Dynatrace, Inc. (DT) Earnings Call Transcript & Summary

Okay. Welcome to the [indiscernible] everybody. We're very happy to have Rick and Jim here to talk through the Dynatrace story. Thank you, gentlemen, and Noelle for attending our conference. Again, we always love to have you. We are delighted to be here. It's a great venue for our conference, isn't it?

Yes. And it's -- the good news is shareholders and investors like to come to it, and it's a great place to see. Thanks for having us.

Thank you so much. So let's start off with some good news because I think in this last quarter, you guys reported some numbers and some comments that were quite constructive. Obviously, 16%, 17% revs ARR growth, 20% CRPO growth. Your net new ARR of $70 million was up nicely year-over-year. So obviously, something is feeling good in the business to give you these kind of numbers. Maybe you could put your finger on 1 or 2 things that went right during this most recent quarter.

Well, I think, Karl, you just pointed a number of them out. We delivered strong performance in net new ARR growth at 14% for the first half, 16% for the second quarter. That is, of course, the fuel to drive overall ARR growth. We increased in addition to exceeding the high end of the guide for Q2, we further increased the guide for the back half of the year for ARR growth. So that was positive. And in our view, we derisked the second half as well. So from the standpoint of sort of core metrics that organizations look at as to performance, we believe that we contributed in a number of those areas. On top of that, there were numerous other growth drivers, which we do speak about that are really the leading indicators, maybe a level down of how does the business feel a level below the core metrics of new ARR.

Let's talk about some of those.

And that gets you into, for example, our Dynatrace platform subscription DPS customers, that's now 70% of overall ARR. We see double the consumption growth of DPS customers as non-DPS customers -- so the greater the percentage of ARR on DPS, the greater the opportunity for further NRR accretion in the future and ARR growth. So that's expansionary. Logs, huge performance on logs now in just the last year, having essentially built a $100 million-plus consumption business or it is, let's just say, rapidly approaching $100 million or so in that region, growing at more than 100% year-over-year. And that has been also expansionary as part of the overall end-to-end ecosystem. And then you end up with pipeline growth amidst the strategics very positive and then consumption growth underlying that, which we view as a leading indicator of future ARR growth. And that was in the 20% range, 20% plus range. So a number of these, let's say, core underlying factors we felt very good about in the quarter.

And Rick, let's hit on that consumption strength because as you talked about on the call that's one of the things that's driving early expansion, so what is driving that consumption strength in the quarter and hopefully since.

I'll give you that one, if you want it.

So I mean I think it a byproduct of getting customers onto a Dynatrace platform subscription contracting vehicle. As we've said from the beginning that once we get customers on this vehicle, it makes it much easier for them to consume the platform. They commit to a dollar amount. They get a unit price based on their commitment. And so they have full access to the platform with a full rate card. So there's no longer an issue of having a sales engagement anytime you want to have trial a new product. And so now having that many customers, and it's been growing, as you know, over the last 3 years, now the core underpinning is now they can leverage more of the platform, and they are leveraging more of the platform. Rick provided a statistic that customers that are on a Dynatrace platform subscription consume at 2x the rate of a SKU-based customer. They trial 2x the capabilities of the platform. And so I think what you're seeing manifested themselves in the half 1 results were changes we made in fiscal '25 to go on the offensive from a go-to-market perspective. You're seeing it show up now. That wasn't going to happen overnight. And I would say the fastest-growing product that Rick mentioned with logs, you're seeing a lot of our expansions that we saw early, but those were customers that maybe weren't necessarily thinking of leveraging logs as a use case. They were able to trial it on their platform subscription, and it's led to some very significant expansion. So I think we're seeing the manifestation of that now in the results.

Okay, so let's hit on that log performance a little bit more. That was one of the highlights from this call that struck my attention. Similar question. What's behind that? To what extent is that incumbent log management companies like Splunk giving share to rivals like Dynatrace. I'm sure it's partly the investment that you've made in that log management product such that it's just getting better and better, more customer traction. Can you unpack that? And how big could that be?

Well, there are 2 primary drivers to keep it simple to our logs growth. One of them is to reduce cost. I have seen, I don't know how many dozens of customers around the globe in the last few months. And the adjectives they use range from out of control to meteoric to these kinds of numbers on log costs. Why? It's because cloud is exploding. AI is exploding. It is exploding AI workloads. It is exploding cloud-native workloads that is creating more logs. More logs mean more cost associated with those logs and an ability to manage that is important. And if you have an ability to optimize the use of logs, traces, metrics, all observability data types as opposed to only looking at logs, then you can get better outcomes for less money. So cost is a piece of it. The second I just alluded to, which are outcomes. Most of the -- well, many of the log vendors traditionally have not had end-to-end observability capabilities. They've had logs. So how are you going to find a root cause analysis, right? You are going to perform a root cause analysis when you only have logs, you're going to use logs, but maybe that's not the right tool. Maybe that's not the right data set. Maybe you need traces, metrics and having all of that data combined in context to provide analytics then delivers a better outcome. And so it isn't just a cost equation. It is really the combination of cost plus outcomes that's driving end-to-end observability. That is driving tool consolidation. And in our target segment, which is Global 15,000, so the largest of the largest companies around the planet, that causes them to move to consolidating these elements with Dynatrace.

