Datadog Inc
NASDAQ:DDOG
Earnings Call Analysis
Q3-2023 Analysis
Datadog Inc
Datadog's unified Software as a Service (SaaS) platform has witnessed strong multi-product adoption from customers. The company's emphasis on integrating Artificial Intelligence (AI) capabilities—to deliver differentiated value through features such as the Bits AI assistant, AI-generated synthetic tests, and AI-led error analysis—portrays its commitment to innovative customer solutions. With substantial customer wins, including significant deals across various sectors such as dental care, FinTech, convenience retailers, federal agencies, and industrial conglomerates, Datadog has demonstrated its key role in supporting migrations to cloud environments and operational optimizations, often replacing legacy systems and conflicting tools.
Datadog's third-quarter (Q3) revenue soared to $548 million, marking a 25% increase year-over-year and a 7% growth from the previous quarter. Usage growth trends have improved compared to the second quarter (Q2), with larger customers growing at a slower pace than smaller ones but showing an upswing across the board. This trend underlines Datadog's strong performance at the beginning of the fourth quarter (Q4). The company also reported a healthy trailing 12-month net revenue retention slightly below 120% and a consistent gross revenue retention in the mid to high 90s, reflecting the mission-critical nature of its platform.
Datadog experienced a steady climb in revenue growth both in North American and international markets. Despite ongoing customer optimizations, the impact on usage seems to be moderating, suggesting that cost management practices may become less intense and widespread. With a net income per share expected to be $0.42 to $0.44 for Q4 and $1.52 to $1.54 for fiscal year 2023, based on estimated 355 million weighted average diluted shares, the company continues to reassure investors of its stable and promising financial trajectory. For the full fiscal year 2023, revenues are anticipated to reach between $2.103 billion and $2.107 billion, a sign of confident, continued expansion.
The operational discipline of Datadog is highlighted by a 17% year-over-year growth in operating expenses, improved gross margins at 82.3%, and a significant operating income of $131 million. These figures eclipse past performance, propelling the operating margin to 24%. With impressive cloud cost efficiencies contributing to this robust margin, Datadog also showcases a strong balance sheet, ending the quarter with $2.3 billion in cash, cash equivalents, and marketable securities. The free cash flow stood at $138 million, keeping a healthy cash flow margin of 25%. Such solid financial health points to Datadog's remarkable ability to translate its operational success into tangible financial results.
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Good day, and thank you for standing by. Welcome to the Third Quarter 2023 Datadog Earnings Conference Call. [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.
Thank you, [ Gigi ]. Good morning, and thank you for joining us to review Datadog's third quarter 2023 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pomel, Datadog's Co-Founder and CEO; and David Obstler, Datadog's CFO. During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the fourth quarter and the fiscal year 2023 and related notes and assumptions, our gross margins and operating margins, our product capabilities, our ability to capitalize on market opportunities and usage optimization trends. The words anticipate, believe, continue, estimate, expect, intend, will and similar expressions are intended to identify forward-looking statements or similar indications of future expectations. These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-Q for the quarter ended June 30, 2023. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended September 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. We are pleased with our execution in Q3. We delivered another quarter of profitable growth and robust notable bookings and we continue to broaden our platform to have customers become and grow digital businesses. Let me start with a review of our Q3 financial performance. Revenue was $548 million, an increase of 25% year-over-year and above the high end of our guidance range. We ended with about 26,800 customers, up from about 22,200 last year. We ended the quarter with about 3,130 customers with an ARR of $100,000 or more, up from about 2,600 last year. And these customers generated about 86% of our ARR. And we generated free cash flow of $138 million with a free cash flow margin of 25%. Turning to platform adoption. Our platform strategy continues to resonate in the market. As of the end of Q3, 82% of customers were using two or more products, up from 80% a year ago. 46% of customers were using 4 or more products, up from 40% a year ago and 21% of our customers were using 6 or more products, up from 16% last year. Now let's discuss this quarter's business drivers. In Q3, we saw usage growth we've seen customers improve compared to Q2. Overall growth in Q3 was relatively consistent throughout the quarter and comparable to levels we've seen in Q1. We are seeing signs that the cloud optimization activity from some of our customers may be moderating. As a reminder, last quarter, we discussed a cohort of customers who began optimizing about a year ago and we said that they appear to stabilize their users growth at the end of Q2. That trend has held for the past several months with that cohorts usage remaining stable throughout Q3. Overall, we continue to see impact from optimization in our business. But we believe that the intensity and breadth of optimization we've experienced in recent quarters is moderating. Meanwhile, our new logo activity has remained robust. New logo bookings continue to scale and grow year-over-year. And