Datadog, Inc. (NASDAQ:DDOG) Q3 2023 Earnings Call Transcript

Datadog, Inc. (NASDAQ:DDOG) Q3 2023 Earnings Call Transcript November 7, 2023

Datadog, Inc. beats earnings expectations. Reported EPS is $0.45, expectations were $0.34.

Operator: Good day, and thank you for standing by. Welcome to the Third Quarter 2023 Datadog Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker’s presentation, there will be a question-and-answer session. [Operator Instructions] Please be advised that today’s conference is being recorded. I would now like to hand the conference over to your speaker today, Yuka Broderick, Vice President of Investor Relations. Please go ahead.

Yuka Broderick: Thank you, Dee. Good morning, and thank you for joining us to review Datadog’s third quarter 2023 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pomel, Datadog’s Co-Founder and CEO; and David Obstler, Datadog’s CFO. During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the fourth quarter and the fiscal year 2023, and related notes and assumptions, our gross margins and operating margins, our product capabilities, our ability to capitalize on market opportunities, and usage optimization trends. The words anticipate, believe, continue, estimate, expect, intend, will, and similar expressions are intended to identify forward-looking statements or similar indications of future expectations.

These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our form 10-Q for the quarter ended June 30th, 2023. Additional information will be made available in our upcoming form 10-Q for the fiscal quarter ended September 30th, 2023 and other filings with the SEC. This information is also available on the Investor Relations section of our website along with a replay of this call. We will also discuss non-GAAP financial measures which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com.

With that, I’d like to turn the call over to Olivier.

Olivier Pomel: Thanks, Yuka, and thank you all for joining us this morning. We are pleased with our execution in Q3, as we delivered another quarter of profitable growth and robust new logo bookings, and we continue to broaden our platform to have customers become and grow digital businesses. Let me start with a review of our Q3 financial performance. Revenue was $548 million, an increase of 25% year-over-year and above the high end of our guidance range. We ended with about 26,800 customers, up from about 22,200 last year. We ended the quarter with about 3,130 customers with an ARR of $100,000 or more, up from about 2,600 last year. And these customers generated about 86% of our ARR. And we generated free cash flow of $138 million with a free cash flow margin of 25%.

Turning to platform adoption. Our platform strategy continues to resonate in the market. As of the end of Q3, 82% of customers were using two or more products, up from 80% a year ago, 46% of customers were using four4 or more products, up from 40% a year ago, and 21% of our customers were using six or more products, up from 16% last year. Now let’s discuss this quarter’s business drivers. In Q3, we saw usage growth of existing customers improve compared to Q2. Overall growth in Q3 was relatively consistent throughout the quarter and comparable to levels we’ve seen in Q1. We are seeing signs that the cloud optimization activity from some of our customers may be moderating. As a reminder, last quarter, we discussed a cohort of customers who began optimizing about a year ago, and we said that they appear to stabilize their usage growth at the end of Q2.

That trend has held for the past several months, with that cohort’s usage remaining stable throughout Q3. Overall, we continue to see impact from optimization in our business, but we believe that the intensity and breadth of optimization we’ve experienced in recent quarters is moderating. Meanwhile, our new logo activity has remained robust. New logo bookings continue to scale and grow year-over-year. And for the second quarter in a row, we closed a record number of new deals with more than $100,000 in annual commitments. With our land and expand model, we expect new logos to turn into much larger customers over time as they lean into the cloud and add up more of our products. Finally, regarding customer growth, we are pleased with the new logos, new workloads, and new product [indiscernible] we added this quarter.

We added a number of exciting new customers in Q3, and I’ll discuss a couple examples later. Note, that our total customer count is largely driven by our long tail of very small customers, while our sales motions are more targeted to the middle and high end of our prospects. And as a reflection of our team’s strong execution, our net ads of customers over $100,000, saw an increase in Q3 compared to Q2. Despite a more cost-conscious demand environment over the past year, our business has continued to grow across product lines, and we are very proud to achieve several key milestones. First, our infrastructure monitoring ARR exceeded $1 billion. Today, our infrastructure products cover monitoring the performance of hosts, networks, containers, Kubernetes deployments, serverless functions, and other aspects of infrastructure in the cloud, as well as a full set of AI and machine learning tools to help our customers separate signal from noise.