I'd add maybe something to provide additional context for it that -- so we really got the product and the packaging right last fall. So while we had a log solution, I'd say with the product and the packaging and the pricing, we got that right in the fall of last year. And then I think we've augmented that with the addition of the strike teams. So we have these product strike teams that are focused on particular product areas. One of them is logs. And I would suggest to you that we have both the product, we have the pricing, we have the packaging. And we now have teams of people that are allowing our sales force to be much, much more productive around having these discussions, either leveraging logs on their own, meaning it's an extension of what they're already buying or in some cases, to Rick's point, broadening to an end-to-end observability story. So a lot of the building blocks that you're seeing for things that we've been putting in place has been very purposeful.

So, Jim, Maybe a question for you. You and Rick have talked about a lot of things that are going right in the business. Yet, how do we bridge that goodness with the guide for the second half, which you guided to a deceleration? Rick, you used the term derisked. Is it just conservatism, Jim? Or are there any factors that informed that second half guidance?

No, it's much more just -- the term I've used is prudent. And I'd start with what does the demand environment look like? The demand environment is incredibly healthy. Our pipeline is the strongest it's been in 5 or 6 quarters. So the pipeline is extremely robust. A consequence of some of the go-to-market changes we made, which is orienting more resources around these high propensity to spend customers, which are large, call it, Global 500 customers is, by definition, you're going to have large deal sizes. We're seeing that play out. We saw that in the first half of the year. Our pipeline is relatively weighted from a mix perspective to these very large deals. And so end-to-end observability, which tends to be the play that is the most successful. There is a lot of pipeline in that area. The timing of that is difficult to judge. It doesn't mean we won't win it. It just means pegging it, does it happen in the fourth quarter? Does it slip into Q1? So we thought that we should build some kind of prudence into that. What I would tell you is that if we have close rates similar to the first half in the second half, we will deliver a much better outcome.

Okay. Jim, on the call or at least the call back, you also mentioned that there were some year-over-year compare headwinds this quarter or next. Can you elaborate on what those were? Is there any way to quantify like on an adjusted basis what growth might have been?

So that was more oriented around subscription revenue than necessarily ARR that -- as you know, that we used to recognize ODC revenue as incurred. And so you saw building over last year. From an accounting perspective, we had to change that in Q1 to a more ratable model. And so the variability that you were seeing in ODC revenue has gone away. It's now smooth. So you're seeing a bit of a headwind just on a year-on-year compare perspective from ODC revenue. And then every company now again that even with a subscription revenue business, some customers may be what we call on hold, meaning maybe they weren't paying you. So you stop recognizing revenue for them. And then they get off hold and then you start recognizing, you do true-ups. And so last year, we had more of those in the back half of the year than normal. And so what I've suggested to people because they've looked at the back half of the year guide and they say, jeez, that seems like a pretty significant deceleration in subscription growth. And my comment back to them is that if you do adjust for those things that I just mentioned, I'd say the normalized growth rate for the business is more mid-teens, call it, 16%. And that's the way you should think about it exiting fiscal '24.

Okay, that's helpful. Let's switch subjects a little bit to the competitive environment. And I think one of the issues in the last couple of weeks that this group has been thinking through, there's always consolidation in your space, mostly to private equity, not so much strategics. But Palo Alto acquired Chronosphere, a much smaller player than you guys. But obviously, that created a little bit of concern in the Street that weighed at least temporarily on your shares as well as Datadog. Rick, what did you think of that acquisition? What's your perspective as CEO?

Who's Palo Alto Networks? I am kidding. Chronosphere certainly is a visible competitor. But from a direct perspective from Dynatrace, we just don't see them. In the market, they are oriented to metrics. They do not have a broad base of end-to-end observability as a solution and they have traditionally sold metrics increasingly into AI native companies and we're selling into the Global 15,000. So partly because of the end-to-end observability nature of the solution and the breadth of our solution and selling into the kinds of customers we're selling to and to the personas within those customers to whom we're selling, it really is not aligned as a direct competitive threat. So we don't really see it. Now having said that, of course, Palo has an ability to invest in that business. And as with all competitors, we will approach it with paranoia and a clear view as to what's happening over the course of time, and we'll make adjustments. One thing that it does certainly validate or one thesis that it certainly validates, of course, is the thesis we communicated a couple of years ago, which is that observability and application security are certainly converging. So we do see that, but they have some headwinds and the headwinds are going to be breadth of portfolio. Another headwind is going to be the buyer persona of the CISO buyer for Palo Alto Networks versus an IT ops or CIO-type buyer for observability traditionally. And so that's what they're going to have to work through, I think, as they go forward.