for the second quarter in a row, we closed a record number of new deals with more than $100,000 in annual commitment. With our Land and Expand model, we expect new logos to turn into much larger customers over time as they lead into the cloud and add up more and more products. Finally, regarding customer growth, we are pleased with the new logos, new workloads and new product attaches we added this quarter. We added a number of exciting new customized in Q3, and I'll discuss a couple of examples later. Note that our total customer count is largely driven by our long tail of very small customers, while our sales motions are more targeted to the middle and high end of our prospects. And as a reflection of our team's strong execution, our net adds of customers over $100,000, saw an increase in Q3 compared to Q2. Despite a more cost-conscious demand environment over the past year, our business has continued to grow across product lines and we are very proud to achieve several key milestones. First, our infrastructure monitoring ARR exceeded $1 billion. Today, our infrastructure products cover monitoring the performance of hosts, networks, containers, Kubernetes deployments, saves functions and other aspects of infrastructure in the cloud as well as a full set of AI and machine learning tools to help our customers separate signal for noise. Second, our APM suite, which includes core APM, Synthetics, Real User Monitoring and Continuous profiler, exceeded $500 million in ARR, and we continue to expand our capabilities in APM, most recently with single-step instrumentation, which allows a single engineer to enable APM across all applications without core changes and we ship advances in mobile app monitoring, including mobile application testing and mobilization replay. Third, our log management product exceeded $500 million in AR. We also continue to expand our capabilities in load management. And with Flex logs, customers can easily scale storage and compute separately, allowing for new very high-volume logging use cases in a cost-effective manner. From the very beginning, my cofounder Alexis and I had a vision to create a unified platform that serves end-to-end use cases across datasets, products and SIM boundaries. We believe that these ARR milestones and their balance across the 3 pillars of observability demonstrate that Datadog is unique within the industry in establishing true platform value for customers. And of course, even though these products have become significant in size, we are only just getting started. We will continue to innovate to deliver more solutions for our customers across observability and beyond. I will add that we have empathy for our customers in their pain points, in part because we are ourselves users of cloud and next-gen technologies at a meaningful scale and we extensively deploy a user on solution, which is appropriately known as dog footing. As an example, we have extensively relied on our cloud cost management product as we expanded its capabilities this past year. And the use of our product has played a large role in delivering cost performance and efficiency improvements, optimizing our own cloud usage and ultimately resulting in expansion of our gross margins in recent quarters. We also continued to innovate in the depth take-up space. Our recent expansions in cloud security include cloud SIEM investigator, where customers can visualize logs over a long period of time to conduct security investigations. And within our cloud security management product, we have introduced Cloud Infrastructure Entitlement Management, or CIEM, to help customers prevent identity and access management security issues. For a few years now, the industry has been talking about the idea of DevSecOps, the breaking down of silos among development, operations and security teams. And we entered the security space on the premise that DevOps and security teams should share the same data in the same platform. So starting this month, we are making the practice of DevSecOps easy to adopt for all customers by bringing together all the components needed to fully monitor and secure their entire stack with 2 simple packages. First, with infrastructure DevSecOps, our customers can observe and secure their entire cloud environment in one package. With a simple purpose price and a single agent deployed, customers get end-to-end visibility into performance, availability and security issues in one place. And from that one place, teams can also quickly remediate problems using built-in workflows and without any code or contribution changes. Second, with APM DevSecOps, we take this one step further. Customers can instrument cloud applications for both performance and generality issues in one single package enabled with the same unified agent used for infrastructure DevSecOps. APM DevSecOps complements infrastructure DevSecOps by surfacing open source and code level security viabilities alongside performance issue. Finally, we continue to be excited about the opportunity in generative AI and Large Language Models. First, we believe adopting NextGen AI will require the use of cloud and other modern technologies and drive additional growth in cloud workloads. So we are continuing to invest by integrating with more components at every layer of the new AI stack and by developing our own LLM observability products. And while we see signs of AI adoption across large parts of our customer base, in the near term, we continue to see AI-related usage manifest itself most accurately with next-gen AI native customers who contributed about 2.5% of our ARR this quarter. In the mid- to long term, we expect customers of all industries and sizes to keep adding value to their products using AI and to get their early explore -- to get from early exploration to development into production, thus driving larger cloud and observability usage across our customer base.
