$DDOG Datadog Q1 2024 Earnings Conference Call

Thanks, Yuka, and thank you all for joining us this morning. We are pleased with our execution at the start of 2024. First, we have continued to broaden our platform across observability, cloud security, software delivery, as well as closing the loop with cloud service management. We also kept supporting our customers' adoption of new technologies, including GenAI and large language models, and we have continued to add new customers and to see existing customers increase their usage, growth, and product adoption. Let me start with a review of our Q1 financial performance. Revenue was $611 million, an increase of 27% year-over-year and above the high end of our guidance range. We ended the quarter with about 28,000 customers, up from about 25,500 last year. We had about 3,340 customers with an ARR of $100,000 or more, up from about 2,910 last year. These customers generated about 87% of our ARR. And we generated free cash flow of $187 million with a free cash flow margin of 31%. Turning to platform adoption, our platform strategy continues to resonate in the market. As of the end of Q1, 82% of customers were using two or more products, up from 81% a year ago. 47% of customers were using four or more products, up from 43% a year ago. 23% of our customers were using six or more products, up from 19% a year ago. And 10% of our customers were using eight or more products, up from 7% last year. We continue to see robust growth in our three pillars of observability: infrastructure monitoring, APM, and log management. But we also have many younger products that are becoming more meaningful contributors to our business over time. For example, our products outside of infrastructure monitoring, APM suite, and log management exceeded $200 million in ARR in Q1. And as a reminder, within the APM suite, we include core APM, synthetics, RUM, and continuous profiler. And as we look at the 12 products that we launched between 2020 and 2022, those now contribute about 11% to our ARR. Of those 12 products, eight are over $10 million in ARR, which is a nice milestone for these relatively new additions. And we are seeing some products grow faster than we initially expected. For example, database monitoring is already 1% of our revenue with strong and growing product penetration across our customer base. So we are very pleased with the progress of our new products, even though we know we have much further to go with them. Now let's discuss this quarter's business drivers. In Q1, we saw usage growth from existing customers that was higher than in Q4, and this usage growth in Q1 was similar to what we experienced in Q2 and Q3 of 2022. As a reminder, that was a period when we started to see a normalization of usage following the accelerated growth we had experienced in 2021. Overall, we saw healthy growth across our product lines, and as usual, our newer products grew at a faster rate from a smaller base. While some of our customers are continuing to be cost-conscious, we are seeing optimization activity reduce in intensity. As an illustration, the optimizing cohort we identified several quarters ago did grow sequentially again this quarter. We also see that customers are adopting more products and increasing usage with us. We think this shows that they are moving forward with their cloud migration and digital transformation plans and that we are executing on opportunities to consolidate point solutions into our platform. And finally, churn continues to be low, with gross revenue retention stable in the mid-to-high 90s, highlighting the mission-critical nature of our platform for our customers. Moving on to R&D, we had another very productive quarter. In the GenAI space, we announced general availability of Bits AI for incident management. By using Bits AI for incident management, incident responders get auto-generated incident summaries to quickly understand the context and scope of a complex incident, and users can also query Bits AI to ask about related incidents and perform tasks on the fly from incident creation to resolution. We're also continuing to see more interest in AI from our customers. As a data point, ARR for GenAI customers was about 3.5% of total ARR, a strong sign of the growing ecosystem of companies in this area. To have customers understand AI technologies and bring them into production applications, AI integrations allow customers to pull their AI data into the Datadog platform, and today about 2,000 of our customers are using one or more of these AI integrations. And we continue to keep up with the rapid innovation in this space, for example, adding a new integration in Q1 with the Nvidia Triton Inference Server. In the cloud service management area, we released event management in general availability. Our customers face increasing complexity at scale, causing the volume of alerts and events to explode, which makes it difficult for teams to identify, prioritize, summarize, and route issues to the right responders. Event management addresses this challenge by automatically reducing a massive volume of events and alerts into actionable insights. These are then used to generate tickets, call an incident, or trigger an automated remediation. And by combining event management with Watchdog, Bits AI, and workflow automations, Datadog now provides a full AIOps solution that helps teams automate remediation, proactively prevent outages, and reduce the impact of incidents. In the observability space, our log management product continues to expand in capability. In March, we made error tracking for logs generally available. Error tracking intelligently combines millions of errors from logs into a manageable number of issues for customers. And beyond error