Second. Our APM suite, which includes core APM, synthetics, real user monitoring and continuous profiler exceeded $500 million in ARR. And we continue to expand our capabilities in APM, most recently with single step instrumentation, which allows a single engineer to enable APM across all applications without code changes and we achieved advances in mobile app monitoring, including mobile application testing and mobile session replay. Third, our log management product exceeded $500 million in ARR. We also continue to expand our capabilities in log management, and with Flex logs, customers can easily scale storage and compute separately, allowing for new and very high-volume logging use cases in a cost-effective manner. From the very beginning, my Co-Founder [Alexi] (ph) and I had a vision to create a unified platform that serves end-to-end use cases across datasets, products, and team boundaries.

We believe that these ARR milestones and their balance across the three pillars of observability demonstrate that Datadog is unique within the industry in establishing true platform value for customers. And of course, even though these products have become significant in size, we are only just getting started. We will continue to innovate to deliver more solutions for our customers across observability and beyond. I will add that we have empathy for our customers and their pain points, in part, because we are ourselves users of cloud and next-gen technologies at a meaningful scale. And we extensively deploy a new [indiscernible] solution, which is appropriately known as dog fooding. As an example, we have extensively relied on our cloud cost management product as we expanded its capabilities this past year.

And the use of our product has played a large role in delivering cost, performance, and efficiency improvements, optimizing our own cloud usage, and ultimately resulting in expansion of our gross margins in recent quarters. We also continue to innovate in the DevSecOps space. Our recent expansions in cloud security include Cloud Sim investigator, where customers can visualize logs over long periods of time to conduct security investigations. And within our cloud security management product, we have introduced Cloud Infrastructure Entitlement Management, or CIEM, to help customers prevent identity and access management security issues. For a few years now, the industry has been talking about the idea of DevSecOps, the breaking down of silos among development, operations, and security teams.

And we entered the security space on the premise that DevOps and security teams should share the same data in the same platform. So starting this month, we are making the practice of DevSecOps easy to adopt for all customers by bringing together all the components needed to fully monitor and secure their entire stack with two simple packages. First, with infrastructure DevSecOps, our customers can observe and secure their entire cloud environment in one package. With a simple per-host price and a single agent deployed, customers get end-to-end visibility into performance, availability, and security issues in one place. And from that one place, teams can also quickly remediate problems using built-in workflows and without any code or configuration changes.

Second, with APM DevSecOps, we take this one step further. Customers can instrument cloud applications for both performance and vulnerability issues in one single package, enabled with the same unified agent used for Infrastructure DevSecOps. APM DevSecOps complements Infrastructure DevSecOps by surfacing open-source and code level security vulnerabilities alongside performance issues. Finally, we continue to be excited about the opportunity in generative AI and large language models. First, we believe adopting next-gen AI will require the use of cloud and other modern technologies and drive additional growth in cloud workloads. So we are continuing to invest by integrating with more components at every layer of the new AI stack and by developing our own LLM observability products.

And while we see signs of AI adoption across large parts of our customer base, in the near term, we continue to see AI-related usage manifest itself most accurately with next-gen AI-native customers, who contributed about 2.5% of our ARR this quarter. In the mid to long term, we expect customers of all industries and sizes to keep adding value to their products using AI and to get their early exploration — to get from early exploration to development and into production, thus driving larger cloud and observability usage across our customer base. Besides observing the AI stack, we also expect to keep adding value to our own platform using AI. Datadog’s unified platform and purely SaaS model, combined with strong multi-product adoption by our customers, generates a large amount of deep and precise observability data.

We believe combining AI capabilities with this broad data set will allow us to deliver differentiated value to customers. And we are working to productize this differentiated value through recently announced capabilities such as our Bits AI assistant, AI generated synthetic tests, and AI-led error analysis and resolution. And we expect to deliver many more related innovation to customers over time. Let’s move on to sales and marketing, where we continue to execute on both new logos and existing customers. So let’s discuss some of our wins. First, we signed a seven-figure land over five years with a leading provider of dental care. This company’s legacy monitoring just didn’t cut, and it contributed to delays with their migration to Azure. What concerned them was that, customers noticed poor application performance and were complaining publicly on social media.

By adopting six Datadog products, they expect to find and fix the vast majority of incidents internally before their customers are affected. And in signing a five-year deal, this customer showed its confidence in Datadog as a long-term partner in their migration. Next, we signed a seven-figure land with a South American FinTech company. By moving from basic, built-in cloud monitoring, legacy tooling, and open-source tools to Datadog, this customer expects to significantly reduce costs by spending less on tooling, reducing time to resolution, and giving time back to engineers to innovate on their own products. Next, we signed an eight figure running all over three years with a major American chain of convenience stores. With this expansion, Datadog will bring all aspects of these customers’ tech systems into one platform, including their application, hybrid clouds, network, in-store IoT technology, point of sale systems, self-serve kiosks, fuel pumps, and corporate infrastructure.

