Title

Presentation

Datadog, Inc. beats earnings expectations. Reported EPS is $0.36, expectations were $0.28.

Operator: 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. [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, 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.

Olivier Pomel: Thanks, Yuka, and thank you all for joining us this morning. Our team continued to execute well in Q2 as we welcome 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 the users growth at the end of Q2, as indicated by the recent activity and the related commitments with us. And we saw usage growth in aggregates 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 product. 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 include expansion into our new 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, cloud craft and 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 model. We showcased our LLM observability product, enabling ML engineers to safely deploy and manage the models in production. This includes the model catalog 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 issue with the model themselves; and help identify model drift, the performance degradation that happens over time as model interact with real-world data.

We also introduced Bits AI. Bits understands natural language and provide 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 success, generating synthetic tests and triggering workflows to automatically remediate critical issue. And we announced 15 new integrations across the next-generation AI stack from GPU infrastructure providers to Vector databases, module vendors and AR 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 getting traction with AI customers. And 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. And 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 as our hosts. With custom code venerability detection, we extended our detection capabilities beyond auto [indiscernible] and into customers on code identifying the exact vulnerable code mixed feedback with the majority in detail.

And 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 can set rules and prevent e-secure, buggy or slow code from deploying production. Finally, we announced new capabilities to help customers spend on property to receive more efficiently. Our container resource utilization functionality makes it clear which applications are under or over provisioned. And with cloud cost recommendations, we’re adding to our cloud cost management product to automatically discover saving opportunities and act 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 unified platform, which breaks on 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. These customers’ previous SaaS observability vendor was not delivering on critical capabilities such as quality alerting and collaborative incident management and a recent pricing change motivated to get some rich consider other vendors. By moving to Datadog, this customer expects to get higher value out of their monitoring, produce [indiscernible] and eliminate silos among users. And 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 in open-source tools meet longer incident resolution times and confusion among teams.

This customer is developing 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 toys 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 the 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 workload.

Using their home-grown tools were slowing them down and put at risk critical product launches. With Datadog, this team is able to programmatically manage new environments as they come online, track and alert on their service level objectives and provide real-time visibility for [indiscernible]. 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 application. And as their business units modernize, they are expanding to 10 Datadog products and replacing a number of legacy commercial tools and that is 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. And 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?

David Obstler: Thanks, Olivier. Q2 revenues was $509 million, up 25% year-over-year and up 6% quarter-over-quarter. In Q2, we continued to execute solidly and we also continue 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 to lower than in recent quarters, with broadly similar trends across our product lines. While 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, appear 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 are 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 decline 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, which 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 in 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 conservative. 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. And 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 $0.34 per share and 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 for our efforts in this quarter. And 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 the line of Raimo Lenschow from Barclays.

Raimo Lenschow: Hey. Thank you. Olivier, on the — if you think about the niche, can you discuss a little bit in the nature (ph) 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.

Olivier Pomel: No, we don’t see a big change in the nature of the optimization, it’s a mix of a optimization of the cloud workloads themselves and little bit also on the observability side for the new (ph) products that have volume that can be separate from the cloud workloads, such as log from metrics and things like that. I would say, so this quarter we did see a little bit lower growth as we said in the comments across the board from existing customers. We suggest that the customers have started optimizing earlier, we’re not done yet and some others have started later and they all across many are (ph) there. We did see, however, that some of the customers in the course of customers and but you’re going to stay optimizing a year ago and that we’re on the larger side and on the primary side has stabilized their growth.

And we feel a lot more confident now that they’ve done at least as far as they know. As we’ve seen some of these customers start committing long-term forward again with us and at levels that are at or above their current levels of usage, which suggest that you have a good idea of what is going next, which is all inspired — part of what you for your comments about the — fact that we think we might we see some signs that the this period by end. Still too early to call it, but we see some — we seem to be on more solid ground there.

Raimo Lenschow: 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.

David Obstler: 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 — in our guidance philosophy, we discount the most recent performance, particularly around usage growth, but also in new logos. So it’s a combination of both of that, those flowing through in our financial results for the year.

Raimo Lenschow: Okay. Perfect. Thank you.

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

Sanjit Singh: 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 low end. We see total customer count growth slow down this quarter. So we think of about either [indiscernible] competition, competition with open source or DIY or maybe even customers rather than getting to hyperscale or needed solutions. Has it seen any sort of pick up there? And is that a potential as part of the mix of why we’re seeing slower usage trends this quarter?

