Datadog, Inc. Q2 FY2023 Earnings Call

Good day, and thank you for standing by. Welcome to the Q2 2023 Datadog Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speakers’ presentation, there will be a question-and-answer session. 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.

Thank you, Gigi. Good morning, and thank you for joining us to review Datadog's second 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 third 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 March 31, 2023. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended June 30, 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.

Thanks, Yuka, and thank you all for joining us this morning. Our team continued to execute well in Q2 as we welcomed thousands of attendees at our Dashes conference last week. We continue to deliver a large number of new product innovations and we recorded strong new logo bookings throughout the quarter. Let me start with a review of our Q2 financial performance. Revenue was $509 million, an increase of 25% year-over-year and above the high-end of our guidance range. We ended with about 26,100 customers, up from about 21,200 last year. We ended the quarter with about 2,990 customers with ARR of $100,000 or more, up from about 2,420 last year. These customers generated about 85% of our ARR, and we generated free cash flow of $142 million, with a free cash flow margin of 28%. Now let's discuss this quarter's business drivers. At a high level, first, we saw Q2 usage growth for existing customers that was a bit lower than it had been in previous quarters. Second, we do see signs that cloud optimization may start to subside. And third, we continue scaling our sales with strong new logo bookings in Q2. Going one level deeper. In Q2, we saw usage growth for existing customers that was a bit lower than it had been in previous quarters. We continue to see customers, particularly some larger spending customers, scrutinize costs and optimize their cloud and observability usage during Q2. We are reflecting this lower growth in our updated guidance for 2023, and David will provide more commentary regarding our guidance geography. On the other hand, we are seeing signs that the cloud optimization across our customer base may start to subside. The cohort of customers who began optimizing about a year ago appear to have stabilized their growth at the end of Q2, as indicated by the recent activity and the related commitments with us. And we saw usage growth rebound in July to levels that are more similar to what we see in Q1. While it is too early to call an end to cloud optimization and a significant level of macro uncertainty remains, these new trends, along with the tenor of our customer interactions are encouraging. Lastly, our bookings were strong in Q2. Our new logo and new product bookings and deal cycles haven't been impacted by the period of cloud optimization and we continue to see healthy growth on the sales side. From a new logo bookings perspective, we had our largest Q2 and second largest quarter ever, only behind the seasonally larger Q4 2022. We also closed a record number of new business deals larger than $100,000 in annual commitment. And with our land-extend model, we expect new logos to turn into much larger customers over time as they lead into the cloud and add up more of our products. So as a conclusion, while we do apply conservatism to our guidance, recent usage trends as well as strong new logo activity and customer ramp-ups are positive signs for our future growth. Now turning to platform adoption. Q2 metrics show that our platform strategy continues to resonate in the market. As of the end of Q2, 82% of customers were using two or more products, up from 79% a year ago. 45% of customers were using four or more products, up from 37% a year ago, and 21% of our customers were using six or more products, up from 14% a year ago. The strong multiproduct adoption includes expansion into our newest products. About 30% of our customers have already adopted at least one of our products launched since 2021, including CI visibility, database monitoring, cloud security management, sensitive data scanner, and cloud craft, among others. We expect more opportunities to expand adoption of these products as we continue to broaden their capabilities over time. In securities, we mentioned last quarter that over 5,000 customers have adopted security products. While many of these 5,000 are just getting started with Datadog Security, we are seeing opportunities to help customers secure their cloud at scale. As of Q2, 79 of our customers spent more than $100,000 on Datadog Security and a handful are now spending more than $1 million. Now let's move on to R&D. Last week, we had our DASH User Conference and introduced a number of exciting new products and features for our users. To kick off our keynote, we launched our first innovation for generative AI and large language models. We showcased our LLM observability product, enabling ML engineers to safely deploy and manage the models in production. This includes the model catalog, a centralized place to view and manage every model in every state of our customer development pipeline; analysis and insight on model performance, which allows all engineers to identify and address performance and quality issues with the model themselves; and help identify model drift, the performance degradation that happens over time as models interact with real-world data. We also introduced Bits AI. Bits understands natural language and provides insights from across the Datadog platform as well as from our customers' collaboration and documentation tools. Among its many features, Bits AI can act as an incident management copilot identifying and suggesting solutions, generating synthetic tests, and triggering workflows to automatically remediate critical issues. We announced 15 new integrations across the next-generation AI stack from GPU infrastructure providers to vector databases, module vendors, and A/R orchestration frameworks. As we said last quarter, we are excited about these new AI technologies, and we believe Datadog is uniquely positioned to both help our customers make the best of them as well as to incorporate them into our product alongside our data and workloads. And although it's early days for everyone in this space, we are gaining traction with AI customers. In Q2, our next-gen AI customers contributed about 2% of ARR. Moving on from AI. We showcased