Besides observing the AI stack, we also expect to keep adding value to our own platform using AI. Datadog's unified platform and purely SaaS model, combined with strong multiproduct adoption by our customers generates a large amount of deep and precise observability data. We believe combining AI capabilities with this broad data set will allow us to deliver differentiated value to customers. And we are working to product that is differentiated value through recently announced capabilities such as our bid Bits AI assistant, AI generated synthetic test and AI-led air analysis and resolution, and we expect to deliver many more related innovation to customers over time. Let's move on to sales and marketing, where we continue to execute on both new logos and existing customers. So let's discuss some of our wins. First, we founded 7-figure land over 5 years with a leading provider of dental care. This company's legacy monitoring just didn't cut and it contributed to delay with their migration to Azure. What's concerning to them was that customers notice poor application performance and were complaining publicly on social media. By adopting 6 Datadog products, they expect to find and fix the vast majority of incidents internally before their customers are affected. And in signing a 5-year deal, this customer showed its confidence in Datadog as a long-term partner in their migration. Next, we signed a 7-figure land with a South American fintech company. By moving from basic built-in cloud monitoring, legacy tooling and open source tools to Datadog, this customer expects to significantly reduce costs by spending less on tooling, reducing time to resolution and giving time back to engineers to innovate on their own products.
Next, we signed an 8-figure renewal over 3 years with a major American chain of convenience stores. With this expansion, Datadog will bring all aspects of these customers' tech systems into one platform, including their applications, hybrid cloud, network, in-store IoT technology, point-of-sale systems, self-serve kiosks, fuel pumps and corporate infrastructure. This will free up employee time to focus on customer service with expectations to save millions of dollars annually. This customer plans to use 6 Datadog products replacing 3 commercial observability tools. Next, we signed a 7-figure expansion with a major U.S. federal agency. When we first started working with this customer a year ago, Datadog was approved for a limited subset of programs. But as we have demonstrated value and gain eternal adoption, this customer is now deploying Datadog across the entire agency. They have a added 6 Datadog products, and by doing so, consolidated out of 7 tools. Next, we signed a 7-figure expansion with a Fortune 500 industrial company. Customer was concerned with out-of-control costs with its legacy log management products and was using a dozen different tools. And when they began using Datadog, they noticed far fewer support tickets submitted to their reliability team. By growing set with Datadog and expanding to 7 products, this customer expects to deliver better service while saving time and reducing cost. And last, we signed a 7-figure expansion with a software business that is part of a tech hyperscaler. This long-term customer has used Datadog for infrastruction metrics and will now expand to adopt 7 Datadog products. Datadog will be replacing its commercial APM tool, which was well adopted by its engineers and led to inefficient troubleshooting outages and revenue impact. Our support of open telemetry, in particular, was key to their decision to expand with Datadog, that it makes it possible for APM tracing to be democratized and use across their entire DevOps team. And that's it for this quarter's highlights. I'd like to thank our go-to-market teams for their strong execution in Q3. Before I turn it over to David for a financial review, let me reiterate our longer-term outlook. As we have said throughout this period of cloud optimization and macro uncertainty, our long-term plans have remained unchanged. We continue to believe digital transformation and cloud migration are long-term secular growth drivers of our business and critical motions for every company to deliver value and competitive advantage. So we continue to invest aggressively to better our platform, and we aim to be our customers' mission-critical partners as they move to cloud and to modern DevSecOps With that, I will turn it over to our CFO, David.