Olivier Pomel: Sanjit, you’re breaking up a little bit. So I hope I answered your question appropriately, but the — we do see a slightly higher return at the very, very low end. This is more related to the health of what happens to tiny, tiny businesses that use us for small amounts and that themselves might disappear go out of business or start having needle together. We did have a onetime cleanup also this quarter as we — on an ongoing basis, we don’t create some customers if they are not super active in the platform or if they are deals are out — are not paid up today. We changed some of the criteria around that, which ended up with a onetime cleanup of 200 customers, which changed a number there. But beyond that, we do see a little bit higher churn at the very, very low end. The numbers there are small in terms of revenue. They’re actually completely material and the overall gross retention remains unchanged and in the mid to high 90s in aggregate.

David Obstler: We said that — I think on the other side of it, we said that in dollars, we had a strong new logo bookings and also cross-sell. And a lot of that, as I said in my comments, or a portion of that tends to be consolidation onto the platform, which has been going on a long time.

Olivier Pomel: Yeah. And beyond that, I think it’s a good point, David, we do see — we’re actually very happy with what we see on the new product and new logos out of the business. We’re lending record numbers of new customers of scale and we’re also seeing more and more consolidation on to us. If nothing else, the committee dynamics seems to turn more into our favor as time goes by there, independently from what we see in terms of churn or go to very end (ph).

Sanjit Singh: I appreciate the color. And then David and Olivier, you made some sort of, I guess, 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?

Olivier Pomel: 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 the 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 and that’s the one we based on a lot of comment on. In addition to the other trends that David mentioned earlier, on the fact that in aggregate, we saw our growth of existing customers pick up first late in Q2 and then in July.

Sanjit Singh: I appreciate the color, Olivier. Thank you.

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

Mark Murphy: Yes. Thank you very much. Once the larger customers have compressor 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. And 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 then for all these reasons, should we be optimistic on growth picking up just relative to how it’s going to exit in Q4 of this year, which I think is around — 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 time frames qualitatively. Thank you.

David Obstler: Yeah. I think we haven’t provided guidance for next year. We cited that given the amount of our revenue growth that embedded in our existing customer base. The timing of the lapsing of optimization is critical to that. We said we see green shoots has 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 terms of assigning new customers who then ramped is another green shoot that could do that, but it’s — we haven’t provided guidance on specific numbers for next year, so I really can’t go further.

Olivier Pomel: Well, look, I mean, we are — obviously, we’re 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 to 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 who we’re going to get our customers to implement new use cases, add up new products, scale up, consolidate onto our platform.

There was still a little bit of customers thinking about cost control, optimization and things like that, but we also see less a bit of a time. 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, long term, obviously.

Mark Murphy: And Olivier, thank you for that. Just as a quick follow-up. You mentioned strong new logo bookings and I think we don’t see that in the new customer count, but you rattled off a handful of seven and eight figure wins, which I believe each and every one of this sounded like a consolidation play onto other vendor — off of other vendors and displacing those on to Datadog. Am I interpreting it accurately to think that maybe you’re seeing a pretty big shift there, where maybe in terms of just win rates, competitive displacements kind of seeing this vision of the consolidated platform really putting a dent in the competitive landscape to Datadog’s advantage?

Olivier Pomel: Yeah. Well, in general, we see it and we see — by nature, this consolidation deals tend to be the ones that have the biggest headline number when we close them as opposed to just a continuation of their existing run rate we have with those customers. So that’s what causes the step functions there, and that’s why we call them out on the earnings call. But in general, we have a record number of new business deals across — above $100,000. So what you don’t see in the overall number of customers is the spread between smaller, medium and larger. There’s quite a bit of noise at the low end of that customer count, which makes the number ebb and flow a little bit. But for the part that we target with our sales force, which are the middle and the high end of it, where we actually see those numbers go nicely and commensurately with all sales force. So we’re very happy about that.

David Obstler: Just to clarify the customer count. So on gross additions, a number — very consistent with what we’ve seen in previous quarters. But as Olivier mentioned, more larger deals resulted in a higher average land. That’s what produced the record Q2. And the net — the weight on the net is, we mentioned the cleanup, but on the very low end customers that are on the border between very, very slight usage and free trial. So the gross addition activities were consistent and strong. And in fact, I think as you mentioned and as you get to the larger deals, you have more consolidation impetus within those wins.

Mark Murphy: Thank you very much.