a number of new capabilities in the observability space. We introduced Flex logs for log management, allowing customers to flexibly choose retention periods and required performance separately to make new high-volume million-use cases cost-effective. We are simplifying APM onboarding for large organizations so engineers can enable APM across all applications without any core changes. With APM trade squaring, our customers can now understand the complete impact of any localized issue. We introduced our Error Tracking Assistant, which manages AI capabilities with live observability data to automatically explain, solve, and test for production errors. In digital experience, we're also applying next-gen AI technologies to help customers automatically generate synthetic tests from their live traffic data. We have expanded our mobile monitoring features, bringing a first-class experience for mobile developer teams with mobile session replay and mobile application testing. We also announced several innovations in cloud security. Our new security inbox surfaces the most pressing security issues, correlating thousands of technical insights and reducing them to a smaller number of actionable tasks. We can now expect more infrastructure vulnerabilities, whether they are in applications, container images, or our hosts. With custom code vulnerability detection, we extended our detection capabilities beyond automated detection and into customer code, identifying the exact vulnerable code with feedback in detail. With Cloud Sim investigator, our customers can visually map an attacker's behavior going back more than a year, leading to faster investigation and remediation. Shifting left, we're delivering more solutions to developers with static analysis. Customers can scan code for quality issues directly within Datadog, and we are introducing quality gates for engineers, allowing them to set rules and prevent insecure, buggy, or slow code from deploying to production. Finally, we announced new capabilities to help customers spend on resources more efficiently. Our container resource utilization functionality makes it clear which applications are under or over-provisioned. With cloud cost recommendations, we're adding to our cloud cost management product to automatically discover savings opportunities and take action on them. Those were just some of the many announcements we made at DASH. Our Investor Relations website includes a link to the DASH keynote, and I encourage you to watch it to learn more. Before I step away from more innovation, I'm also pleased to note that for the third year in a row, Datadog has been named the leader in the 2023 Gartner Magic Quadrant for Application Performance Monitoring and Observability. We believe this validates our approach to deliver a unified platform that breaks silos across teams and to focus intensely on product innovation. Now let's move on to sales and marketing. As I said earlier, we recorded strong new logo bookings, and we continue to see significant expansion opportunities with existing customers. So let's discuss some of our wins. First, we signed an eight-figure deal over three years with a major American video games company. This customer’s previous SaaS observability vendor was not delivering on critical capabilities such as quality alerting and collaborative incident management, and a recent pricing change motivated them to consider other vendors. By moving to Datadog, this customer expects to get higher value out of their monitoring solutions and eliminate silos among users. As we achieve better results, they expect to save over $1 million annually by shifting to Datadog from their previous vendor. Next, we signed a seven-figure land with a major broadcaster. This customer is moving to AWS and serverless, and its fragmented legacy and open-source tools resulted in longer incident resolution times and confusion among teams. This customer is implementing seven Datadog products, consolidating five tools, and has already ramped Datadog to over 500 users. Next, we signed a seven-figure land with a leading Japanese toy and media company. This company has been using a competitive observability vendor alongside smaller tools and home-grown capabilities. With the adoption of five Datadog products, they have full visibility into their applications. They can save time on busy work and focus on delivering great experiences for their customers. Next, we signed a seven-figure expansion with one of the world's largest tech companies. This customer is seeing massive adoption of its new generative AI product and needs to scale their GPU fleet to meet increasing demand for AI workloads. Using their home-grown tools was slowing them down and putting critical product launches at risk. With Datadog, this team is now able to programmatically manage new environments as they come online, track and alert on their service level objectives, and provide real-time visibility for their applications. Last but not least, we signed an expansion with one of the world's largest financial institutions, taking this customer to eight-figure ARR. This customer operates at massive scale, supporting thousands of applications run by tens of thousands of developers, and we have a strategic initiative to move aggressively to the public cloud this year. They chose Datadog as their preferred observability platform for cloud applications, and as their business units modernize, they are expanding to ten Datadog products and replacing several legacy commercial tools. That is it for this quarter's highlights. I'd like to thank our go-to-market team for their execution in Q2 and for helping our customers make the most out of Dash last week. Before I turn it over to David for a financial review, let me speak to our longer-term outlook. Despite the recent trends of product optimization and continued macro uncertainty, our posture remains the same. We are confident in our long-term growth opportunities, driven by the secular trends of cloud migration and digital transformation as well as our rapid pace of innovation to set customers in observability and beyond. We think our strong new logo and product adoption trends this quarter are indicative of the continued large and growing opportunity for Datadog. So our long-term plans have not changed. We are continuing to invest to serve our customers as they move to the cloud, AI, and other modern technologies. With that, let me turn it over to our CFO. David?

