DigitalOcean Holdings, Inc. (NYSE:DOCN) Q1 2024 Earnings Call Transcript

DigitalOcean Holdings, Inc. (NYSE:DOCN) Q1 2024 Earnings Call Transcript May 10, 2024

DigitalOcean Holdings, Inc. misses on earnings expectations. Reported EPS is $0.1508 EPS, expectations were $0.38. DOCN isn’t one of the 30 most popular stocks among hedge funds at the end of the third quarter (see the details here).

Operator: Thank you for standing by and welcome to the DigitalOcean First Quarter 2024 earnings conference call. All lines have been placed on mute to prevent any background noise. After the speakers remarks, there will be a question-and-answer session. [Operator Instructions] I would now like to turn the call over to Rob Bradley, Vice President of Investor Relations. Please go ahead.

Rob Bradley: Thank you, Rochelle. And good morning. Thank you all for joining us to review DigitalOcean’s first quarter 2024 financial results. Joining me today are Paddy Srinivasan, our Chief Executive Officer, and Matt Steinfort, our Chief Financial Officer. After our prepared remarks, we will open the call to a question-and-answer session. Before we begin, let me remind you that certain statements made on the call today may be considered forward-looking statements which reflect management’s best judgment based on currently available information. I refer specifically to the discussion of our expectations and beliefs regarding our financial outlook for the second quarter and full year 2024. Our actual results may differ materially from those projected in these forward-looking statements and direct your attention to the risk factors contained in the company’s 10-Q filed with the Securities and Exchange Commission and those referenced in today’s press release that is posted on our website.

DigitalOcean expressly disclaims any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements made today. Additionally, non-GAAP financial measures will be discussed on this conference call and reconciliations to the most directly comparable GAAP financial measures are also available in today’s press release as well as in our updated investor presentation that outlines the financial discussion in today’s call. A webcast of today’s call is also available on our website in the IR section. With that, I’d like to turn the call over to our CEO, Paddy Srinivasan. Paddy?

Paddy Srinivasan: Thank you, Rob. Good morning, everyone. And thank you for joining us today as we review our first quarter results. After my first three months in the role, I’m pleased with both the solid execution and durable growth we delivered in Q1 and the early progress we are making to position the company to take advantage of the material growth opportunities that are in front of us. In my remarks today, I will briefly highlight our first quarter results, share some initial observations from my first 90 days, provide several examples of our increasing product velocity, and discuss our progress pursuing the tremendous AI growth opportunity. Before I get too deep into my remarks, I want to highlight our Q1 performance, which was solid across the board.

Revenue growth accelerated quarter-over-quarter, and we continue to deliver strong adjusted EBITDA and free cash flow margins while increasing investments in our higher growth businesses, demonstrating the strength of our business model. We are also encouraged by the improving growth fundamentals. Net dollar retention continued to slowly rise from our low last summer, increasing as expected to 97%. Our core product usage grew faster in Q1 than it did in Q4 of 2023. And we’re also seeing strong uptake of our still early stage AI and machine learning platforms. While we still have a lot of work ahead, our Q1 results are very encouraging. Matt will walk you through more of the details later in this call. I will start my deeper commentary with some initial observations after my first quarter as CEO.

I’ve spent a meaningful portion of my first 90 days with customers, partners, and employees. The feedback and insights I have received have only increased the excitement and optimism I have for DigitalOcean and our growth potential. More than anything, I’ve been thrilled with the positive and constructive feedback that I’ve gotten from our customers. We have an incredibly loyal customer base that relies on DigitalOcean to run their businesses, that want to do more with us as they grow, and they also have very clear feedback on how we can help them accelerate. Most of the builders and scalers on our platform run revenue generating software products on DigitalOcean and have come to know and love us for our simplicity, our valuable technical content, and our compelling price to value.