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

Anisha Narayan: Hey. This is Anisha (ph) 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.

Olivier Pomel: Yeah. On the — so first on the growth slowdown. This is, I would say, across the board with the optimization, but it is a lot more pronounced with cloud-native businesses than with traditional enterprises. And the reasons for that are that cloud native businesses have a lot more they’re spending on the cloud and a lot more of an emphasis on saving there than the larger enterprises that are a lot earlier in the cloud migration and that still have most of their system or a majority of their IT spend that is outside of cloud. So this is where we’ve seen the most optimization. It’s still where we see the most optimization, though, as we said in the call, we saw that the earlier cohorts of cloud-native customers that started optimizing a year ago are showing some stabilization and some higher commitments with us in the past couple of months.

In terms of hiring, I think we’re still growing the company, and we’re still investing. What we’ve done is we have moderate to that of growth to align on the — on what we’ve seen in the market. But we still consider we are very, very early in terms of the — or put our journey. We still have a lot to build in observability. We have a lot to build in security. We have a lot to build and develop our workforce and developer experience. We have a lot to be in ITSM. There’s many, many new use cases we’re going after, including AI. And so we’re not going to stop hiring and we’re not going to stop innovating there. The last thing I’ll mention is that we’ve also been growing our go-to-market teams. And the reason for that is those investments in go-to-market are yielding incremental growth on the new logo and new product side.

As we said in the call, that part of the business has been working very well, and we’re very satisfied with the output there. So we’ll keep growing the team while being mindful of the margins we need to protect.

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

Jacob Roberge: 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?

Olivier Pomel: We don’t really see that trends play. I would say — the one thing I would say is or AI customer is fully into two accounts right now. They are the ones that have been working on it for the past two, three years, that our providers of AI themselves or business that are completely built on AI and we see those business reaching scale, in some cases, very large scale right now. And — but it’s a relatively small number of customers. There’s a much larger number of customers that are standing to embrace AI. But those are still early, and it’s probably going to take a number of quarters even yours in some cases for those use cases and those customers to reach full scale. So again, a much larger number of customers, but quite early. So we have those two trends at play when you look at our AI penetration and the AI adoption.

Jacob Roberge: 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?

Olivier Pomel: Right. And is part of your question — can you read it? You were – your volume was a little bit low.

Jacob Roberge: Yeah. The first part was just around the strong new logo bookings and just if there was any commonalities between those customers from a size or an industry perspective?

Olivier Pomel: The new logo bookings are in terms of value like their [indiscernible] at 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. And 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 adapting more product. More recently, we have one of those also in the call comments from a very large customer.

Jacob Roberge: Great. Thanks for taking my questions.

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

Brent Thill: 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.

David Obstler: 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 (ph) 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.

Brent Thill: 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?

David Obstler: I didn’t understand — what — I didn’t understand the question.

Yuka Broderick: Brian, you’re talking about the net adds of $100,000 plus customers?

Brent Thill: Correct.

David Obstler: 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 (ph). 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. And 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.

Olivier Pomel: Yes. And just to reiterate what we’re saying, we’re very happy with the addition of customers on the medium and large size. These numbers are going up across the board in terms of new customers and new products and — so we feel very good about that. And if nothing else, the things are improving there.

Brent Thill: Thank you.

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

Michael Turits: Hey, guys. Two questions. First, can you finish on [Technical Difficulty] Can you just talk about how usage traded month by month, April, May, June? And if you can go there any logic around that? And then my second question is just, Olivier, you had said there was the difference between those [Technical Difficulty].

Olivier Pomel: I didn’t hear your second question. You’re breaking up a little bit. So the first question — and for the first question to start, maybe was on the ERT during the quarter, I guess. Yes. So ERT was not completely out of the ordinary for us. So I will say we see — we had a low in May. I would say in late April and May, we started having a low. And then things improved in June and improved some more in July, which is after the end of the quarter. That being said, as we — for more guidance for the rest of the year, we based that on what we saw throughout the quarter and we discount it. And we’re trying to avoid looking too much at what we saw the partial quarters we go after that. That’s been offset as you through that, and we’ll stick to that today.

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

Olivier Pomel: So 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 tradition 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 co-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.

Michael Turits: Okay. Thanks.

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

Andrew Nowinski: 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?

David Obstler: 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.

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

David Obstler: I don’t know — sorry, I don’t understand your question. We do our guidance based on taking the assumptions and then discounting. I don’t know — you’d have to clarify what you mean by the discount rate.