Thanks, Olivier. Q2 revenues were $509 million, up 25% year-over-year and up 6% quarter-over-quarter. In Q2, we continued to execute solidly and we also continued to see pressure on the usage growth of existing customers. To dive into some of the drivers of Q2 performance. First, as to usage growth of existing customers, we saw positive usage growth this quarter that was lower than in recent quarters, with broadly similar trends across our product lines. While it’s too early to draw broad conclusions, existing customer usage growth improved in July and was more similar to Q1 than that of Q2. We saw more pressure on cloud-native businesses than traditional enterprise customers, similar to previous quarters. Regarding customers by spending size, the more moderate growth trends were consistent across the customer base with relatively more pressure on usage growth rates with larger customers. As Olivier discussed, the cohort of customers who began optimizing about a year ago appears to have stabilized their usage growth with Datadog, though we recognize that the growth rates of these optimizing customers may remain muted, and other customers could optimize. Regarding total customers, our customer count increased to 26,100 from 25,500 last quarter. This quarter’s total paying customer count includes a one-time cleanup of about 200 financially immaterial customers at the very low end, who were moved to our free tier. Our gross customer additions have remained strong, especially with larger customers. Meanwhile, we are seeing some churn of smaller customers who have limited impact on our revenues. As a result, our gross revenue retention rate remains unchanged in the mid to high 90s, indicating the stickiness of our product and the importance of our product to our customers’ operations. We are executing on strong new logo bookings and new customers contributing meaningfully to our growth as they ramp up. As Olivier mentioned, we had our second-largest new logo bookings quarter and a record for Q2. We expect these customers to become more meaningful as they expand with us. In Q2, about 40% of our year-over-year revenue growth, or 10 points of growth, was attributable to growth from these new customers that were acquired in the past year. Finally, we continue to see consolidation opportunities, particularly in larger deals. Consolidation allows our customers to improve functionality by getting all of their data into one platform while saving money at the same time. Moving on to our trailing 12-month dollar-based net retention rate, or NRR. NRR was over 120% in Q2 as customers increased their usage and adopted more products. As we expected and as we discussed on last quarter’s call, our trailing 12-month NRR declined but was above 120 in Q2 as existing customers continue to scrutinize their tech stack costs and make efficiency improvements. If our growth trajectory continues at current levels, we expect our trailing 12-month NRR to decline to below 120 in Q3. Moving on to our financial results. Billings were $520 million in the quarter, up 31% year-over-year. Billings duration increased slightly year-over-year. Remaining performance obligations, or RPO, was $1.25 billion, up 42% year-over-year. Current RPO growth was about up 30% year-over-year. We signed some larger multiyear deals in the quarter, which drove an increase in the duration year-over-year. As we’ve mentioned before, we continue to believe revenue is a better indicator of our business trends than billings and RPO, as those can fluctuate relative to revenue based on the timing of invoicing and the duration of customer contracts. Now let’s review some 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 $414 million, representing a gross margin of 81.3%. This compares to a gross margin of 80.5% last quarter and 80.8% in the year-ago quarter. We continue to experience efficiencies in cloud costs reflected in our cost of goods sold this quarter. As a result, we are experiencing a gross margin that is in excess of our target in the high 70s. Our Q2 OpEx grew 26% year-over-year, and this was a decline from 45% year-over-year growth last quarter. We moderated our hiring pace and executed on controlling costs, given the macro uncertainties. Q2 operating income was $106 million, or a 21% operating margin, up from 18% last quarter and flat to 21% in the year-ago quarter. We are pleased with our execution on cost control and disciplined investment this quarter. Turning to the balance sheet and cash flow statements. We ended the quarter with $2.2 billion in cash, cash equivalents, and marketable securities. Cash from operations was $153 million in the quarter. And after taking into consideration capital expenditures and capitalized software, free cash flow was $142 million for a free cash flow margin of 28%. Now turning to our outlook for the third quarter and the fiscal year 2023. In forming our guidance, we continue to use conservative assumptions as to the usage growth of our existing customers. As a reminder, our guidance philosophy is to carry forward trends observed in recent quarters, discounted with additional conservatism. For the third quarter, we expect revenue to be in the range of $521 million to $525 million, which represents a 19% to 20% year-over-year growth. Non-GAAP operating income is expected to be in the range of $98 million to $102 million. Non-GAAP net income per share is expected to be in the range of $0.33 to $0.35 per share based on approximately 354 weighted average diluted shares outstanding. And for the full fiscal year 2023, we expect revenue to be in the range of $2.05 billion to $2.06 billion, which represents 22% to 23% year-over-year growth. Non-GAAP operating income is expected to be in the range of $390 million to $400 million. Non-GAAP net income per share is expected to be in the range of $1.30 to $1.34 per share based on approximately 351 million average sales diluted shares outstanding. Now finally, for some additional notes on the guidance. We have continued to balance near-term financial strength with investment in our large long-term opportunities, and we are executing well on our plans to invest efficiently. Next, we expect net interest and other income for fiscal year 2023 to be approximately $85 million, and we expect our tax expense for the full year to be $14 million to $16 million. Finally, we expect capital expenditures and capitalized software together to be about 4% of revenues in fiscal year 2023. To reiterate Olivier's comments, we remain excited about our long-term growth opportunities, and we're continuing to execute against those opportunities. I want to thank our Datadog worldwide teams for their efforts in this quarter. And with that, we will open the call for questions. Operator, let's begin the Q&A.

