Good afternoon. Thank you for joining us at the Morgan Stanley TMT Conference. My name is Elizabeth Porter. I'm an analyst on the U.S. software team, and I'm really excited to have with us this afternoon ZoomInfo's CEO and CFO, Henry and Cameron. We are going to take audience Q&A, so Mike will go around at the end. Four important disclosures: please see the Morgan Stanley Research Disclosure website at www.morganstanley.com/researchdisclosures. With that, thank you guys so much for joining us.
Of course. Thanks for having us.
Great.
Yes.
So I think to start off, it'd be really helpful to get your views on the macro demand backdrop, first from the new customer side and then also from the existing customer side, just given some of the differences there. So I think to start off with the new customer side, in Q4 you highlighted some things like record new logos closing in Q4, including some of the largest amounts of enterprise logos that you had added in quite a few years. So kind of what changes are you seeing from kind of the new customer demand side to start the year, and what are some of the expectations that you have around how growth contribution can look differently in 2024 versus 2023 from the new business side?
Yeah. Look, I think we continued to see relatively strong performance from our new business side of the house. We saw that throughout 2023, that while our customer base and net retention were more under pressure, new business continued to perform. Q4, we talked about our largest net new logo or new logo count we've seen on record. And so our new business team continues to generate demand and close that demand. Our sales cycles have gotten faster. Our create and close in the month has gotten faster. So our product has great product-market fit and is really resonating with the market. In our customer base, I think we are continuing to feel the pressure from customers who bought ahead of the seats that they had, customers who have had layoffs.
When you look at the layoffs that are happening, particularly around tech, it's overweight against the go-to-market organizations, the sales, the marketing, the SDR, the account executive organizations. And so we feel that pain more acutely than other software providers because we're directly servicing that group of sellers. And so in our customer base, you're seeing downsell. Our gross retention rates have stayed largely the same, but there's been real downsell pressure in the customer base to normalize the number of users.
Great. And on that layoff side, when we started off this year in January, we kind of saw renewed kind of announcements for layoffs across tech. But you noted that these layoffs look a little bit different than what we saw over a year ago, kind of alluding to being more surgical. So what exactly are you seeing, and how is that different?
One thing that I'll also mention is while we in the customer base, we feel pain in the SMB, in the mid-market, in the enterprise, we continue to see real opportunity and continue to grow our largest customers and so continue to feel good about our competitive positioning, our product-market fit, new products we're bringing to market to our enterprise customer base, and feel good about the growth in that customer base. As it relates to layoffs in January and into this year, I think what you're seeing is last year, there was kind of blanket layoffs, and it was kind of more panic-driven than anything because what is happening inside of the boardrooms of private equity and venture capital-backed companies is the boards are saying, "Listen, we're not done scrutinizing every last dollar of spend.
We want to get to real margins in these businesses." The place that they're going out to do that is within their existing contracts. On the other side, where we're seeing strength in new business, what we're also hearing from that side is we believe that driving growth in our business is going to come from us driving efficiency and effectiveness of our frontline sales rep, cutting waste from our marketing professionals. So while companies are grappling with cutting costs, they're also trying to figure out how to drive efficiency with the remaining workforce. We're seeing that happen on the new business side, but there is a push to cut costs in the existing vendor base.
Great. And on the Q4 call, you noted to some customers being these boomerang customers, some that had left and have since returned. In fact, you saw 550 that had left the platform and then returned in the back half of the year for 2023. Any way of sizing kind of the magnitude of customers coming back relative to those that left or relative to any sort of the growth customers that you're adding? Is this a trend that we could expect to see continue into 2024?
So, in terms of the customers that we see losing, it does kind of span the typical. We don't lose a lot of kind of higher-end enterprise customers, but throughout the rest of our customer base, you see them kind of moving largely reflects the average size of the customers. And realistically, I think in time periods where you do see macroeconomic pressure and times are tough, people are really scrutinizing budgets, there's a little bit more impetus for people to think about, "Wow, could I try something that's much cheaper?" And therefore, there's more of those customers that went out and tried something much cheaper, realized that they're not getting the benefit. The sales teams are really loud about how they're not able to make their number in the same way when they're not using a high-quality source for data and insights.