tracking, we are delivering new features to allow customers to do more with their logs within the Datadog platform, starting with new query capabilities such as enhanced full-text search and support for advanced subqueries, both highly desired by our customers. We also continue to make progress with Flex Logs. As a reminder, Flex Logs allow customers to easily scale storage and compute separately, which in turn allows for new, very high-volume use cases in a cost-effective manner. While Flex Logs remains in limited availability, we are seeing a high level of interest from customers, many of whom want to retain logs for long-term purposes such as audit, security, and compliance. And we're pleased to see that with only a limited set of customers so far, Flex Logs already exceeds $10 million in ARR. In the digital experience area, we launched mobile app testing in general availability, giving access to fast, no-code, reliable testing on real mobile devices, which was a big challenge for customers given the wide range of devices and operating systems in use by consumers. And in cloud cost management, we've added full support for Google Cloud, so FinOps and DevOps teams can optimize their cloud spend across the AWS, Azure, and GCP footprint. Cloud cost management is another of our newer products that exceeds the $10 million ARR milestone, and we believe there's significantly more opportunity for us to have our customers there. As usual, I'd like to thank our product and engineering teams for the quarter, and I'm looking forward to the many announcements we'll make at our Dash conference in late June here in New York. Now let's move on to sales and marketing. We've been pleased to once again add some exciting new customers and expand with many more, so let's go through a few examples. First, we signed a three-year, seven-figure expansion with a leading online grocery business. This customer has used Datadog as their platform of choice for several years now, and as they migrate to Azure, they are looking to ensure reliability and security as they deploy at scale. With this renewal, they are adding Cloud Security Management, Application Security Management, and Cloud Cost Management to enable a shift to a DevSecOps culture in the organization. And this customer expects to add seven products for a total of 14 across the Datadog platform. Next, in two deals over the past six months, we had a seven-figure expansion with a medical device company. This customer was primarily using our infrastructure monitoring and APM suite, but its legacy logging solution was becoming cost-prohibitive, while a lack of correlation across siloed teams was causing frustration and higher times to resolution. With this expansion, the customer plans to adopt nine products and consolidate its log management tool as well as four other commercial and open-source tools into Datadog. Next, we signed a high six-figure expansion with an athletic apparel company. This company had a dozen disparate monitoring tools which wasted time and impacted operations, revenue, and customer experience. With this expansion, the company plans to consolidate out of four commercial and open-source point solutions. They also expect to save millions of dollars over the next several years while providing a great consumer experience. Next, we signed a high six-figure expansion with a European division of one of the world's largest carmakers. This customer has chosen Datadog as its observability vendor in many business units globally, and in Europe, they currently monitor about a quarter of their applications with us and are migrating hundreds of applications to fully move to Datadog in the next two years. With this expansion, this customer is using nine products in the Datadog platform. Next, we signed a six-figure land with a division of a Fortune 500 industrial company. The company is moving its e-commerce applications to Google Cloud. They felt that existing on-premise monitoring tools would not transition well to the cloud and are starting with three of our products as they are confident in Datadog's ability to keep innovating in modern cloud and serverless environments. Finally, we signed a six-figure land with one of the world's largest communication infrastructure companies. This company started a cloud migration a couple of years ago and found itself limited by fragmented tooling and lack of data correlation. In contrast, the Datadog service catalog gives them a single view for performance, ownership, security, SLOs, and KPIs, which this customer believes is a unique capability among the vendors it considered and which aligns with their goal of delivering centralized observability across the business. And this customer is adopting seven Datadog products initially and consolidating out of four tools. And that's it for another productive quarter from our go-to-market teams. Let me now say a few words on the longer-term outlook. Overall, we continue to see no change in the multi-year trend towards digital transformation and cloud migration. We are seeing improved usage growth with less impact from optimization than we had seen in the last few quarters. For those customers who are remaining cost-focused, we are very happy to have them get value from their observability solutions and consolidate into the Datadog platform to achieve time and cost savings. Meanwhile, we are seeing continued experimentation with new technologies, including a growing adoption of AI, which we believe will be an accelerator of technical innovation and cloud migration over time. And we're working every day to innovate and help our customers adopt new technologies with confidence and become better businesses in the process. With that, I will turn it over to our CFO, David.