Thank you. Our first question comes from the line of Raimo Lenschow from Barclays.

Hey. Thank you. Olivier, on the if you think about the niche, can you discuss a little bit in the nature of the optimizations that you see when you compare a little bit what you saw at the early parts of the after recession or the cycle late last year versus what you see now. Does the nature has changed there in terms of what you're seeing there? And then I have one follow-up, David.

No, we don't see a significant change in the nature of the optimization. It's a combination of optimizing the cloud workloads themselves and some focus on the observability side for new products with volume that can be separated from the cloud workloads, such as logs and metrics. This quarter, we did notice slightly lower growth across the board from existing customers. We believe that some customers have started optimizing earlier, while others have started later, and they are all at different stages. We did observe that some customers who have been optimizing for about a year have stabilized their growth. We feel more confident now that they understand what to expect. We've seen some of these customers begin to commit long-term with us again at levels that match or exceed their current usage, which indicates they have clarity on what is coming next. This aligns with your comments about potential signs indicating that this period of adjustment might be coming to an end. While it’s still too early to make definitive claims, we feel we might be on more stable ground.

Yes. Okay. And then just linking that up with the guidance because that's where I get a lot of the questions, you think about your Q3 and then Q4 implied guidance, even given that you had a full year there’s obviously still headwinds on growth that are kind of coming there. Like how much of that Q3, Q4 is kind of a lagging effect of what we've seen before versus kind of maybe other factors like conservatism, et cetera? Thank you.

Yeah, it's both. Because our growth was a little lower than in Q2 than it had been in the previous quarters, we have that effect moving forward given our recurring revenue model. And then on top of that, we discount the most recent performance, particularly around usage growth, but also in new logos. So it’s a combination of both of those flowing through in our financial results for the year.

Thank you. One moment for the next question. Our next question comes from the line of Sanjit Singh from Morgan Stanley.

Thanks, guys for taking the question. I think I understand the comments around slower usage growth trends, particularly compared to Q1. I just wanted to dig into sort of issues around competition. David, you mentioned sort of higher churn at the low end. We see total customer count growth slow down this quarter. So we think of about either competition, competition with open source or DIY or maybe even customers adjusting their tech stack to hyperscale or needed solutions. Has it seen any sort of pickup there? And is that a potential as part of the mix of why we're seeing slower usage trends this quarter?

Sanjit, you're cutting out a bit. I hope I addressed your question adequately. We are experiencing somewhat higher churn at the very low end, which is primarily related to the challenges faced by very small businesses that utilize our services for minimal amounts and may close or downsize. Additionally, we conducted a one-time cleanup this quarter; generally, we do not retain customers who are not active on the platform or whose payments are not current. We adjusted some criteria, resulting in the removal of 200 customers in this cleanup, impacting our figures. Nevertheless, we still observe slightly heightened churn at the low end. The revenue from these customers is relatively small and immaterial; overall, our gross retention rate remains stable, sitting in the mid to high 90s on average.