This will free up employee time to focus on customer service with expectations to save millions of dollars annually. This customer plans to use six Datadog’s products, replacing three commercial observability tools. Next, we signed a seven-figure expansion with a major US federal agency. When we first started working with this customer a year ago, Datadog was approved for a limited subset of programs. But as we have demonstrated value and gained internal adoption, this customer is now deploying Datadog across the entire agency. They have adopted six Datadog products, and by doing so, consolidated out of seven tools. Next, we found a seven-figure expansion with a Fortune 500 industrial company. Customer was concerned with out of control costs with its legacy log management products and was using a dozen of different tools.

And when they began using Datadog, they noticed far fewer support tickets submitted to their reliability team. By growing usage with Datadog and expanding to seven products, this customer expects to deliver better service while saving time and reducing costs. And last, we signed a seven figure expansion with a software business that is part of a tech hyperscaler. This long-time customer has used Datadog for infrastructure metrics and will now expand to adopt seven Datadog products. Datadog will be replacing its commercial APM tool, which wasn’t well adopted by its engineers and led to inefficient troubleshooting, outages, and revenue impact. Our support of OpenTelemetry in particular was key to their decision to expand with Datadog as it makes it possible for APM tracing to be democratized and used across their entire DevOps team.

And that’s it for this quarter’s highlight. I’d like to thank our go to market teams for their strong execution in Q3. Before I turn it over to David for a financial review, let me reiterate our longer term outlook. As we have said throughout this period of cloud optimization and macro uncertainty, our long-term plans have remained unchanged. We continue to believe digital transformation and cloud migration are long-term secular growth drivers of our business and critical motions for every company to deliver value and competitive advantage. So we continue to invest aggressively to broaden our platform and we aim — sorry, and we aim to be our customers mission critical partners as we move to cloud and to modern DevSecOps. With that, I will turn it over to our CFO, David.

David Obstler: Thanks, Olivier. Q3 revenue was $548 million, up 25% year-over-year and up 7% quarter-over-quarter. To dive into some of the drivers of this Q3 performance, first regarding usage growth. We saw an improvement in usage growth in Q3 versus Q2. The Q3 usage growth was more similar to Q1 and relatively steady throughout the quarter. We had a very healthy start to Q4 in October. While it is too early in the quarter to know for sure what will happen in the next couple of months, the trends we see in early Q4 are stronger than they’ve been for the past year. Regarding usage growth by customer size, we continue to see larger spending customer growth at a slower rate than smaller spending customers, but usage growth improved for all customer sizes in Q3 relative to Q2.

And as Olivier discussed, we believe there are signs that the optimization activity we’ve been seeing is moderating. Last quarter, we discussed the cohort of customers who started optimizing about a year ago. This cohorts usage has been stable — was stable throughout Q3. As we look at our overall customer activity, we continue to see customers optimizing, but with less impact than we experienced in Q2, contributing to our usage growth with existing customers improving in Q3 relative to Q2. While we expect cost management to continue, we believe we are seeing moderation that is still present, but is less intense and less widespread than we experienced in recent quarters. Geographically, we experienced similar sequential revenue growth in North America and in our international markets.

And finally, as regard to retention metrics, our trailing 12 month net revenue retention was in line with our expectations and came in slightly below 120% in Q3. Our trailing 12-month gross revenue retention continues to be stable in the mid to high 90s, a sign of the mission critical nature of our platform for our customers. Moving on to our financial results. Billings were $607 million up 30% year-over-year. Billings duration increased slightly year-over-year. Remaining Performance Obligations, or RPO, was $1.45 billion, up 54% year-over-year. Current RPO growth was about 30% year-over-year. Over the past couple of quarters, we have seen an increasing preference from our customers to sign multi-year deals, and our weighted average booking duration was up sequentially and year-over-year.