I’ve been actively engaging and listening to them, and they have helped validate some of the hypothesis that I have long held about this solution. Number one, that the market opportunity for cloud platforms is large and growing, and is only increasing with the advances of AI and machine learning technologies. Our customers are optimistic about their own long term growth prospects and are telling us that they see opportunities to expand their business with DigitalOcean. Our platform matches what growing technology businesses require, a scalable and performant platform, a platform which is simple to get started on and scales with them, a platform that is cost effective and more importantly provides transparency of ROI with robust technical support both directly from us and also from our passionate community of developers.

My conversations with dozens of customers offered key insights into the gaps in our platform and highlighted the emerging needs of our core target customer. This reinforces our mission, and we are going to continue to focus on product innovation and ensuring we delight our customers and the developer ecosystem. Their endorsement of DigitalOcean is powerful, and we will work tirelessly to earn and retain their business while attracting net new customers. With this backdrop, let me give you an update on what we’ve been working on recently. Over the past few weeks, we’ve made demonstrable progress accelerating our product innovation and the velocity of our new releases. Let me share a few highlights with you. First, we recently introduced turnkey data protection for our customers by launching daily Droplet backups.

In true DigitalOcean fashion, to make it super simple for developers, this capability enables one click Droplet data protection, providing peace of mind from accidental deletion through automatic retention of the seven most recent copies. In parallel, we also improved the speed of our snapshots capability by up to 6x, enabling customers to back-up even larger droplets much faster than before. While it is still early days, we are seeing robust adoption from both existing and new customers, enabling daily backups. We have already seen more than 1,300 new customers enabling daily backups and 150% month over month increase in overall droplets being backed up daily just between March and April of this year. We also rolled out new additions to our premium Droplet offerings, expanding these premium options to memory and storage optimized families.

With high-performance, non-volatile memory express, SSDs, and 5x increased networking throughput over regular droplets alongside our flexible egress bandwidth allowance, these new memory and storage optimized droplets are ideal for memory, data, network, and bandwidth intensive workloads. We are very excited for the potential they will offer to new and existing customers across a variety of use cases like caching, databases and many others as they get ramped up. Also in Q1, we introduced horizontal scaling for Managed Kafka, continuing our focus on making the complex simple for our customers. Horizontal scaling for Kafka is particularly critical for our customers who manage large volumes of streaming data and want to prioritize scaling bandwidth and highly performant end user experiences.

This facilitates right provisioning of nodes in support of fluctuating workload requirements, enabling customers to handle spiky data volumes and traffic, improve the reliability of their clusters and optimize their resources. A few other notable releases we are excited to highlight since our last call include a series of app platform improvements such as CPU-based auto-scaling and dedicated egress IP support from our platform. Turning into our managed hosting cloud-based offering, in January, we were proud to launch cloud-based Autonomous. With a few months in market now, the initial feedback from customers and community has been very positive with over 650 customers adopting the new capability today. Alongside Autonomous, we shipped a number of other crucial items to simplify and secure our managed hosting offering for our customers.

These include DNS Made Easy to simplify DNS management for users, an integration with Patchstack to provide an extra layer of vulnerability detection and alerting, and most recently in April, client billing, the first tool launched for our planned Agency Suite that will automate and streamline various agency workflows to enable simpler, more efficient, and more agile operational support to help our agency customers grow on the DigitalOcean platform. More to come on this throughout the rest of this year. These examples are just a few highlights from the list of capabilities we continue adding in our mission to simplify the cloud for our customers. We will continue to listen closely to our customers and strive to accelerate our delivery velocity to ensure our customers are positioned for success as they grow on our platform.

We know that when our customers win, we all win. And our focus remains squarely on delivering a rapid cadence of new releases aimed at delighting our customers, enabling them to scale their businesses, and ultimately increasing our net dollar retention. Before turning it over to Matt, I would like to share some updates on what we’re seeing across the AI landscape. It is an exciting time in AI, and you can see that every day in the headlines that you read. Companies across virtually every vertical that you can imagine are eager to incorporate AI into their value proposition. While large language models or LLMs get most of the headlines, we’re learning that our target customers, many of which are software vendors, are looking to consume a variety of different AI models into their offerings, like fraud detection, sentiment analysis, natural language processing, live translation, demand forecasting, and of course, LLM based models like image and video generation, coding assistance, Q&A bots, and many more.