Yeah, hi Sanjit. I think in general, it's hard to draw a precise quarter-by-quarter one-to-one mapping between the revenue of the cloud providers and our revenue. I think you pointed out there are things in their products that don't relate to us directly, or things in their revenue that relate to us directly. We have products that don't tie one-to-one with infrastructure on their end. But in general, over the longer term, we are very exposed to the growth trend you will see with the cloud providers, and the correlation you've seen in the past between our businesses we expect will remain in some form in the future. We are also very exposed to the same tailwinds of cloud migration but also AI adoption. I will say also on AI adoption that some of the revenue jumps you might see from the cloud providers might relate to supply of GPUs coming online and a lot of training clusters being provisioned, and those typically won't generate a lot of new usage for us. We tend to be more correlated with the live applications, production applications, and inference workloads that tend to follow after that and are more to all of these applications going into production. So these are the things to factor, but overall same trends, just not a one-to-one timing.

Yeah, so we have products for monitoring not just the infrastructure but what the LLMs are doing. Those products are still not in GA; we're working with a smaller number of design partners for that. As I think not only these products are maturing, but also the industry around us is maturing and more of these applications are getting into production, you should expect to hear more from us on that topic in the near future. The customers we have that are the most scaled on AI workloads are the model providers themselves, and they tend to have their own infrastructure for monitoring the quality of the models. But we think they are good bellwethers in terms of where the adoption of AI is going to be from all the other companies. And we definitely see a trend where customers start with an API-driven or API-accessible model, build applications, and then offload some of that application to other models that typically come from open source, and they might try to fine-tune themselves to get to a lower cost and lower time to respond.

Yes, so I'll let David speak about the cRPO dynamics. But look, we've seen over the past couple of years really, but really the past two quarters, more consideration than we've seen in the past, in part driven by customers wanting to be cost-conscious, wanting to save money, but in part also by customers getting a little bit further into their cloud migration and rationalizing what they're using as they do that. So we keep saying that we've mentioned a number of those deals in the examples we've given. That's a large part of what our enterprise business is doing in particular. There's no particular change in Q1 compared to what we've seen in Q4 before. Q1 is we typically do a lot of larger deals in Q4 compared to Q1 seasonally in general. To the point you made earlier, we do see typically a bit of a lag between these big consolidation deals and the moment where we see our revenue recognized. Typically, when we consolidate products, what we'll see is we'll assume the ramp time for moving usage from other products to our platform over what can be a number of quarters or even years sometimes, and it might take some time for those numbers to materialize in the revenue. On the flip side, we also have a number of deals where customers are growing very quickly in their usage and we capture new commitments with them that might lag a little bit their consumption, and the revenue will be recognized. So we see a little bit of both. David, you want to speak a little bit more?