Therefore, that's when we see those coming back.
As those customers come back to ZoomInfo, any sort of changes in trend that you're seeing as it relates to the spend that they're having versus when they left and when they came back?
Yeah. It's very similar to the spend that we would have seen in the average customer that didn't leave. So in today's world, particularly for customers that are more challenged and have budget scrutiny, there is a net downsell that we're seeing. So we do see a similar level of net downsell. You think about it, someone who had 20 seats, wanted to try something much cheaper, was only going to renew at 15 seats anyways. We're basically seeing those come back at those sort of levels.
Gotcha. And as we've worked through kind of a lot of the headwinds on renewals, where do you see that bottoming? And I know Q1 is a tough quarter. So any sort of trends that you're seeing thus far into that renewal base and the behavior of those customers?
Yeah. So Q1, we are expecting to continue to see downsell pressure. Part of that is it's a big renewal quarter. We have a number of multi-annual contracts coming up and maybe more importantly, a much bigger cohort of small business customers as part of that expiring base. But as we look forward, we do see that even in Q4 and as we move forward, that the enterprise set of customers are stabilizing a little better, and you see that upsell. One of the encouraging trends is if you look back earlier in 2023, customers that downsold in, say, Q2 or Q3 of 2022, they downsold even more. In 2023, you think about that as the first cuts were before they did a whole bunch of layoffs.
Maybe they were just removing some of the expected growth that they thought they had and didn't achieve, but then went and laid off a whole bunch of people. That created more pressure for downsell. So we got through Q4. In the beginning of Q1, we do see that those customers that were more volatile or had more significant downsells in 2022 had less downselling or maybe even came in more stable in 2023. So that's certainly an encouraging trend, particularly as we get through the kind of bigger bolus of small business renewals that we have in Q1.
And kind of looking beyond the near-term kind of tough macro, as we start to get to the stabilization, people feeling better about the economy and budgets, a big opportunity that you guys have is with the advanced kind of functionality going beyond just the core data set. So can you give us a view of, one, what are some of these offerings that are in the advanced functionality? What you're seeing is some of the most demand and how that trend it seems that advanced functionality is somewhat stalled a little bit just in the tough environment. But when can we start to see some acceleration?
I think first from a product perspective, you can think of this as one aspect is intent data, so data that tells me when a company that might be a prospect of mine is researching my competitors, is researching my products and services, when they're doing that in an elevated way that would indicate they're in market for my products and services. That's valuable, but really, I want to tie that around Workflow because when that happens, I want something to automatically happen from a marketing perspective or a sales perspective. So Workflows is a software tool that we've built that lets you take a signal like an intent spike or a company that visits your website and then orchestrate a go-to-market motion downstream from there. So when a customer builds Workflow around a signal inside of ZoomInfo, those customers retain at the highest rates.
They get the most value out of ZoomInfo. And so advanced functionality when we think about advanced functionality, we also think about it as a way to get our customers to higher net retention rates because the more they're using workflow-focused solutions, the more they're growing with us, retaining at higher rates with us.
I think the other thing about advanced functionality that's interesting is those customers that are more sophisticated in using advanced functionality across a bigger part of their organization are seeing more traction. That's particularly true with OperationsOS and MarketingOS where people are able to automate specific motions or route and cleanse within their database. Sometimes they're using that for AI projects or operations-related projects that they're doing. So that part of advanced functionality continues to see really good traction. I think there are other parts of advanced functionality where it's really interesting for the sales team or provides interesting data, but there's not a specific use case that people are using. In those areas, it has been under more pressure, particularly as people are focusing on budget cuts.
The interesting part of that is as we're rolling out the AI Copilot functionality, it really brings a lot of these things together. So we can take some of the advanced functionality around, say, workflows or intent and actually essentially automate the setup of that through a generative AI, so build those workflows without someone having to go in and be an expert in the system, which really speeds the value, can leverage some of the other integrations or other things that we've built to drive really exponential value for the customer.
On that Copilot point, you announced this solution, and pricing strategies are kind of still in the works. So how do you imagine a pricing could be for a Copilot? Are there any historical examples within your product suite of how attach rates have trended for solutions that you could point to as potential views of how we could see this playing out?