We’re seeing strong revenue growth for our early stage AI solutions as we continue to ramp up our initial GPU capacity through the first part of this year. And our expectations are that demand will continue to outstrip supply for the foreseeable future. As of March, our ARR grew to $19 million, most of which is our platform-as-a-service offering, a 128% annualized increase from December 2023, driven by demand for both AI model training and consumption of models, also known as inferencing. In addition to our existing AI platform-as-a-service that helps AI and machine learning developers consume a variety of open source models, we also launched our GPU based infrastructure as a service offering in January of 2024, and are seeing strong traction with GPU hours sold and consumed increasing 67% just from March to April of this year.

The growing customer base for our AI infrastructure-as-a-service offering are both venture backed startups as well as established businesses. Over the last four weeks, we have onboarded several customers that came to us for our availability, simplicity, and support. Customers are using our AI platform-as-a-service and infrastructure-as-a-service platform for a variety of use cases, including text and video generation, AI coding co-pilots, recommendation algorithms, model hosting services, and many more. Let me give you a couple of concrete examples. First is a venture-backed customer that is a leading AI-driven storytelling platform that helps build marketing storyboards, visual manuals for complex products, and comics, all from textual prompts.

Another customer example is an AI assistant tool that developers leverage to code with greater speed, flexibility, and accuracy. These are just two new examples of customers that we have seen this year as the AI market continues to quickly grow and evolve. I’ve spent a significant portion of my time and attention in my first 90 days working directly with these customers to understand their needs deeply and translate that into our longer term AI strategy. Our customer needs, while similar, are quite distinct from the needs of large enterprise customers using hyperscalers or large language model builders who use the raw infrastructure from GPU form providers. To put this in perspective, over a decade ago, DigitalOcean identified and delivered an innovative compute solution with a clear product market set that was not being effectively addressed by the larger cloud providers, creating an easy on-ramp for developers, startups, and entrepreneurs to learn, test, and scale their businesses by simplifying cloud computing.

We see a similar opportunity emerging now to democratize the access to AI and machine learning capabilities, not only by providing simple access to GPU capacity via infrastructure as a service, but also by integrating AI and machine learning into the developer experience itself to transform how developers build and run their workloads on our platform. Like many cloud platform providers, we are simultaneously turning up incremental capacity to meet near-term demand, while also rapidly learning and evolving our AI strategy. While we are certainly in the very early innings of this transformative growth opportunity, we continue to believe that software, more than hardware, will be DigitalOcean’s long-term differentiator and competitive advantage, especially for our target customers.

We are confident in the strategic direction we are taking and believe that AI will be a meaningful growth contributor in 2024 and in the years ahead. We will make the right choices on investment this year as we continue to see positive results. We will share more on our plans on this front over the course of this year. To close my comments, I’m pleased with our performance in the early months of 2024, and I’m optimistic on our near and long-term growth potential. We have a very solid performance and growing core business. Our revenue growth accelerated quarter-over-quarter, NDR improved, and profitability and cash flow margins were all very healthy. We are accelerating our pace of innovation and delivering new capabilities in rapid cadence which will help our customers grow on our platform, thereby increasing our net dollar attention.

Our AIML solutions are resonating very strongly with our customers and we are working to turn up incremental capacity over the balance of the year to keep up with robust demand. There’s a lot of work to do to take full advantage of our opportunity, but we are moving in the right direction and continue to make steady, rapid, and respectable progress each quarter. I will now turn the call over to Matt to provide details on our financial results and on our outlook for Q2 and for the balance of the year. Matt?