So we're growing sales capacity. We've been growing it for the past few years. We grew it a little more slowly last year as we were careful about profitability and not getting too far ahead of ourselves with a tough market, but we're definitely growing sales capacity. And there's a ramp model that is associated with that. So the capacity typically lags a little bit the growth in terms of headcount as it takes time for people to be productive, but we're investing, we're growing. And our long-term sales capacity is very much calibrated to revenue and growth. As Olivier mentioned, there are periods where it will move higher than that as we make investments, and there are periods where we might optimize. I think last year was a period where we digested previous investments, optimized a bit, and we said this year we're leaning into expansion of our sales capacity and investment. But long term, it correlates with revenue, and we look at whether we have enough sales capacity relative to what we see as the demand in the market, the territories, and the expected ARR growth. To give you just a bit more color, one of the big areas of focus inside the company is ramping up recruiting again. So we're recruiting a lot faster, a lot more than we were last year, and so we had to rev up that recruiting engine again. I want to congratulate our business recruiting team there for doing a fantastic job really bringing that engine back up.

Yeah, so it really depends on the product. Some products are extremely broad-based in terms of their appeal, and some others are really more directed at certain types of customers. For example, all products that have to do with monitoring physical networks tend to be more appealing to larger, older enterprises because they're the ones with large physical footprints. Whereas products like cloud cost management, for example, or even database monitoring, have very, very broad appeal because every single customer cares about their cloud cost, and every single customer is using databases that are at the center of their applications and that are absolutely critical to understand. And we mention those products because we see that as our efforts paying off in terms of broadening the offering and investing in R&D, and these are green shoots that we expect to grow into the future. Some of those products we have extremely high expectations for because they correspond to very large categories which we think can be very meaningful to the business in the long run. Some others are surprising us a little bit. That's why we mentioned database monitoring. We were not sure if it was going to be a huge category in cloud environments, but it turns out not only is there a very big problem customers need us to solve there, but also this product hit that problem on the head from day one really, and we expect now a lot more from it.

Yeah, for us to be successful, there are two factors that are needed. First one is cloud adoption needs to happen because we can't run it really, and the second one is we need to deploy sales capacity and grow sales capacity. And that's really the combination of the two. In most markets today, cloud adoption is happening. There are still maybe a few holdouts that are slower, but we're not yet deploying enough sales capacity everywhere, and that's one of our big areas of focus as I mentioned earlier.

Yeah, again, I bring it back to what I was saying earlier. A big focus internally is recruiting and making sure that we go fast enough there. I would say one more thing: last year when the market was slowing down, most of our peers laid off their recruiting teams, and we didn't do that because we knew we need to rev up the recruiting engine back up and grow the engineering and the sales team fast enough for us to go after the gigantic market opportunity we have. So we are very happy we haven't done that, but we still have a lot of work to do to recruit enough of the right people fast enough.

On the first question, we see a lot of interest in these new products. These are new products. We just announced in GA the event management product, which is the main missing building block we had for a full AIOps platform, and we also just released into GA Bits AI for incident management. So there's a lot of demand for it. The products actually, I will say for Bits AI for incident management, it's a joy to use, so that's great. But you should also expect to hear more from us on that topic in the next couple of months, so this is all very exciting. On the tooling, I would say there's a handful of players that have been building that tooling for a few years in a way that's very specialized to what they do internally. They're not necessarily very representative of the bulk of the market. So in those situations, we're always careful about overfitting products to a group that might not be the right target customer group in the end. In the same way that building infrastructure monitoring for the cloud providers to use internally might not be an exact fit for what the rest of the world needs. That being said, we work a lot with those companies, and they have a number of needs that some of them they can meet internally and some of them they don't. If I go back to the example of hyperscalers, we actually have teams at the hyperscalers that use us for application or infrastructure or logs internally even though they've built a lot of that tooling themselves. So I think everything's possible in the long run, but our focus is really on the vast majority of the customer base that's going to either use those API-based products or tune and run their own models.

Yeah, so I'll start with Amit, our president. Amit wanted to stop working as a full-time operator but wants to stay close to the company, and we want to stay close to him too. It's been, as you pointed out, a big part of the Datadog story, and we definitely want to keep him involved in the company and keep working with him. So the plan is for him to join the board. You should expect him to maybe reappear at some point as a VC investor, something that's less operational than what he's doing today, and we expect him to be a part of the company for the future as well. I will say I will miss him every day in the office.