We see continued interest in multi-year duration deals in our pipeline as customers seek longer term strategic partnerships with us. We continue to believe that revenue is a better indicator of our business trends than billings and RPO, as those can fluctuate relative to revenues based on the timing of invoice and the duration of customer contracts. Now let’s review some of the key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. Gross profit in the quarter was $451 million, representing a gross margin of 82.3%. This compares to a gross margin of 81.3% last quarter and 79.7% in the year ago quarter. As Olivier mentioned, we continue to experience efficiencies in cloud costs reflected in our cost of goods sold in the quarter, as our engineering teams pursue cost savings and efficiency projects.

Our Q3 OpEx grew 17% year-over-year, this is a decline from 26% year-over-year growth last quarter. We continued to execute on controlling costs given the uncertain environment. And Q3 operating income was $131 million for a 24% operating margin, up from 21% last quarter and above the 17% in the year-ago quarter. Our margins were higher than we expected in Q3 as our organic growth was higher than in Q2, while our internal optimization and cost management efforts were successful. Turning to the balance sheet and cash flow statements, we ended the quarter with $2.3 billion in cash, cash equivalents, and marketable securities. And cash flow from operations was $153 million in the quarter. After taking into consideration capital expenditures and capitalized software, free cash flow was $138 million for a free cash flow margin of 25%.

And now for our outlook for the fourth quarter and for the full fiscal year 2023. A reminder, our guidance philosophy remains unchanged. We base our guidance on trends observed in recent months and apply conservativism on these growth trends. For the fourth quarter, we expect revenues to be in the range of $564 million to $568 million, which represents about 20% to 21% growth year-over-year. Non-GAAP operating income is expected to be in the range of $129 million to $133 million. And non-GAAP net income per share is expected to be $0.42 to $0.44 per share, based on approximately 355 million weighted average diluted shares outstanding. For fiscal year 2023, we expect revenues to be in the range of $2.103 billion to $2.107 billion, which represents 26% year-over-year growth.

Non-GAAP operating income is expected to be in the range of $453 million to $457 million, and non-GAAP net income per share is expected to be in the range of $1.52 to $1.54 per share based on approximately 351 million weighted average diluted shares outstanding. Some additional notes for our guidance. First, we expect net interest income and net interest and other income for fiscal 2023 to be approximately $95 million. We expect tax expense in the fiscal year to be $12 million to $14 million. And finally, we expect capital expenditures and capitalized software together to be in the 3% to 4% of revenue range in fiscal 2023. And now regarding 2024. It is too early for us to speak to 2024 revenue growth. We will digest the information we see over the next several months and give you our 2024 revenue guidance next quarter.

As it relates to non-GAAP profitability, our operating income and margins were a little higher in Q3 than we targeted, as usage growth improved from Q2 levels and we were successful with our cost efficiencies. We expect continued strong execution on profitability in Q4. At the same time, we continue to be excited by our numerous long-term growth opportunities, and we have no shortage of investments to make and are confident in our ability to execute to strong ROI on those investments. As a result, while we are not providing 2024 margin guidance at this point, as always, we will balance our investments in long-term growth with margin discipline. And we will update you on that in more detail next quarter. With that, we will open the call for questions.

Operator, let’s begin the Q&A.

Operator: Thank you. [Operator Instructions] Our first question comes from Mark Murphy of JP Morgan.

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Q&A Session

Mark Murphy: Thank you very much and congratulations on a very strong performance. Olivier, I’m interested in your mention of 2.5% of ARR being driven by the native AI providers. Should we think of that mostly consisting of OpenAI, LLaMA, Anthropic, Coherent, et cetera, or are you meaning that as a slightly different reference? Can you just help us understand, is that up from close to zero a year ago? Then I have a quick follow-up.

Olivier Pomel: Yeah, so it’s a number of companies that — without naming anyone, so they tend to be model providers, but not just on the language side, like model providers on the language, image side, like there’s a number of different — or video side, there’s a number of different types of companies, even some good copilot type companies. These customers all had revenue one year ago, but they’ve been growing a little bit faster than the rest of the customer base recently. The reason we should be [indiscernible] in this space is, today we see the usage growth related directly to AI coming mostly for these customers that provide models to others. Whereas we see broad usage of AI functionality across the customer base, but at low volumes. And it corresponds to the fact that for most customers or most enterprises really, they’re still in the early stages of developing and shipping AI applications. So for now, the usage is concentrated among the model providers.

Mark Murphy: Okay. Yeah. That makes sense. And Olivier, as a quick follow up, you mentioned that log management has crossed $500 million in ARR. It’s quite a milestone. You also mentioned the replacement of some legacy products. I’m curious if you see the acquisition of Splunk or any other acquisition activity in that market as a beneficial development. Just wondering if Splunk customers or other companies that have been provided — that have been acquired – excuse me, might be looking for any alternatives out there that are more modern and a more converged platform and if you’re seeing that in the pipeline.