Matt Steinfort: Thanks, Paddy. Good morning, everyone, and thanks for joining us today to review our first quarter results. Revenue growth continued to improve quarter over quarter. We are seeing positive signals from our key growth drivers and we continue to deliver attractive adjusted EBITDA and free cash flow margins while we increased investment in our AI platform to pursue this material growth opportunity. This morning, I will provide a deeper look into the first quarter results before providing our financial outlook for Q2 and for the full year. Revenue in the first quarter was $184.7 million, which was up 12% year-over-year and up sequentially from the fourth quarter of 2023. We added $19 million of annual recurring revenue, or ARR, in the quarter, which was the largest organic quarterly increase we generated since the second quarter of 2022 and was 82% higher than the incremental ARR we generated in Q1 2023.

Contributing to this growth was steady incremental revenue from new customers, improving net dollar retention from our existing installed base, and healthy contributions from our managed hosting and AI platforms. Revenue from new customers in their first 12 months remained both steady and a key element of our solid growth foundation in Q1. As we discussed in February, improving our net dollar retention or NDR is a major focus area and a key driver for accelerating our overall growth rate as we move through this year. As anticipated, NDR improved to 97% in Q1 and has continued to steadily increase since we reached our low point in July of [2023] (ph). We continue to see steady and historically consistent levels of churn and we are seeing modest month-over-month improvements in our net expansion which is expansion net of contraction as our customers are slowly returning to growth.

The work that we are doing on both accelerating our product roadmap and continuing to enhance our customer success motions should enable us to continue to increase our net dollar retention as we seek to remove it as a headwind and eventually return it to a tailwind to our overall growth. Our managed hosting product, Cloudways, another key growth driver, contributed revenue of $22 million in the first quarter and grew 34% year-over-year. While we will see a slower year-over-year growth rate from Cloudways as we lap the managed hosting price increase that we made in April of last year, we do anticipate managed hosting continuing to be one of our faster growing platforms for the foreseeable future. As Paddy described, we are still in the early innings with our AI and machine learning solutions.

But the rate of growth of both the leading indicators and our revenue on this new platform is already meaningful. Our AI and machine learning platform contributed $4 million in revenue in Q1, and we exited Q1 with AI ARR of more than $19 million, a 128% annualized increase. This strong growth came despite our being capacity constrained in the majority of the first quarter as we navigated supply chain challenges and turned up the first wave of servers that we had ordered in Q4 of 2023. We are consistently selling through our available capacity as it comes online and we saw our hours sold on each 100s increase 67% in April just over March in just a single month. We will continue to add the next waves of our planned incremental capacity over the balance of the year and anticipate that demand for our AI solutions will continue to be robust.

Turning to the P&L, gross margin was 61%, which was an increase from 56% in the first quarter of the prior year. The largest factors in this 500 basis point improvement were the success of our ongoing cost optimization efforts and/or having grown into infrastructure investments from prior periods. As is the nature of our business, incremental investments in equipment, space and power, and networking cause modest step function increases to cost of goods that are then smoothed as we fill the capacity with incremental revenue. Given our planned AI investments, we anticipate that gross margin will moderate somewhat in the coming quarters. Adjusted EBITDA margin was 40% in the first quarter, in line with the prior quarter, as we continue to diligently manage expenses.

Our healthy profitability in our core platform continues to provide us the flexibility to make additional investments in R&D to accelerate our product roadmap and to invest in our higher growth opportunities such as AI. Diluted net income per share was $0.15 and non-GAAP diluted net income per share was $0.43. GAAP and non-GAAP diluted earnings per share increased by $0.32 and $0.15 respectively on a year-over-year basis. While we have been cash flow positive since 2021, it is notable that we are now posting positive net income quarters on a GAAP basis, which is a further indication of the profitability of our core DigitalOcean business. Adjusted free cash flow margin was $34 million, or 19% of revenue, which was an improvement from 16% of revenue in Q1 of 2023.