So in our history, we've done two big platform migrations, one in 2017 after we made an acquisition of a company called RainKing, and we put those two products together. We migrated the legacy RainKing customer base onto a new combined platform over the next 18 months. We did it across the entire customer base, and we monetized that transition. And then when we made the acquisition of ZoomInfo in 2019, we did a similar thing. We built a new platform, and then we migrated all of the customers from ZoomInfo and all of the customers from DiscoverOrg to the new ZoomInfo platform. We did that, I think, over the next 3 years, 3, 4 years. And we monetized that migration. We learned a lot from both of those migrations.
We learned how to enable the sales team, how to get the go-to-market collateral together, how to go out with one message. We feel really good about repeating that motion here with Copilot, where not only do you get not only is it Copilot, Copilot's kind of the showcase feature in our new AI-enabled platform. And so there are a number of other AI features that we built into that platform: chat AI, account summaries, the ability to ask questions about accounts that pulls data from your CRM systems, a company's earnings calls, all of ZoomInfo data to understand the account better. But we've built this suite of AI functionality that will migrate our customers similar to the way we've done those other migrations over and into a new AI-enabled platform, and we'll monetize on our way to that.
Great. Another way that ZoomInfo is benefiting from generative AI is also demand for the core data asset, as customers need kind of high-quality data to feed it into their CRM before you can really do generative AI applications on top of that CRM. A thesis around ZoomInfo being used to clean CRMs isn't new, but how is generative AI starting to drive acceleration in this use case? Is this something that's playing out now? If so, where do we see it, and how could this trend evolve?
Yeah. I've spent my entire professional career and nearly two decades telling everybody who would listen that the data in their CRM systems was not good enough to be leveraged by their sales teams, by their marketing organizations for any go-to-market motion. Now, when you go up to the chief revenue officer , that's kind of like not an interesting topic. It's like, "What do I care about the data being dirty inside of my CRM system?" It was like relegated to an IT administrator somewhere. Over the last decade, what you've seen is this incredible rise. LinkedIn's the number one new title in the world, according to LinkedIn, is the head of RevOps. What does a RevOps person do? They're literally responsible for orchestrating data in your different systems to run campaigns, to create territory mapping, territory assignment, lead routing.
They build the infrastructural elements of how you go to market. The key input in that is data on your customers and data on your prospects. Today, every C-suite in the world is talking about, "How do I use Gen AI to make my business more efficient, to make my business more effective, to give myself an edge?" When they go down to the go-to-market organization to say, "How are you using AI?" the place where they're going to tap into data to leverage AI is their CRM systems. All of a sudden, this very boring problem of your data is not fully accurate in your CRM becomes acute because you can't plug in data that says Walmart is a small business into an AI machine and have it figure out how to message Walmart what products to sell, which sales rep to assign it to.
And so not only cleansing the data that exists in CRM, but when you think about the ZoomInfo data asset on a company, it's not just the company and the size and the location. It's also a number of long-tail attributes. Those attributes will include things like, "How many locations do they have? How many people in data science do they have? If it's a hospital, how many beds do they have? How much funding have they received? What is their employee trend line over the last three years?" And so the ability to leverage that data in any number of generative AI use cases is abundant.
We're starting to see that in the enterprise, particularly in the high end of the enterprise, where they're being thoughtful about, "How do I actually leverage AI to a proper end use case for my sales teams?" And it's just not possible to do that with the data that organically lives inside of the systems that go-to-market professionals are using. And I think that's a big reason you're seeing this rise of revenue operations professionals who have to leverage data to run really any go-to-market motion, but particularly the generative AI ones. And we think of this as an infrastructural element to your CRM application, to your data warehouse application. We started building processes and applications on top of our CRM data for go-to-market, and we skipped over the fact that the data that gets in there gets in there from a variety of different places.
Marketing puts it in, sales puts it in, someone buys a list, someone goes to a webinar, puts it in, events, scan a badge, it goes into your CRM system. That data is constantly changing. People are getting promoted. They're leaving their jobs. Companies are growing. They're shrinking. They're doing M&A. And there's nothing that just organically populates those changes inside of your CRM system. And so you need infrastructure that actually does that. And we're the most obvious, obviously the largest infrastructural provider of that.