Olivier Pomel: We don’t have a discount rate card for guidance. But we do discount the historical, as we give guidance for the future.

Andrew Nowinski: 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 pr do you have enough of those eight-figure deals in the pipeline that it will blend out?

Olivier Pomel: I don’t think you need to normalize for it.

Andrew Nowinski: Okay. Thank you.

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

Taz Koujalgi: 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?

David Obstler: We haven’t discussed the duration of new bookings versus existing bookings, our durations in terms of contract it tended to be just under a year, nine months to 10 months, but we haven’t given information on the difference between new bookings, I would say the larger — if you’re getting to the because most of the revenues are existing customers, if it’s — if you’re talking about renewals or new contracts on existing customers that would have the larger effect on contract duration. As we said, there was a trend towards longer-term deals, which extended the duration in terms of our existing customers.

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

Olivier Pomel: 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.

Taz Koujalgi: 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?

Olivier Pomel: Yeah. We report that in our Qs. That’s — the 40% has is higher than it had been. That’s mathematically true when net retention goes down with more consistency of new, you would have a higher percent. The 10 points, so the 10 points of growth or of our growth would be something that would be more consistent and not as dependent on the net retention.

Taz Koujalgi: Got it. Thanks very much.

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

Koji Ikeda: Hey, Olivier and David. Just 1 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 customers, say, like an LLM vendor? And then what was that contribution during 1Q? Thanks, guys.

Olivier Pomel: So it’s — you can see it as the customers that are either selling AI themselves. So that would be LM vendors and the like. Our customers whose whole business is so is built on differentiated AI technology. And we’ve been fairly selective in terms of who we put in a category because companies everywhere are very eager to said that they differentiate we are today. So this is an illustration basically of the new kinds of businesses we’ve seen emerge, I would say, in the past year, 1.5 years, two years. In some cases, it might be divisions of existing larger companies, but in most situations, these are fairly recent and newer companies.

David Obstler: 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.

Koji Ikeda: Got it. That’s super helpful. Thank you very much for taking the question.

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

Patrick Walravens: 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 the — or your thoughts around the return to in-person events like this?

Olivier Pomel: So overall, we’re actually very happily surprised. So we have decided to go to put Dash in San Francisco this year. So we switch 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 our stories about or get people into price to show up. And 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 roads. And so overall, the time was very good. The conference was very productive. That was very, very good. 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 an 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.

Patrick Walravens: Okay. Thanks, Olivier.

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

Gregg Moskowitz: 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. And I’m just wondering if you have any thoughts as to why the usage growth for existing customers may have downtick this quarter? Anything come across?

Olivier Pomel: Well, I think it’s — look, at the end of the day, we have a slightly different customer mix than some of the other folks. There are some optimizations that are with others that are special to cloud that maybe it’s also specific to different clouds of which we have a different mix than the rest of the industry. So when you combine all of that, you might see some different timing effects in terms of how various optimization might heat us versus others. So I wouldn’t read too much into that. I think the trends are broadly the same as what you see anywhere in the industry. And the other participants are also quite careful about not calling an IBM (ph) to all of the optimization. So are we, even though from the behavior we see from our — who we think of other customers, who are the most at risk of optimization. We feel better about the path we see them tech and the usage trends we see of late.

Gregg Moskowitz: 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. So 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.

Olivier Pomel: The largest customers there tend to use almost all of our security products today. Sometimes there are some exceptions. And these are customers that tend to be on the tech forward mid-market higher-end of the market side that deployers world-to-world in their organizations. Typically, the customers that have us in a six- figures are above tend to be — can be enterprise or mid-market, but the ones that are mid and above tend to be mid-market and more tech forward. And I would say overall, the adoption tracks the — the adoption in the industry of a unified DevSecOps as a practice. And again to zoom out a little bit, we believe that this is where the whole industry is going. And we’re building a product with completely ready and we have a fully mature end-to-end solution that is relevant to every single possible customer.

So that by the time this becomes with general practicing in industry where we no-brainer choice for all of those customers and so-far we’re pleased with what we’re doing there.

Gregg Moskowitz: Very helpful. Thank you.

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

Olivier Pomel: 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’s around the world for a Q2 that was very well-executed. And I want to thank all of our customers for making DASH last week such a vibrant conference and making some products here in terms of conversations we’ve had with them. And with these good words, thank you all.

Operator: This concludes today’s conference call. Thank you for participating. You may now disconnect.