As we have said previously, free cash flow margin is a more meaningful metric on an annual or trailing 12-month basis. And quarterly free cash flow margin will vary given the timing of capital spend and other working capital impacts. Turning to our customer metrics, average revenue per customer increased 8% year-over-year to $95.13. The number of builders and scalers on our platform, those that spend more than $50 per month, was 158,000, an increase of 8% year-over-year. Their revenue growth year-over-year was 13%, ahead of our overall growth rate of 12%. The number of builders and scalers on our platform, which represent 87% of our revenue, increased by 1,300 during the quarter. The increase in our higher spend and higher growth customers is a result of our focus and concentration of our marketing, product development, and customer success investments on these builders and scalers.

Along with the increase in our higher value customers, we did see total customer count decline by 7,400 quarter-over-quarter. This change was due to a reduction of 8,700 of our lowest spending customers, our learners, with that reduction collectively representing only around $100,000 a month of recurring revenue as the average spend for those customers was less than $10. Our balance sheet remains very strong as we ended the quarter with $419 million of cash and cash equivalents. During the first quarter, we leveraged our material cash balance and free cash flow to repurchase 200,000 shares of common stock for $8 million as part of our ongoing share buyback. Looking forward and building on our steady growth in Q1, we expect Q2 revenue to be in the range of $188 million to $189 million, representing 11% year-over-year growth at the midpoint of our guidance range.

For the second quarter, we expect adjusted EBITDA margins to be in the range of 37% to 38% and non-GAAP diluted earnings per share to be $0.38 to $0.40 based on approximately 102 million to 103 million in weighted average fully diluted shares outstanding. With improving NDR and the strong demand for our AI platform that we saw in Q1, we are increasing the bottom end of our full year revenue guide by $5 million, projecting revenue to be in the range of $760 million to $775 million for the year, a $2.5 million increase in the midpoint of our guidance range and representing year-over-year growth of 10% to 12% for the range. On the profitability side, we continue to drive operating leverage in our core DigitalOcean platform, enabling us to increase investment in our faster growing managed hosting and AI and machine learning platforms, while maintaining attractive overall margins.

We continue to execute the plan we articulated in February and continue to project our adjusted EBITDA margin for the full year to be in the range of 36% to 38%. We also maintain our forecast range for full-year adjusted free cash flow margin at this point. As we continue to see positive signals from our AI solutions over the balance this year, we will continuously assess whether to deploy additional capital to further accelerate our AI growth, which may result in reductions to our free cash flow margins to support that. We are also maintaining our non-GAAP diluted earnings per share guidance, which we expect to be in the range of $1.60 to $1.67. That concludes our prepared remarks and we’ll now open the call to Q&A.

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Q&A Session

Operator: Thank you. We will now begin the question-and-answer session. [Operator Instructions] Your first question comes from the line of Raimo Lenschow of Barclays. Your line is open.

Raimo Lenschow: Thank you. Congrats from me for a great quarter. First question on AI, if you think about the state or the evolution of AI adoption, there’s like training and experience, inference, sorry, and the — what are you seeing at the moment on the platform side, and how do you think that will kind of evolve for you? And then another question on NRR, if you think about it, it’s obviously a lagging indicator. Like, how do you think the weaker periods coming out, kind of impacting kind of NRR going forward? Thank you.

Paddy Srinivasan: Okay, great. Thank you for the question, Raimo. I’ll start with the AIML question and then I’ll let Matt chime in with the NRR question. So from an AIML perspective, as I said, it is very exciting traction, but I have to remind that we are in very early innings, not just at DigitalOcean, but as a market as a whole. So I think for us, we are super focused on the needs of our customers. And our customers are a little different, as I described in my prepared remarks. A lot of our customers are tech businesses that build and run software applications on the DO platform. And they need a variety of different AI models, not just LLMs. And they are mostly AI extenders. So if you take the example of LLMs that a lot of people are familiar with these days, you can inject data and fine tune and extend current AI models.