Great. I want to shift track a little bit to the go-to-market strategy. In previous quarters, you guys have talked about some sales efficiency hurdles. What steps has the company taken to alleviate those? Any sort of updates in terms of the efficiency that you guys have been driving thus far and any further investments that you guys are looking to make around that sales capacity piece?
Sure. So in terms of the go-to-market engine, we are continuing to grow our capacity from a sales and marketing perspective to continue to basically drive that engine of growth. From a new sales perspective, we continue to see solid demand there and really continue to see fairly good go-to-market efficiency. Certainly, we've invested into our PLG motion. So now customers that we wouldn't have necessarily put into the sales team, they can get a free trial upgrade through to a paid version. We're starting to see solid success with that. It's still small, but growing well through Q4. And certainly, that enables more of the higher potential, higher-end customers to come in and get more attention from the sales team as well. And then on the existing customer side, we've seen that our churn rate hasn't moved that much.
It's a little higher with a worsening macro, but it's still very solid. We've seen that the net downsell among our customers has been significantly increased. What we've focused on this year is really refocusing the sales team to be more consultative, to help those customers find value in what they have already, and really help reset the relationships that we have with our customers so that we can rebuild that trust. When they are ready to grow again, when they do start thinking about where they can invest, that we're really well-positioned to help them with that and to drive value, particularly when we're coming to market with a new exciting tool for them in the Copilot, the AI-based Copilot, to really help them find efficiencies in their business as well. Those two aspects of where we've been able to shift the go-to-market are very exciting.
We think about that as basically customer centricity that leads to fertile ground so that when we show up with something that we believe will drive tremendous efficiency and effectiveness inside of their businesses, that there's willing ears to listen to that. And if you think about the time between 2019 and 2021, we did this platform migration. We made a number of M&A acquisitions. We built a number of new products, and then we incentivized our sellers to take that to market. And so it did start to feel from the customer-based perspective that every time we showed up, it was to sell more product. And they wanted to buy new product in those periods of time too. But as the macro changed, they wanted us to show up and consult on how to drive value out of what they've already purchased.
And so we've really focused on customer centricity over the last year to make sure that that is the mentality that our account managers show up with, that the comp is designed in a way that doesn't punish them for driving value in the customer base or not upselling every last possible product. We think that has put us in a much better position to show up in the middle of the year with Copilot that we feel really strongly about that can drive efficiencies for them.
Great. And as you've expanded the portfolio kind of going beyond just the data asset, you are building more of the platform play here. But we do hear about competitors like the Apollo, the RocketReach that are a little bit more kind of narrowed in focus. So I'd love to kind of get your perspective on how ZoomInfo is competing against them in terms of the breadth of the data, the breadth of the solutions as well. And then second, for this self-service motion, is that putting you guys up against them at all more in the lower end of the market, or is it really just same target customer that you've always had but just a more efficient way to get them to try?
Yeah. I think about this in a number of ways. One, if you look at just data side by side, from a data quality, a data breadth, a data coverage perspective, we're far and away the leader. I started the company 17 years ago with a focus on data quality being the largest differentiator, and that carried the company through. And so we need to continue to make sure our customers can see the differences in that data quality and understand the impact around when you don't have that data quality, what actually happens to your go-to-market motion. And we know we're the leader there. The second thing is what we really believe the future of go-to-market is around signals. It's not enough to just have information on every company in the world and every business professional who works at those companies and how to contact them.
Timing matters a lot. What we've been focused on is building signal that tells you when a company is in market for your products and services. That might be intent data. That might be that they visited your website but didn't fill out a form and were able to de-anonymize that company. That might be that they just hired a new chief information officer who's in your buying committee. Maybe on an earnings call, they mentioned your types of products and services, that they're struggling with something that your products and services might resolve. Maybe they opened a new location, and that's important to you. There's a plethora of signal that is important to every one of our customers that they should be leveraging to know when to get in front of a customer.