Can we talk a little bit about some of your own efforts to step into the security space, not so much Palo Alto going the other way. But what has Dynatrace done to add security features to your already world-class observability platform?

Our application security business -- so our logs business is growing faster than any other business for us at the moment. Second fastest growth is application security. So we are investing there and investing in a significant way because we do believe that convergence. Having said that, we have been very disciplined in our strategy of application security. It is not our intent, I should say, hasn't been our intent to go compete aggressively with all the security vendors. We don't believe that, that is a winning strategy. The winning strategy for us in application security, we believe, to be investing in areas of security in which real-time runtime observability data matters to the security outcome. And so that has resulted in areas and investments like runtime vulnerability analytics, which is our largest application security portion of the business. It is cloud security posture management, Kubernetes security posture management. It is cloud SIEM. These are areas where runtime analytics coming out of a broad-based data lakehouse consisting of security data types add enormous incremental and immediate value to the security outcome. So those are the areas in which we've been focused as part of the strategy to really evolve and leverage the 2 businesses together as opposed to try to construct a separate security business.

Okay. That makes sense. Rick, let's also talk about some of the ways that Dynatrace differentiates from some of these rivals, many of which sort of as you describe Chronosphere are very cloud-native, AI native. They don't have a presence with Fortune 200s where a lot of their infrastructure is on-prem. So can you elaborate a little bit on the on-prem cloud mix, how that perhaps gives you an edge and which way the wind is blowing in terms of that mix?

Sure. It is clear that in -- and I'll just pick a vertical for the sake of argument, but in financial institutions where we have very, very deep penetration really across the financial organizations, it is the case that they're going to have on-prem workloads for a lifetime to come. They're just going to continue to exist indefinitely. Now of course, they're also bringing up cloud workflows and those are getting supplemented or they're supplementing the on-prem workloads. So it really is a combination of factors, but the on-prem workloads don't dissipate. And so the result of it is that we believe that this is a significant advantage for Dynatrace by being able to do both with a common underlying platform. And that does give an advantage because now you're looking at the same dashboard, you're looking at the same capabilities, you're expecting the same answers irrespective of where the workload resides. And as it moves to the cloud or as you move some of those workloads from on-prem to become hyperscaler workloads, then you can use the same set of observability tools, capabilities and platform to oversee that transition.

Okay. I think another differentiator would be on the pricing front, where I think Dynatrace has been a little bit further along in being flexible on your pricing with DPS to customers, whereas some of the other large observability vendors are -- have a reputation for being quite expensive. So to what extent has that let's call it, more flexible pricing structure giving you a head-to-head edge?

I would say that it has. I'd say that the feedback that we get from customers almost universally of the DPS model is it is the most flexible contracting model that's out there. We don't charge overage rates. So if you exceed your commitment, we don't charge you a premium rate when you exceed that, others do. And now obviously, we will talk to them about if you're exceeding your commitment, it means that you're probably getting value. And oh, by the way, we may be able to offer you a better unit price. So there is this kind of give and take around whether they want to do an early expansion or whether they want to go on demand. And so we get very good feedback around that pricing model. They like the fact that they can trial the platform. They don't have to have a sales engagement. So it's just that it's a kind of a perfect match for what the customer is looking for and what we're looking for. One of the things that we've done that Rick started out that this notion of consumption and driving consumption, that's not a muscle that we've had, Karl. That historically, we have not been a very consumption-oriented company that I'd say now we have incentive structures focused on consumption. Our customer success teams are focused on consumption. They have a compensation at risk based on consumption. Our strike teams, their compensation goals are consumption of that particular product that they're supporting. And so this muscle of get them on DPS, get your teams of people that work with customers around driving consumption, driving consumption will ultimately lead if the customer is getting value and they're consuming at a rapid rate to an early expansion. And so you're starting to see that play out. And I would suggest to you that some of the performance that we saw in the first half of the year was a manifestation of that.

Okay. Let's talk a little bit about AI. There's a couple of aspects to it that are interesting. I think one topic that our team is thinking through, and I'm sure investors are, is when will the AI phenomenon be a real pull-through at the observability layer? I think I'll share the consensus and then Rick you can rebut it if you don't agree, that most of the AI applications inside large enterprises are today, still early stage, somewhat lightweight. They're chatbot-based, they're coding tools. They're not robust enough, and they're not really at scale in production to really need a lot of monitoring pull-through. So you haven't seen it yet. But you will, once the likes of UBS start building more robust enterprise-grade apps, then you'll see the pull-through. Does that feel right to you? Or are there ways in which you're actually seeing a benefit even today?