Thanks, Olivier. Q3 revenue was $548 million, up 25% year-over-year and up 7% quarter-over-quarter. To dive into some of the drivers of this Q3 performance, first, regarding usage growth. We saw an improvement in usage growth in Q3 versus Q2. The Q3 usage growth was more similar to Q1 and relatively steady throughout the quarter. We had a very healthy start to Q4 in October. While it is too early in the quarter to know for sure, it will happen in the next couple of months, the trends we see in early Q4 are stronger than they've been for the past year. Regarding usage growth by customer size, we continue to see larger spending customer growth at a slower rate than smaller spending customers, but usage growth improved for all customer sizes in Q3 relative to Q2. And as Olivier discussed, we believe there are signs that the optimization activity we've been seeing is moderating. Last quarter, we discussed the cohort of customers who started optimizing about a year ago. This cohort's usage has been stable -- was stable throughout Q3. As we look at our overall customer activity, we continue to see customers optimizing but with less impact than we experienced in Q2, contributing to our usage growth with existing customers improving in Q3 relative to Q2.
While we expect cost management to continue, we believe we are seeing moderation that is still present but -- a moderation is still present, but is less intense and less widespread than we experienced in recent quarters. Geographically, we experienced similar sequential revenue growth in North America and in our international markets. And finally, as regard to retention metrics, our trailing 12-month net revenue retention was in line with our expectations and came in slightly below 120% in Q3. Our trailing 12-month gross revenue retention continues to be stable in the mid- to high 90s, a sign of the mission-critical nature of our platform for our customers. Moving on to our financial results. Billings were $607 million, up 30% year-over-year. Billings duration increased slightly year-over-year. Remaining performance obligations, or RPO, was $1.45 billion, up 54% year-over-year. Current RPO growth was about 30% year-over-year.
Over the past couple of quarters, we have seen an increasing preference from our customers to sign multiyear deals, and our weighted average booking duration was up sequentially and year-over-year. We see continued interest in multiyear duration deals in our pipeline as customers seek longer-term strategic partnerships with us. We continue to believe that revenue is a better indicator of our business trends than billings and RPO as those can fluctuate relative to revenues based on the timing of invoice and the duration of customer contracts. Now let's review some of the key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. Gross profit in the quarter was $451 million, representing a gross margin of 82.3%. This compares to a gross margin of 81.3% last quarter and 79.7% in the year ago quarter. As Olivier mentioned, we continued to experience efficiencies in cloud costs reflected in our cost of goods sold in the quarter as our engineering teams pursue cost savings and efficiency projects. Our Q3 OpEx grew 17% year-over-year. This is a decline from 26% year-over-year growth last quarter. We continued to execute on controlling costs given the uncertain environment. And Q3 operating income was $131 million for a 24% operating margin, up from 21% last quarter and above the 17% in the year ago quarter.
Our margins were higher than we expected in Q3 as our organic growth was higher than in Q2, while our internal optimization and cost management efforts were successful. Turning to the balance sheet and cash flow statements. We ended the quarter with $2.3 billion in cash, cash equivalents and marketable securities and cash flow from operations was $153 million in the quarter. After taking into consideration capital expenditures and capitalized software, free cash flow was $138 million for a free cash flow margin of 25%. And now for our outlook for the fourth quarter and for the full fiscal year 2023. A reminder, our guidance philosophy remains unchanged. We based our guidance on trends observed in recent months and apply conservatism on these growth trends.
For the fourth quarter, we expect revenues to be in the range of $564 million to $568 million, which represents about 20% to 21% growth year-over-year. Non-GAAP operating income is expected to be in the range of $129 million to $133 million and non-GAAP net income per share is expected to be $0.42 to $0.44 per share based on approximately 355 million weighted average diluted shares outstanding. For fiscal year 2023, we expect revenues to be in the range of $2.103 billion to $2.107 billion, which represents 26% year-over-year growth. Non-GAAP operating income is expected to be in the range of $453 million to $457 million and non-GAAP net income per share is expected to be in the range of $1.52 to $1.54 per share based on approximately 351 million weighted average diluted shares outstanding. Some additional notes for our guidance. First, we expect net interest income and net interest and other income for fiscal 2023 to be approximately $95 million. We expect tax expense in the fiscal year to be $12 million to $14 million. And finally, we expect capital expenditures and capitalized software together to be in the 3% to 4% of revenue range in fiscal 2023.
And now regarding 2024. It is too early for us to speak to 2024 revenue growth. We will digest the information we see over the next couple of months and give you our 2024 revenue guidance next quarter. As it relates to non-GAAP profitability, our operating income and margins were a little higher in Q3 than we targeted as usage growth improved from Q2 levels, and we were successful with our cost efficiencies.