Now, today in the platform, it's very much a pull mechanism to get that insight out. You have to go look at intent and then website and then something else. The premise of Copilot has been, we go tap into your CRM system. We understand all of your customer wins and your customer losses. Because we have that underlying data on those companies, we're able then to model what your lookalike best customers look like. So I look at all of your wins, and then I can see the underlying attributes. Maybe they all use Salesforce and Marketo. Maybe they all are in the Midwest. Maybe they're all hospitals with 100 beds. Maybe they all have seven data scientists or more.
Some unique attribute that we're able to see in that metadata that we're able to take and say, "Okay, this is now your best universe of companies to go after." Great. But now I want to know signal that tells me when they're in market for my products and services or that they're increasing their research on topics that are relevant to me. Or they hired a new CIO or someone in my customer base just left and went to be into the buying committee at this company in my target market. And so what Copilot does is it gets that data from CRM. It then goes out and reads everything it can find about a company. It'll read the website, the job descriptions that they've posted, the press releases if it's a public company. It reads their earnings call.
We ingest podcasts and transcripts from any interviews they do on YouTube or elsewhere. We take all of that information, and then we know who do you care about? Who do you care about from a type of company perspective? Who do you care about? What products do you sell? Who is the buying committee you sell that to? Then without the customer doing anything, we customize the entire experience around that. So then we know the intent topics you care about, the buying committee you sell to, the projects and initiatives that matter to you. Then we're delivering that against that lookalike company set in real time every single day and then actually drafting the message based on all of that context that you should be sending out to the key members of that buying committee.
We think that changes the way our customers interact with our products and services. We think we were seeing it drive up engagement across over 20,000 beta users of the product, including our own sales and account management teams. We think it expands the seat count for us within our customer base where today we may largely play in part of the account executive organization, the SDR organization, but we think this expands us, gives us the opportunity to expand across all of account executives, all of the account management organization, and the customer success organization as well. So we really think that the ability to simplify that user interface leveraging generative AI really drives a much better experience for our customers and a great monetization opportunity for the business.
Great. I'm going to ask a couple more questions and then turn it over to the audience in case we have any questions. I wanted to do a little bit on the financials. When I look at kind of the revenue guidance for 2%-3% growth in fiscal 2024, it implies the days-adjusted sequential revenue growth does get better as we get towards the end of the year. So how should we think about the level of conservatism in guidance? And you mentioned that we're going to be past a lot of these renewal headwinds by the time we get to the end of the March quarter. Any sort of trends to call out that you've seen kind of thus far and how that can impact your visibility?
Yeah. So certainly, the underlying components of growth set up pretty well for us. Part of that is we talked about before the clients that had downsold or downsold and selling a little less. Certainly, our health scores, that's engagement and utilization of the products, are better as we start looking into Q2 and Q3. And that obviously implies an improvement in renewals. And honestly, just the demographic of our customers as we get out past Q1 is weighted a little bit more towards larger customers. Certainly, the mix of customers in our more challenged industries like software and technology are smaller than they were before. So I think there's a lot of things that set up well for us. Certainly, that would naturally create a potential improvement to net retention.
I think our base case in the guidance is that there's probably some unknowns or other pressure that isn't being reflected in those things that might offset some of those things to create a little bit less upside than you might expect just looking at those underlying trends. That gets us to a guidance level at the midpoint that's probably a similar net retention rate that we saw in 2023 with new sales being kind of flat to slightly up. Obviously, the high end of guidance would be an improvement against that, and the low end of guidance would imply that there's increased macroeconomic pressure that would drive that lower.
Great. Then before I turn over the mic, I want to hit on margins. You guys guided to about 39% operating margin for fiscal 2024, slightly below that 40% line that I think some of investors had in their minds. What's driving kind of the expectation for some margin contraction? Is it really just kind of the leverage in the model, and we should see that reverse as we get back to better revenue growth? Longer term, how should we be thinking about the normalized margins for the business?
Yeah. Certainly, we are investing for growth in the long term. The Copilot investments that we're making, both between the people that are helping to develop that as well as the infrastructure and training costs associated with that, are probably a few hundred basis points of costs that we're pushing into the system. Obviously, we've focused on identifying and executing against potential efficiencies in the business to largely offset that. It's an important investment for us to be making for the long term and to really kind of continue to drive growth. That is what we're largely focused on. I do think as we continue to move forward and reinvigorate growth as we get to a more normalized environment and start to realize more benefits from Copilot and the other things that we're doing, there is natural operating leverage in our business.