Yeah, so look, everything's on the table for us. We're very busy on the M&A side. We have a team that is at any point in time reviewing multiple deals, and everything's possible. I would say the larger the acquisition, the less likely it is to happen because we're extremely selective in terms of not only the economics of any deal but also the fit and whether we think it is truly going to accelerate us in the mid to long term. But everything's possible. We are very fortunate to have a very efficient business, as you pointed out, that is generating quite a bit of cash now, and that opens a number of doors for us, and we fully intend to use that if we have the right opportunity.

Look, first of all, I'm not sure this is a metric we'll keep bringing up. I mean, it was interesting for us to look at this small group of early AI-native companies to get a sense of what might come next, knowing the world of AI. But I think as time goes by and as AI adoption broadens, I think it becomes less and less relevant. But the one thing I will say is we try to compare our exposure to AI to what we see from the hyperscalers, because they are upstream from us in that respect. The hyperscaler that is the most open or transparent about it in terms of numbers is Microsoft, as they disclose how much of their growth comes from AI more specifically. And I will say that if you compare our business to theirs, the AI part of our business is growing faster than Azure itself, and the AI-driven part of our Azure business itself is also growing faster than what you see on the overall Azure number. So we think we have similar exposure and we track to the same trends broadly. The other top providers are not as forthcoming with metrics, so it's harder to do a direct comparison, but in the longer term, we expect the same trends to apply.

So I mean, yes, the number of customers going up faster than it was the past few quarters. I would say it's hard to read too much into it because we have a large number of smaller customers, and there's more variability in the number of those smaller customers we get and we lose at any point in time, without really having a very large impact on the business. So I wouldn't read too much into that. I will say that the trends of all in customer acquisitions and retentions are good. Another number we reported on which I think is worth mentioning is we saw also a higher number of customers above $100,000 across that mark, and that's a return to the mean of what we had seen before. I think last quarter's number was a little bit lower, and it really shows what we said last quarter, which is that customers are growing on that revenue curve, and sometimes there are little peaks and valleys in the distribution of customers across the revenue curve for us. But overall, the motion is still the same: customers are landing, they're small, and they're growing, and they're getting bigger, and as a result, we're getting a larger and larger number of customers above $100,000, above a million, and driving the major revenue.

Yeah, the news are pretty good on these new packages. Again, we want to wait to have seen them in the market for a few quarters before we comment too much on those, but the uptake is good. They seem to resonate well with customers, correspond to the right need, and they're fairly easy to insert into the sales process, so all that is good news so far. I realized we didn't put too much into the script on security. We actually have a few things coming out as there is RSA this week in San Francisco, and our team there is there to meet with customers. One of the new pieces of functionality we announced last week was the agentless scanning for infrastructure security products, which we think is going to help a lot of customers deploy the product much more broadly, much more quickly. So we're very excited about that. It's in beta right now. And overall, the same trends we've been discussing last quarters are still true: thousands of customers buying on security, revenue growth, growth on a number of different pillars at the same time, which is very exciting and really speaks to our platform approach for security as well.

Yes, there's definitely opportunities there. We spoke in the script about some of the advanced query functionalities we're adding to logs, we spoke about Flex Logs. So those are all geared towards going after this opportunity. And we think also there's more specifically an opportunity around SIEM workloads, which is why we're investing heavily in our cloud SIEM product. So we think there's definitely a lot of opportunity there, and the teams are very focused on that. I don't expect these opportunities to make a big dent in our numbers in the next couple of quarters, but in the next year or so, definitely we expect to see more.

All right, thank you. So again, I want to thank the whole team for what was a great quarter. And I know many of our customers and users are listening to the earnings call, so I want to make sure everybody knows we're having our Dash conference in June in New York. You can go to dashcon.io, and we really look forward to seeing you there. So thank you all.