We expect continued strong execution on profitability in Q4. At the same time, we continue to be excited by our numerous long-term growth opportunities and we have no shortage of investments to make and are confident in our ability to execute to strong ROI on those investments. As a result, while we are not providing 2024 margin guidance at this point, as always, we will balance our investments in long-term growth with margin discipline. And we will update you on that in more detail next quarter. With that, we will open the call for questions. Operator, let's begin the Q&A.
[Operator Instructions] Our first question comes from Mark Murphy of JPMorgan.
Congratulations on a very strong performance. Olivier, I'm interested in your mention of 2.5% of ARR being driven by the native AI providers. Should we think of that mostly consisting of open AI, LAMA, anthropic, Cohere, et cetera? Or are you meaning that as a slightly different reference? And can you just help us understand, is that up from close to 0 a year ago? And then I have a quick follow-up.
Yes. So it's a number of companies that, without naming anyone, so they tend to be model providers, but not just on the language side, like a providers on the language, image side, like there's a number of different -- or video side, there's a different types of communities there given some good pilot-type companies. These customers all had revenue 1 year ago, but they've been growing a little bit faster than the rest of the customer base recently. And the reason we did that in the crisis -- we -- today, we see the usage growth related directly to AI coming mostly for these customers that provide models to others. Whereas we see broad usage of AI functionality across the customer base, but at low volumes, and it corresponds to the fact that for most customers or most enterprises really, they're still in the early stages of developing and shipping applications. So for now, the usage is concentrated among the model providers.
Okay. Yes. That make sense. And Olivier, as a quick follow-up, you mentioned the log management has cost $500 million in ARR. It's quite a milestone. You also mentioned the replacement of some legacy products. I'm curious if you see the acquisition of Splunk or any other acquisition activity in that market as a beneficial development. I'm just wondering if small customers or other companies that have been provided, that have been acquired, excuse me, might be looking for any alternatives out there that are more modern and a more converged platform and if you're seeing that in the pipeline.
I mean, we've seen that for a while now that customers were looking for more integrated platforms, more model offerings, things that were more cloud first. And that's been one of the reasons of our success in landing largely in brand-new applications, brand new environment, brand new cloud initiatives and then over time, consolidating our customers away from whatever they were using in the legacy. We don't think that it is going to change with the various acquisitions and tech privates that we've seen over the past quarter. So we think we will just see more of that over time. One exciting bit on your first question, interesting bit, if you -- as I know many of you are trying to understand what the AI landscape is made of. Interestingly enough, the -- when we look at our cohort of customers that are that we consider to be AI native and built largely on AI in all AI providers, they tend to be on different clouds. What we see is that the majority of those companies actually have a lot of their usage on AWS. Today, the larger part of the usage or the larger of these customers are on Azure. So we see really several different adoption trends there that I think are interesting to the broader market.
And our next question comes from Sanjit Singh of Morgan Stanley.
Olivier, the company has been innovating throughout this downturn quite aggressively across core observability, security as well as AI. As we look into 2024, and we think about a potential new product cycle for Datadog, what parts of the portfolio do you think could be contributors either in 2024 -- later in '24 and 2025, what are the things that you face to customers will be most respective to? Just wanted to get a sense of where you think where the sort of the timing of some of these new products that you've been delivering over the past couple of years.
Well, the -- mathematically, the products that will contribute the most to the growth next year are going to be the products that have been here the longest in the core observability products. We mentioned $1 billion in infrastructure, $0.5 billion in APM, $0.5 billion in logs. This is great, but still a small fraction of these products can be at scale, and we are primarily going after that. There's a number of other things we've been investing in and growing and we're fairly happy with the way things are going in security, as I mentioned on the call, we saw new packaging, we've also rolled out. And some of the new initiatives that stand, I would say, a little bit left or right of what we've been doing in observability. This year, as you mentioned, was a year of innovation for us. I think it was also a year of cost optimization for customers. It's not necessarily the best year to get products to very quick -- extremely quick revenue growth, but we've planted a lot of seeds that we think are going to deliver in the next couple of years.
