that's been around forever. Realistically, we focus on our win rates at that low end of the market and where we see people coming up. Frankly, our win rates are marginally up from where they were a year or 2 ago. So that's a positive in terms of how that's running. And so I think we are -- we continue to be focused on that. We want to make sure that we're taking as much oxygen out of that low end of the market as we can. But I don't think that -- I don't think it would be realistic to assume that it's just going to -- those companies are all going to go away and never be there. Like there's always going to be some noise at that low end of the market.

It's interesting that the win rates are improving in the last year at the low end. So that's encouraging. What about the large language models? The art of what potentially could be possible if I want to think about pulling data from different things and using large language models to substitute or augment or replace the data that you're providing?

Yes. I mean I think that that's a real opportunity for us because we do provide such a vast array of data, and it's actually not always easy to get to everything that you need. So the large language models, to the extent that you're pulling data in even just from our system, are going to make the usage even better over time. And so I think we're really excited about that. Obviously, there are certain data points that you could use a large language model to generate. For instance, you pointed an LLM at a website, you could probably figure out what the -- what industry that company does, right? That's a really small part of the value that we're providing to customers. In reality, all of the proprietary data we're providing, whether that's contact information, org charts about companies, all the signals and intent that we're providing, that's really why companies are using ZoomInfo and the real value that they get around it with some of that, I'll call it, publicly available information around the edges. So I don't think that your phone number is going to be in a large language model ever. I don't think it's ever going to be able to like figure it out.

Enough people have that already.

Enough people have it.

And one thing you've seen in your [ warranty ] experience probably.

But that's not something that a large language model is like going to be able to figure out by trawling the Internet. The signals about companies and what they're researching online is not something that a large language model can figure out by trawling the Internet. The IP addresses for companies that we're using in the back end to drive our anonymous website identification or intent, like all of those proprietary data sets are things that a large language model could leverage if we provide it to them. And obviously, we're going to get paid to provide that to them so that people can drive better go-to-market motion based on those. So like that actual opportunity for us is the -- is really the biggest one in our mind, where people who are going to want to deploy these things are going to want proprietary, highly accurate and timely information in order to drive better outcomes with those. And that's the opportunity that we can frankly sell more data as a result of that.

So maybe the LLM existential threat, at least on the near-term horizon, doesn't seem like a substitute or alternative. And if that's the case, what can you do with a large language model internally to start to, I don't know, build new things? Leverage just large data set? Are there new products that you could potentially start to think about?

Certainly, we've started with using the down the middle of the fairway use case, which is summarizing transcripts that we're already helping people with. That's gotten a lot of positive feedback from our customers. We are currently working on areas that we could use natural language search to basically get to deeper parts of the system with less -- our product people like to call it cognitive load. So if you had to go and, whatever, take 25 clicks to get to a complex search and kick off a motion around that, being able to do that with natural language modeling in order to get there is like really interesting. I sometimes think about it as like people only use 10% of their brains. I think a lot of people only use 10% of the value of the software that they're using, and that's probably not that different for ZoomInfo as well. So if you can leverage an LLM to actually give people the capability to get 30%, 40%, 50%, 80% of the value out of the system, like that's a huge win and, obviously, will create more value for our customers and more stickiness as well. And then ultimately, I feel like copilot is a overused term. But you could see a virtual SDR capability, particularly for a lot of those salespeople that are responsible for generating their own pipeline. Having that sort of capability, where you have someone that's running a motion to reach out to prospects, setting up meetings for you, figuring out like key data points for your demo or whatever you're doing, like that's the longer-term vision that we could ultimately provide for customers as well.

And as we think about the unit economics, as you think about a new world where data is kind of becoming more important, maybe the sales rep becomes less important over time or more productive over time. What are the unit economics as you just think about the solution set you can provide when you're kind of more data-as-a-service versus what's the traditional seat-based model? What's the tradeoff there?

The interesting example would probably be if we have a customer today that might be a $100,000 customer, so let's say it's 50 to 100 seats, whatever, if that same customer was coming in to buy a similar level of data in the operations OS, that might be a $200,000 to $400,000 ticket for us. So I think we actually like those deals where we're actually providing data into the back end of something because ultimately, it's actually more sticky than having a bunch of people log in because it's really getting routed into the core of the workflow for whatever that company is doing. And frankly, a lot of companies see more value out of that. And so we're able to generate more revenue. So if I can do that for...

Yes, all day.

I'll do that all day.

Where is the -- where are we at in that appetite on those customer engagements, as they start to move away from engaging on a seat-based model to this data-pull model? Is that early?

I'd say we're still pretty early. And interestingly, in the couple of examples that like come to the top of my head, like a bunch of people will come to us and say -- and sometimes, a bigger example is like, I spend $600,000 with you. I want to like consume the data, and I'm going to get rid of all the seats. And we'll say, yes, great. That's a $1.2 million deal. So they end up paying us $1.2 million or whatever the number is, and then they like never really get around to getting rid of the $600,000 seats, partially because like the users still want that interaction. They want to be able to use it. Sometimes, it's because like building something that the users will actually live in is hard, so they have these other tools. But every once in a while, you do have someone who can take out those seats, but it ends up being a happier customer for us at a higher level, and there's continued growth there. So it's still a deal that we're going to do. But the number of times that I've seen that conversation, like more often than not, they end up keeping most of the seats anyways, even if the plan is to ultimately build something internally to kind of fully replace [ ZoomInfo ].

Clearly, this data-as-a-service thing, I need to do more work on. It sounds pretty interesting. My last question really is around next year. What's the one thing that you're most excited about as you think about what investors should think about next year? Product? Go-to-market?

Yes. I think we're continuing to build capacity on the go-to-market side so that -- like I don't know when the economic situation is ultimately going to stabilize and improve. But we want to be in a position to take advantage of that when it does. Certainly, on the product side, there are a lot of exciting things, some of the AI stuff we've talked about. But also, the real focus on the enterprise -- because I do feel like -- particularly at the really high end of the market is an area where we're continuing to do really well. And we're focused on permeating those motions down into the rest of the enterprise and upper mid-market. So as we do that, I think we're excited about the product capabilities that we're integrating in and the go-to-market infrastructure that we're building to be able to improve that high end of the market for us.

Cameron, thank you so much for your time. Really appreciate it, and enjoy Nashville.

Absolutely. Thank you very much.

Thank you.