So that’s a lot of what our customers are looking to do, not just in LLMs, but in other models as well. And typically our customers are AI extenders and AI consumers. And our AI value proposition is twofold, as I explained. We have recently introduced the infrastructure-as-a-service. And the dominant use case right now is model building and model extension and fine tuning, and also model inferencing across different parts of our data center infrastructure. We also have a very robust platform-as-a-service offering with Gradient, a platform we acquired through Paperspace, which is also undergoing considerable enhancements as we speak. So this platform-as-a-service has a much wider aperture in the sense that it deals with AI and machine learning throughout the life cycle of software development.

So we have both that as well as the raw infrastructure-as-a-service to fine tune and build and train and infer these AI models. So as I said, we are very happy with the progress in Q1. We will be focused on serving our customer segment primarily with our AI strategy. And we feel very confident that we are now starting to really understand the evolving needs of our customers and what they’re actually looking for, both in model training and inferencing. And as I said, these are very early innings. A lot of attention is now on model building and fine tuning and training. But the long term use case is going to be super heavy on inferencing and we have both those phases covered with our platform-as-a-service and infrastructure-as-a-service.

Matt Steinfort: And, Raimo, on the net dollar retention, again, we’re encouraged by the, I’d say the steady — slow but steady increase in net dollar retention that we’ve seen, basically on a monthly basis from July of last year. And as we’ve said historically, the churn hasn’t really been the challenge for us over that period and even in the prior year. The issue had been net expansion, which is expansion minus contraction. And we’ve seen slow and steady improvement there, which is driving the improvement in NDR. Contraction continues to kind of get better, a little bit better every month. Expansion, again, was the last of our kind of drivers of NDR to hit the bottom last year. And it is holding steady at the levels it’s been over the last several months and we see positive indications.

But it’s, I’d say, going to be slow and steady growth for us to get that NDR up, and we’re encouraged by the progress that we’re making. And the product development work that Paddy described, and the heightened focus on the customer success, those all contribute to the improvements and we’re banking on only the things that we control, so those improvements. We’re not banking on any macro improvement or kind of market shift to higher growth in terms of what we’re guiding.

Raimo Lenschow: Okay, perfect. That makes a lot of sense. Thank you. Well done.

Operator: Your next question comes from the line of Pinjalim Bora with JPMorgan. Your line is open.

Pinjalim Bora: Oh, great. Thanks for taking the question, and congrats on the quarter. I want to ask you, Paddy, the AI strength is definitely palpable here, but I want to ask you if you are seeing attach rate of the core DigitalOcean offering as people create applications around the AI workloads? Is that flywheel AI driving more core DO starting to happen?

Paddy Srinivasan: Great. Good question, Pinjalim. Nice to hear from you. So the way I’m looking at it is that there are two ways that this cross sell or this cross attach happens. One, our DigitalOcean — traditional DigitalOcean core customers that are now starting to use our both platform-as-a-service as well as our infrastructure to consume some of the AI models that I was talking about. So it is still very early, but we have a handful of examples of some of our top customers that are trying to leverage our infrastructure for things like fraud detection models and things like that. So we are starting to see early signs of that happening. The other thing which is really interesting is startups and other model heavy companies that are coming to take advantage of our GPU as well as our platform infrastructure that we have.

Quickly realized that for them to scale their model and deploy it and as they start getting into the inferencing mode, they need a lot of the core cloud primitives that a platform like DigitalOcean offers from compute, network, storage, bandwidth, and having a geo — a global geo footprint to get inferencing with the lowest possible latency as close to their customers as possible. So we are starting to see very healthy early signs of these model-based companies, quickly realizing that for them to go live and start getting into the inferencing mode, they need a lot more than just raw GPU horsepower. They need all of the cloud primitives. Yes there are idiosyncrasies on how storage or networking works in the world of AI. But these cloud primitives are absolutely essential as the models get deployed and get into inferencing mode.

And that’s something that we’re already seeing a lot of times.