That's great. And then I had a sort of a follow-up question on the sort of new packaging for the DevSecOps, the new package. I was wondering if you could just give us a little bit of color around why you sort of what was the packaging approach and what you're trying to solve for? Is it sort of trying to adopt the capabilities in a single integrated capability? Or is it also about sort of consolidated pricing being potentially 1 SKU, 1 SKU price or to consume all these capabilities. So I just love some detail around -- on the motivation for these new packaging.
Yes. A couple of things. So the first one is we security products have reached a certain level of maturity. And so we think they can be brought into the conversation with a larger set of our customers as opposed to being something that our customers sell select to which is how we started and how we start with most products really. But also we're trying to bring those products in the same conversation as the initial adoption of DevOps basically as opposed to having to branch that conversation into, oh, hey, you're doing operations and applications and can I interest you in some security with that, which would be a different conversation. So we -- so far, the signs for this are encouraging. And again, we think it goes with the broader market trends, the adoption of DevSecOps and what customers actually want to do, and we think is going to help them deliver better outcomes in security. But obviously, it's still -- we just rolled that out. So it's still too early to tell whether we got it right or whether we still need to tweak it a little bit.
And our next question comes from Raimo Lenschow of Barclays.
Congrats from me as well. Olivier, like we're almost a year into this kind of current situation and you saw Q2, obviously, saw the digital natives that you commented, just kind of having extra savings, but we're now back to kind of Q1 usage pattern. What do you see in terms of changing behavior on customers, not thinking into market. More like how do you think about observability and how that potentially would change the world as we think about '24, '25 coming out of this in terms of kind of vendor consolidation, how to kind of build observability, et cetera? And then I have one follow-up for David.
So we think the trends of vendor consolidation will continue. So basically, customers are getting more of it -- more mature in their needs, they're getting further into the cloud. And they're -- as part of that, they will want to add lesser integrators. And if they can use one platform instead of 12 different products, that's something that they all react very positively to and we see that again and again as we expand into our customers. In terms of the broader trends, I think we -- it's too early to tell exactly what the next couple of quarters are going to be made of. We said -- it looks like we've hit an inflection point. It looks like there's a lot less overhang now in terms of what needs to be optimized or could be optimized by customers. It looks like also optimization is more -- is less intense and less widespread across the customer base. So all that is positive. Now there's still quite a bit of uncertainty in the macro environment. So I don't think we should get ahead of ourselves either and declare that it's the end of it for the foreseeable future. So we feel positive about things. But it's still hard to know exactly what's going to happen in a couple of quarters from now.
From a buying behavior perspective, we've never seen customers really slow down in their intent to move to the cloud and direct adoption of new platforms, new products from us. We've done well, we scaled the New Logo acquisition with scale, the new product Hitachi. So that has been a constant throughout this optimization phase. In terms of the user growth and customers scaling new workloads, I don't think we're back to the exibirant times of 2021. But maybe we are reverting back to the mean of what was happening before that.
Okay. And if I can squeeze one quick one and David, we talked about OpEx and OpEx growth and this quarter was lower than others. Should I read your comments about next year. And clearly, there is a big investment opportunity that OpEx growth like maybe wasn't quite where you wanted it to be? Just any comment there? And I know you just can't guide.
Yes. I think as we talked about the movement of the top line because of consumption moves more quickly than we can adjust resources. So we've taken more of an optimization and cost prioritization this year. But we offset that, we do think there's a very large opportunity. So we are expecting to increase the level of investment. But as we say that, we've always been looking at the balance between maximizing the top line growth with producing profit and are going to continue to operate on that taking advantage of the long-term opportunities.
And our next question comes from Karl Keirstead of UBS.
Maybe David, I'll direct this to. I was intrigued by your comment that the fourth quarter, the month of October was off to a healthy start understanding that that's just a month. But just curious if you could unpack that a little bit, largely because investors on this call, we are picking up signals from other tech firms that would suggest a still very tough macro environment or maybe even slightly tougher. So I'm just curious where you might be seeing pockets of strength, if you could add a little more color.
Yes. I think it's just essentially what we try to do in the last couple of quarters is to cushion everybody that we still expect that there will be optimization and cost management, but give everyone a flavor for the direction. And what we're seeing, as I think Olivier and I mentioned, we're seeing the continuation of that but at a more moderated level and that was across the customer base. So we're seeing essentially clients leaning a little more into growth, again, early in the quarter, too early to call it, but the trends seem to be a moderation of the previous cost management and optimization, although it's still continuing.