Olivier Pomel: We’ve seen that for a while now that new customers were looking for more integrated platforms, more modern offerings, things that were more cloud-first. And that’s been one of the reasons of our success in the landing largely in brand new applications, brand new environments, brand new cloud initiatives, and then over time consolidating our customers away from whatever they were using in the legacy. We don’t think that it is going to change with the various acquisitions and tech privates that we’ve seen over the past quarter. So we think we’ll just see more of that over time. One extra thing on your first question, one interesting tidbit if you — as I know many of you are trying to understand what the AI landscape is made of.

Interestingly enough, when we look at our cohort of customers that are considered to be AI native and built largely on AI and [indiscernible] AI providers, they tend to be on different clouds. What we see is that, the majority of these companies actually have a lot of their usage on AWS. Today, the larger part of the usage, the larger of these customers are on Azure. So we see really several different adoption trends there that I think are interesting to the broader market.

Mark Murphy: Thank you for that insight, I appreciate it.

Operator: Thank you. One moment for our next question. And our next question comes from Sanjit Singh of Morgan Stanley.

Sanjit Singh: Thank you for taking the questions. Olivier, the company has been innovating throughout this downturn quite aggressively across core observability, security, as well as AI. As we look into 2024 and we think about a potential new product cycle for Datadog. What parts of the portfolio do you think could be contributors either in 2024, later in 2024 and in 2025? What are the things that you think the customers will be most receptive to? Just wanted to get a sense of where you think — where the sort of timing of some of the new products that you’ve been delivering over the past couple of years?

Olivier Pomel: Well, mathematically, the products that would contribute the most to the growth next year are going to be the products that have been here the longest and the core observability products. We mentioned $1 billion in infrastructure, $0.5 billion in APM, $0.5 billion in logs. This is great, but still a small fraction of these products can be at scale and we’re primarily going after that. There’s a number of other things we’ve been investing in and growing and we’re fairly happy with the way things are going in security, as I mentioned on the call, with some new packaging we’ve also rolled out and some of the new initiatives that stand, I would say, a little bit left or right of what we’ve been doing in observability.

This year, as you mentioned, was a year of innovation for us. I think it was also a year of cost optimization for customers. It’s not necessarily the best year to get products to very quick — extremely quick revenue growth. But we’ve planted a lot of seeds that we think are going to deliver in the next couple of years.

Sanjit Singh: That’s Great. And I had a sort of follow-up question on the sort of new packaging for the DevSecOps, the two new package. I was wondering if you could give us a little bit of color around why you sort of went with the packaging approach and what you’re trying to solve for? Is it sort of trying to adopt the capabilities in a single integrated capability? Or is it also about sort of consolidated pricing, paying potentially one skew price to consume all these capabilities? So just loves some detail around the motivation for these new packages.

Olivier Pomel: Yes, a couple of things. So the first one is, our security products have reached a certain level of maturity, so we think they can be brought into the conversation with a larger set of our customers as opposed to being something that our customers self-select to, which is how we started and how we start with most products really. But also we’re trying to bring those products in the same conversation as the initial adoption of DevOps, basically, as opposed to having to branch that conversation into, oh, hey, you’re doing operations and applications, and can I interest you in some security with that, which would be a different conversation. So, we — so far, the signs for this are encouraging, and again, we think it goes with the broader market trends, the adoption of DevSecOps, and what customers actually want to do, and what we think is going to help them deliver better outcomes in security.

But obviously, we just rolled that out. So it’s still too early to tell whether we got it right or whether we still need to tweak it a little bit.

Sanjit Singh: Appreciate the thoughts, Olivier. Thank you.

Operator: Thank you. One moment for our next question. And our next question comes from Raimo Lenschow of Barclays.

Raimo Lenschow: Hey, thank you. Congrats from me as well. Olivier, we’re almost a year into this kind of current situation and you saw — Q2, obviously, saw the digital natives that you commented just kind of having extra savings, but we’re now back to kind of Q1 usage patterns. What do you see in terms of changing behavior on customers, not thinking [indiscernible], but more like how do you think about observability and how that potentially would change the world as we think about 2024, 2025 coming out of this in terms of vendor consolidation, how to build observability, et cetera. And then I have one follow-up for David. Thank you.