We mentioned that we had strong new logo bookings and cross-sell in terms of dollars. A significant portion of that relates to consolidation onto the platform, which has been ongoing for a long time.

We are very pleased with the performance of our new products and the acquisition of new customers. We are achieving record numbers of new clients, and we are experiencing increased consolidation onto our platform. The competitive dynamics appear to be shifting in our favor over time, despite the slight rise in churn rates at the lower end, which represents a small revenue impact. Overall, our gross retention remains stable in the mid to high 90s.

I appreciate the color. And then David and Olivier, you made some sort of preliminary comments of potentially seeing some green shoots on the optimization headwinds that we've seen over the last several quarters. In terms of the percentage of the base that hasn't optimized, any sort of color how large that is? What percentage of the customer base hasn't yet optimized but potentially could going forward?

We can't really give you a percentage there. But the cohort we mentioned on the call was the one we were looking at for getting a sense of stabilization in the optimization was the cohort that started optimizing first. That was typically large in volume, very cloud-native in nature and that we consider to be the highest risk one. So the one that weighed on our growth numbers the most over the past few quarters. That’s the one we based a lot of our comments on. In addition to the other trends that David mentioned earlier, we saw our growth of existing customers pick up first late in Q2 and then in July.

I appreciate the color, Olivier. Thank you.

Thank you. One moment for our next question. Our next question comes from the line of Mark Murphy from JPMorgan.

Yes. Thank you very much. Once the larger customers have compressed spending, and obviously, there's a limit to how much they can compress that. Then they're going to need to grow that spending again. At some point, you're going to have growth ramping pretty materially in security. It sounds like that has started and all of the LLM observability. And then you're going to have easier comparisons as we head into 2024. Is it reasonable to think that optimizations could be further subsiding as you're entering 2024 based on your comments? And for all these reasons, should we be optimistic on growth picking up relative to how it's going to exit in Q4 of this year, which I think is around the mid-teens? And I know it's hard to answer because you haven't guided on that yet or would you be imagining, David, that we might kind of just drag across that 15% into 2024 as a starting point. And if you can't answer it numerically, maybe you could just kind of speak to some of these timeframes qualitatively. Thank you.

Yeah. I think we haven't provided guidance for next year. We cited that given the amount of our revenue growth that is embedded in our existing customer base. The timing of the lapsing of optimization is critical to that. We said we see green shoots as been said, but it's too early to call that. So that's the biggest factor. In addition, we said that our new logo performance in assigning new customers who then ramped is another green shoot that could do that, but we haven't provided guidance on specific numbers for next year, so I really can't go further.

Well, look, I mean, we are obviously optimistic that we're still very early in a big tech transition. Short-term, we don't really control the growth of existing customers and how much they optimize their cloud environment and things like that. But for everything that we control and we secure on, which is new products, the quality of the products, and the new customers and the attach of these new products with customers, everything we see seems to be working, and we see great results from that. And these are obviously great trends for the future. The one thing I would add is that in our conversation with our customers at a conference just last week, most of the conversations were around how we’re going to get our customers to implement new use cases, add new products, and scale up with us. There was still a little bit of customers thinking about cost control, optimization, and things like that, but we also see less of a need for that. So when that kicks in, in terms of the overall growth in aggregate, as David said, it's too early to tell, and we want to be careful there because we know sometimes our customers will know everything themselves. They might face more difficulties as they go. But we're very optimistic about the mid to long term, obviously.

Olivier, thank you for that. As a quick follow-up, you mentioned strong new logo bookings, but we don't see that reflected in the new customer count. However, you listed several notable seven and eight figure wins, which appear to be consolidations from other vendors to Datadog. Am I understanding correctly that this indicates a significant shift, particularly in win rates and competitive displacements, suggesting that the vision of a consolidated platform is benefiting Datadog in the competitive landscape?

In general, we observe that these consolidation deals tend to present the largest headline figures when we finalize them, rather than simply continuing with their existing revenue from those customers. This is what leads to noticeable changes, which is why we highlight them during the earnings call. Overall, we have achieved a record number of new business deals exceeding $100,000. What’s not reflected in the total customer count is the variance between smaller, medium, and larger customers. There is significant fluctuation at the lower end of that customer count, which affects the overall numbers. However, for the segments we focus on with our sales team, particularly the mid-sized and larger accounts, we see positive growth that aligns well with the performance of our sales force. We are very pleased with this progress.