I would expect that margins, obviously depending on that growth, would be able to improve from where we are now. Certainly, we will focus on reinvesting some of that operating leverage back into driving that flywheel of growth going forward. Certainly, keeping margins in the 40-ish% zip code and potentially going higher from there is in the cards as we move forward.
Great. Do we have any questions from the audience? So I wanted to go a little bit more on that kind of the AI investment side. And we have in our minds, these are some higher costs as you tap into kind of the LLMs. Sounds like this will be a little bit of headwind on the margin side. But as you guys infuse kind of your own technology into your practice, kind of what are some of the benefits that you're seeing, and how does that do net out longer term?
One point on the AI costs too. Today, we leverage OpenAI, we leverage Anthropic, we leverage our own internal LLMs that are modeled off of open-source LLMs. We're balancing across those three different LLMs based on the use case. Sometimes OpenAI gives us the best results. Sometimes Anthropic does. Sometimes OpenAI is less expensive. Sometimes Anthropic is less expensive. Sometimes we can get the same result with our own internally built LLMs. Also, the cost of these is coming down in a pretty meaningful way, almost exponentially. We think there's opportunity over time to reduce the expense structure from an LLM perspective and leverage more of our own internally built LLMs.
I think the other really important aspect to that is that you are always going to get a better result at a lower cost when you're starting with a high-quality finite data set versus everything in the world, but the LLM has to be trained to weed out quality. That better result is going to mean less random answers that you end up getting back. It's going to mean less kind of problematic things coming out. But it's also going to drive a much lower cost. So while we're investing significantly because we have the most robust, highest quality data asset that you can find out there, it means that our investments go a lot further than someone trying to train it off a more randomized or less quality-focused data set.
There's also this question we get that's like, "Hey, isn't there Copilot fatigue? You have Copilots coming from all over the place. Why does your Copilot matter in a world with Copilots from every major software provider?" And I think it's for two reasons. One, when you think about what a Copilot is designed to do, it is designed to help the end user in their most important task. I think this is why you see GitHub's Copilot be so successful and drive so much efficiency because it's driving exactly what the developer is trying to accomplish, which is write code, write code faster, write better, faster code. Now, why is GitHub in such a position to be able to do that? Well, it sits on a mountain of data from everybody who's written code and published it into GitHub.
It's got the most robust data asset to be able to deliver that outcome. When you think about what an account executive, a go-to-market professional, a marketing professional, a sales development rep, an account manager is trying to do every day when they sit down at their desk, they want to know, "Who are the accounts that if I call or engage with or spend time on right now, give me the highest likelihood to close business against? Where should I spend my time? Which accounts and why and how?" When you think about how you deliver that, you can't just deliver it based on your email data or based on your CRM data. You need a whole group of signal or a whole bunch of signal about those accounts that tells you when this account is the right fit for you to reach out to.
The data that just exists in your CRM or just exists in your marketing automation system, it's not enough to deliver that. You really need all of that signal that exists outside of the four corners of your properties to be able to deliver you the when and the who to reach out to. So when it comes to why ZoomInfo is very best positioned to deliver that, is that we own the largest data asset on businesses, on the professionals who work at those businesses, and on the changing signal that's happening at those businesses every day.
Over the last year, we've built an embedded CDP that allows us to take customer data, merge that with ZoomInfo data, and then deliver to our customers, the account executives, account managers, the accounts they should be focused on today that leverages all of that unique signal that we create. There's nobody who's positioned like that for go-to-market professionals.
Great. With about the minute we have left, you guys are in 2024, should be kind of getting through those renewal headwinds, have the opportunity with a broader portfolio, these AI initiatives. If you were to focus on kind of one or two of the top things you're most excited about for next year, what would that be?
I think it is driving Copilot into our customer base and really expanding our footprint across enterprise customers. We think there continues to be a tremendous opportunity in the enterprise where we have incredible product-market fit, where we've made investments from a privacy and security perspective that make us stand out meaningfully within those enterprises. We continue to have real opportunity with them.
Awesome. Great. Well, thank you so much for joining us today.
Thank you.
Thanks a lot.