I think that is right, Karl. I think your articulation is correct. It is the case today that we have hundreds of our customers that have deployed us for AI workloads. So they are already using infrastructure monitoring. They're using log management. They're using metrics. They're evaluating their AI workloads today based on Dynatrace. What will absolutely accelerate is when those go regularly into production and begin to generate production level workloads, I think we'll see an acceleration of that. On the side, you then have the AI natives who are the LLMs, for example, that are doing their own infrastructure monitoring and others with their AI workloads. And those are already moving at a very fast clip, and that's where the infrastructure monitoring really comes into play for those kinds of companies. But I think you have to look at it both from an AI native perspective as well as AI workload perspective within the enterprise, and you have to think about both in order to really understand the evolution of that space.

Can you talk about your outlook for Dynatrace to penetrate that AI native community? I think you called out some successes on this last call. But can you elaborate and describe to the audience exactly what you're doing to become -- essentially gain mind share in that cohort?

Many things. First, the Dynatrace focus has traditionally been the CIO down through IT ops. We're selling an enterprise-wide end-to-end observability solution that delivers answers, and those answers deliver insights to enable very rapid root cause analysis and analytics and resolution of problems. And that's fundamentally what we've done. The evolution of the current environment is suggesting that developers are becoming much more involved in the observability decision, and that is abundantly clear in AI natives. So what we've done is over the last year, we've really spent a ton of time on our road map developing or expanding the Dynatrace platform to become developer-ready, number one. Number two, we've expanded connections into the overall ecosystem. So this past quarter, we announced integrations with Atlassian, very important one with ServiceNow, with GitHub, NVIDIA. So the result of all of these is that we are now built more fundamentally into this ecosystem of agents. And that really results in an ability to deliver autonomous operations in the future through an Agentic ecosystem that others can't provide.

Yes. I think that gets at another question I had about this, and that is all the large successful incumbents like Dynatrace are going to have to worry about essentially, in your case, an AI-native observability player coming at you, but you're not going to sit still and wait for that day to happen. Your R&D team, I'm sure, in a lot of interesting ways, are AI enabling your core product such that you can retain that incumbency. Can you talk a little bit, Rick, about ways in which Dynatrace is getting in front of that risk and essentially innovating to make sure that you indeed are the AI-enabled platform going forward and not some scrappy start-up?

Sure. The most fundamental answer to that question is we're not starting from today looking forward to develop AI sort of capabilities. We have been utilizing our AI-powered platform for more than a decade. We didn't come up with it 2 years ago. We didn't start work on it 18 months ago. We've been doing it for more than a decade. We build a completely integrated, massively parallel processing data lakehouse called Grail with all observability data types built into it in a causal way with context. That then provides the ammunition for our AI engine to analyze that to derive and deliver very specific answers. We believe that those answers are quintessential to enabling an AI ecosystem of agents to then take action. If you cannot deliver answers that are deterministic and trustworthy, I would commit to you, you cannot take action on those outcomes because they are simply guesses. So the way we like to think of it is that Dynatrace delivers answers, not guesses. And by delivering answers through this integration underlying data foundation with an AI engine, we set ourselves up to actually add value into an AI ecosystem that others cannot do.

Okay. Let's finish with maybe a quick thought on all the go-to-market changes that the 2 of you have spent a number of earnings calls discussing. Rather than ask you to go back and describe all that, maybe I'll phrase it a different way, and that is you've now had a year to 2 years. So looking back, what in your judge -- give yourself a report card on those go-to-market changes. What do you think went really well? And where do you think you've still got a little bit of work to do?

Well, I'd say where it went really well was, one, I think the weighting of investment to large strategic accounts. That is the customer base that we really shine in. So fortifying resources in that area, I think, was a smart move. It resulted in pipeline growth. It's already resulted in deal closures. So I feel very, very good about that. Two, I would say we've made great traction in the partner ecosystem, notably with GSIs. The GSIs are now a source of pipeline, and they are enabling even pipeline that they didn't source, enabling us to get exposure to C-level leaders through their involvement. So I feel very good about the weighting of resources to strategic accounts. I feel very good about the partner expansion. I also feel very good about this introduction of strike teams, evolving away from what was a specialist model with security now to the strike teams focused on consumption because at the end of the day, this orientation of consumption, I think, is an important measure for the health of the business. So I'd say if I were to say 3 things now the last -- obviously, all of these things are underpinned by having DPS as a contract vehicle.

Yes, got it. Okay. Any questions from the audience? We've got about 1.5 minutes. We successfully ran through everything. Gentlemen, thanks so much for coming to the event. You've helped to make it even better than it was last year. So I'm super appreciative. Thank you...

Yes. Thank you very much, Karl.

Okay. Thank you all.

I appreciate it.