To clarify the customer count, the gross additions have remained consistent with previous quarters. However, as Olivier mentioned, the prevalence of larger deals has led to a higher average land, contributing to the record Q2. The net figures were impacted by the removal of very low-end customers who are on the verge of minimal usage and free trials. Overall, the gross addition activities were strong. In fact, as noted, we are witnessing more consolidation efforts within those wins.

Thank you very much.

Thank you. One moment for our next question. Our next question comes from the line of Kash Rangan from Goldman Sachs.

Hey. This is Anisha on for Kash. Two quick questions. One may be on usage growth slowdown. Is that coming from particular end markets or segments or verticals that you can highlight? And second, maybe on hiring, while you're seeing green shoots in new logo growth and we had a great number of announcements from the DASH conference, what would give you conviction to ramp up hiring or since you've moderated your go-to-market motion right now? Thank you.

The growth slowdown is noticeable across the board with optimization, especially more so with cloud-native businesses compared to traditional enterprises. This is mainly because cloud-native companies are investing significantly in the cloud and prioritizing savings there, while larger enterprises are still early in their cloud migration and continue to spend most of their IT budget outside of the cloud. This is where we have observed the most optimization. We have seen that the initial cohorts of cloud-native customers who began optimizing a year ago are now stabilizing and increasing their commitments with us over the past few months. Regarding hiring, we are still growing and investing in the company. We have adjusted our growth to align with market conditions, but we believe we are still in the early stages of our journey. We have much to develop in observability, security, workforce and developer experience, and ITSM, along with numerous new use cases, including AI. Thus, we will continue to hire and innovate. Additionally, we've been expanding our go-to-market teams, and those investments are resulting in additional growth in new logos and products. As mentioned in the call, that segment of the business is performing well, and we are pleased with the results. We will keep expanding the team while being mindful of the necessary margin protections.

Thank you. One moment for our next question. Our next question comes from the line of Jacob Roberge from William Blair.

Hey. Thanks for taking my questions. Obviously, AI is something that a lot of customers are excited about, but we're hearing that it may be delaying purchasing decisions in other parts of that tech stack until customers kind of figure out how they want to incorporate AI into their broader organization and just how much that will cost? Do you feel like that dynamic impacted Q2 at all with just maybe a near-term low in IT spending until broader AI plans are finalized? Or is the updated guide mainly just driven by the optimizations you've been calling out?

We don't really see that trend playing out. The one thing I would mention is that our AI customer base is currently concentrated in two accounts. These customers have been working on AI for the past two to three years and either provide AI services or have built their businesses entirely around AI. We are seeing these businesses scaling, in some instances, at a very large scale right now. However, this represents a relatively small number of customers. There are many more customers who are poised to adopt AI, but they are still in the early stages. It will likely take several quarters, and in some cases, even years for these use cases and customers to fully reach scale. So, while we have a larger number of potential customers, they are at a very early stage. This illustrates the two trends we see regarding our AI penetration and adoption.

Okay. Helpful. And then you called out the strong new logo bookings quite a few times there. Are there any commonalities between those customers from just a size or maybe an industry perspective? And I'm curious if you've started to see any of the newer generative AI-focused companies that are creating these LLMs start to actually layer into your model from a customer perspective?

Right. The new logo bookings are in terms of value like their approximately mid-market and enterprise. So on the larger side and on the more traditional side. We have a number of companies or customers that are also the providers of AI, but some of those have been customers for some time already. In some situations, we have new business units of existing customers that were with us for a while, but also started new business units around AI that start adopting more product. More recently, we have one of those also in the call comments from a very large customer.

Great. Thanks for taking my questions.

Thank you. One moment for our next question. Our next question comes from the line of Brent Thill from Jefferies.

On sales and marketing in Q2, you've never been down sequentially. Are you holding back on quota-carrying rep hiring to get the reps productive? Are you going to be adding on that side? And a quick follow-up.

The biggest factor there was the sales kickoff that would be in the first quarter and not in the second quarter. So the change has more to do with the timing of events. Be that as it may, as Olivier mentioned, we're continuing to invest in sales quota-capacity, but we are growing that at a lower rate than we did last year. But the major factor in the sequential was a seasonal thing around events.

Okay. And real quick, just some of the large customer adds in 80, your cadence was pushing 130 to 170. So is something competitively going on there or is it just you're equally seeing the SMB and Enterprise act the same way in terms of their conservatism?

I didn't understand the question.

Brian, you're talking about the net adds of $100,000 plus customers?

Correct.

It was 80 versus 130 to 170 in the last four quarters. Yes. I would say that we said that the number of customers has been relatively steady, although, it's decelled. And we have gotten, I would say, in that range in land, the average land has been larger. So of those that are landing smaller. When net retention goes down because the major source of customers going into that would be from customers below $100,000. And bigger factor would be that it takes longer for those customers to evolve into a $100,000, and that's the biggest factor in that.

Yes. To reiterate, we are very pleased with the increase in medium and large customers. The numbers for new customers and new products are rising across the board, and we feel very positive about that. Overall, things are improving in that area.

Thank you.

Thank you. One moment for our next question. Our next question comes from the line of Michael Turits from KeyBanc.

Hey, guys. Two questions. First, can you discuss how usage changed month by month in April, May, and June? Is there any reasoning behind that? My second question is for Olivier; you mentioned the difference between those points.

I didn't hear your second question because of some technical issues. Regarding the first question, yes, ERT during the quarter was fairly typical for us. We experienced a low in May, starting in late April, but things got better in June and improved further in July, which falls after the end of the quarter. For guidance for the rest of the year, we are relying on what we observed throughout the quarter while being careful not to focus too much on the partial quarters that follow. We've taken these factors into account, and we will maintain this approach moving forward.

Thanks. And then the second question was the optimization that was particular to observability. Is there any difference across your major product categories, let’s say, APM versus logs versus infrastructure?

The ones that are the most sensitive to that are logs, some part of infrastructure, which is custom metrics and some part of APM, which is additional large volume transactions that customers might transition to what they get included with every single cost to deploy APM on. And we've seen some optimization on that, that's been specific to observability. I would say it does go hand in hand with the overall optimization our customers are doing. So the timing might always be exactly the same, which is also why we're careful about the trends that we're forecasting based on the sort of the improvement we've seen recently.

Thank you. One moment for our next question. Our next question comes from the line of Andrew Nowinski from Wells Fargo.

Okay. Thank you. Good morning, everyone. So I want to start with a clarification. Did you actually lower your discount rate that you apply to your organic growth relative to your annual outlook or when you put that together this quarter?

Yes, we would essentially discount the most recent assumption. So if the most recent assumptions were lower, we said they were lower in Q2 then we would be lowering that in the guidance assumptions going forward.

Right. So it wasn't just the organic growth rate being lower, your actual discount rate was lower, too?

I'm sorry, I don't understand your question. We base our guidance on assumptions and then apply a discount. You would need to clarify what you mean by the discount rate.

We don't have a discount rate card for guidance. But we do discount the historical as we give guidance for the future.

Okay. Fair enough. And then I just had a question on that large deal, the eight-figure deal. Is that large enough that we should normalize it when we think about our estimates for next year or do you have enough of those eight-figure deals in the pipeline that it will blend out?

I don't think you need to normalize for it.

Thank you. One moment for our next question. Our next question comes from the line of Taz Koujalgi from Wedbush.

Hey, guys. Thanks for taking my question. I have a question on the new logo bookings that you mentioned. What is the average duration of new bookings or new logo bookings? And how has that trended so far?

We haven't discussed the duration of new bookings compared to existing ones. Typically, our contract durations are just under a year, around nine to ten months, but we haven't shared specifics about the differences in new bookings. I would say that the majority of our revenue comes from existing customers, and factors like renewals or new contracts with these customers tend to have a greater impact on contract duration. There has been a trend towards longer-term agreements, which has increased the duration for our existing customers.

And just to clarify, the duration for new customers was consistent with the prior quarter or was it higher?

The duration increased. So we said that the RPO total was higher than the current RPO, and that the reason was that duration had gone up slightly from previous periods. Duration increased in contracts.

Yeah. Very helpful. Just one follow-up. That 40% of the new, I guess, revenue growth came from new customers. So 10 points of the revenue growth came from new customers who signed up in the last, I guess, year. Is that a consistent metric or was that higher or lower than what you usually see?

We indicate in our quarterly reports that the 40% figure is an increase compared to previous periods. This is mathematically accurate because as net retention decreases with a more stable influx of new customers, the percentage tends to rise. The 10 points of growth from our new customers would be more stable and less reliant on net retention.

Got it. Thanks very much.

Thank you. One moment for our next question. Our next question comes from the line of Koji Ikeda from Bank of America Securities.

Hey, Olivier and David. Just one from me here in the interest of time. Olivier, in your prepared remarks, you called out 2% of ARR being generated from next-gen AI customers. I wanted to dig into that a little bit more. How should we be thinking about how you define what a next-gen AI customer is that an existing customer with very specific AI initiatives or is that a next-gen AI-specific customer, say, like an LLM vendor? And then what was that contribution during Q1? Thanks, guys.

You can view next-gen AI customers as those who are either selling AI products themselves, like LLM vendors, or businesses entirely based on unique AI technology. We have been quite selective in identifying these customers because many companies today are quick to assert that they have a differentiated position in AI. This illustrates the new types of businesses that have emerged over the last year to two years. Some may be divisions of larger companies, but most are relatively new and independent entities.

We didn’t give a comparable for the numbers. This is the first time we disclose this. And we probably won’t disclose it on a regular basis just to give more color to what we see in the market today.

Got it. That's super helpful. Thank you very much for taking the question.

Thank you. One moment for our next question. Our next question comes from the line of Patrick Walravens from JMP Securities.

Great. Thank you. I'd love to hear what you thought about the attendance at Datadog Dash in San Francisco versus your expectations? And then more broadly about your thoughts around the return to in-person events like this?

So overall, we're actually very happily surprised. We decided to put Dash in San Francisco this year. So we switched things up a little bit and maybe see different customers than the ones we see when we do it on the East Coast. We're a little bit worried to be honest because we did it in the summer in San Francisco, and we had heard stories about getting people to show up. We've been very, very happily surprised. We got great attendance actually higher than we had modeled, which forced us to scramble the first day to add some shares in the keynote rooms. Overall, the time was very good. The conference was very productive and very positive. In terms of the return to in-person events across the board, we see them happen whether that’s our own conference or the other industry or conferences that we exhibit at. We see a lot of success with those again, and since customers are very eager to connect and come to these events. So definitely something that’s happening this year that was maybe not happening as much the years before.

Thank you. One moment for our next question. Our next question comes from the line of Gregg Moskowitz from Mizuho.

Thank you for taking the question. First for Olivier and then I had a follow-up. So given the slight improvement in usage trends that you cited in the first quarter, it was a bit surprising to hear that Q2 usage growth for existing customers was a little lower than prior quarters because we haven't really been hearing this from other consumption business models that have recently reported. I'm just wondering if you have any thoughts as to why the usage growth for existing customers may have downticked this quarter? Anything come across?

Well, at the end of the day, we have a somewhat different customer mix compared to others. There are optimizations with other companies that may relate to different cloud setups, which differ from our mix in the industry. This combination might result in varying timing effects regarding how different optimizations could affect us relative to others. So, I wouldn't read too much into it. The overall trends are largely consistent with what you observe across the industry. Other participants are also cautious about making comparisons with IBM in terms of optimization, and we are too. However, based on the behavior we see from our customers, particularly those we consider most susceptible to optimization, we are optimistic about the trajectory they are on and the recent usage trends we have observed.

Okay. Thanks, Oli. And then I wanted to ask on the security side because you mentioned 79 customers now over $100,000, including a handful spending more than $1 million. For those largest customers in particular, can you give us a flavor for which Datadog security products they're most frequently using? Also, how much of this, again, to those largest wins, how much of this is greenfield as opposed to displacement? Thanks.

The largest customers there tend to use almost all of our security products today. Sometimes there are some exceptions. These are customers that tend to be on the tech-forward mid-market higher-end of the market side that deploy our products widely throughout their organizations. Typically, customers that have us in six figures are above tend to be enterprise or mid-market, but the ones that are mid and above tend to be mid-market and more tech-forward. Overall, the adoption tracks the industry adoption of unified DevSecOps as a practice. And again to zoom out a little bit, we believe that this is where the whole industry is going. We're building a product that's completely ready, and we have a fully mature end-to-end solution that is relevant to every single customer. So by the time this becomes a general practice in the industry, we will be the no-brainer choice for all of those customers, and so far we're pleased with what we’re doing there.

Very helpful. Thank you.

At this time, I would now like to turn the conference back over to Olivier Pomel, CEO of Datadog, for closing remarks.

Thank you. So first of all, thank you all for attending the call today. I also want to thank all of our employees, all the Datadog teams around the world for a Q2 that was very well-executed. I want to thank all of our customers for making DASH last week such a vibrant conference and making some productive conversations with them. With these good words, thank you all.

This concludes today's conference call. Thank you for participating. You may now disconnect.