Yes, those color on the -- so yes, we had a healthy start to Q4. We we see trends that are as strong as they've been for the past year in terms of what happened early in the quarter. That being said, Q4 is a tough quarter to call because it has fairly high seasonality. There's a typically a drop of usage in the -- at the very end of the quarter with the holidays. And that drop in different years has been -- can be more or less pronounced. Last year, in particular, it was very pronounced. So we're -- we've given guidance with all that in mind, basically.
Let me just add because this question has been talked about. Like last quarter, we didn't take the strength of October account, we took the exact same guidance approach, which was to take the weighted average historical trends and discount apply conservatism. So like last quarter, we had said that the first quarter looked a little more stable. We didn't take that into consideration on our guidance. And we have stuck to the exact same guidance methodology, which is to act with that conservatism.
One last thing to -- just to comment on that. Because I know a lot of you are trying to understand how we fit with respect to the Large cap providers and core trends correspond to theirs. Remember that we are -- while our trends are similar in the long run, we, in the short term, there can be differences of timing in terms of when we're going to see certain effects where they're going to see them. We also have a different mix where the mix of cap provider is not exactly the same as the border market and a different mix of customers and geographies than the individual cloud providers as well. So things are not exactly one to one there.
Our next question comes from Matt Hedberg of RBC.
And I'll offer my congrats as well. Oli, I wanted to double-click on some of the improved usage trends. Can you provide us with an overview on how some of your large sort of strategic customers think about optimization is really part of an ongoing IT spending strategy, coupled with what's driving some of these increased uses. I guess I'm wondering have IT executives from your perspective changed their view on the level of monitoring needed with new levels of workload?
No. So they didn't change if you on the level of monitoring needed. I think they try to save money wherever they could save it. By far, the biggest area they can save in their cloud infrastructure is their cloud deal itself. As a reminder, when customers pay $1 to us, they pay $10 or $20 to their cloud provider. So there's a lot more sales to be had there. But these savings flow down to us. We charge commercial rate to the size of our customers infrastructure. They also tried to save what they could in observability specifically. And usually, there's always a bit of that you can cut. It can always sample certain things a bit more, you can retain your loss a bit less. You can remove some of the debug logging like things like that, that can drive your cost up, but don't necessarily generate a ton of value. And that's the behavior by the way, that we see all the time. Like we see it for most customers, once a year, maybe twice a year, sometimes usually before contract renegotiations and things like that, why they try to understand what they're going to need for the next 2 or 3 years. The big difference over the past year has been that everybody has been doing that at once and multiple times. It was really an environment where everyone was feeling very uncertain about the economy and needed to save money very quickly. So we expect optimization to continue as part of this macro trend in the near future. And in perpetuity after that, we'll have that continuous cycle of customers optimizing reducing what they can reduce and then growing workloads and maybe creating a little bit more mass over time as well. And then optimizing again on a regular basis, not everyone at the same time.
And our next question comes from Fatima Boolani of Citi.
One for Oli and one for Dave, if I may. Olivier, the packaging and pricing motions that you discussed for the DevSecOps solution set. I wanted to zoom out generally a little bit in knowing what you know about how buying behavior and procurement behavior for a lot of your customers has changed over the course of this past year. I was wondering if you can kind of shed light on how you're thinking about an ELA or EAA-type selling motion. I know it's something that historically you've been averse to, but I'm curious how you're thinking about it in sort of the current day and age, if you will, in terms of how your customers have changed the way they're buying and deploying. And then for David, just wanted to get a sense of what expectations on net retention rates are built into your guidance? And in other words, should this be the quarter that we see a trough in extension rates or net retention rates as you're thinking about it in the guidance?
Yes. So on the ELAs, so in general, look, we're always very open to new approaches in packaging. We try to see core things are consumed from the customer side and what makes the most sense to them. Now ELAs and things that are very difficult or very inappropriate for a business like ours. One because we are fully SaaS-based and there's a very, very large volume dimension to absolutely everything we do for our customers. So it's very, very hard to provide one price it all -- for them. We also philosophically, we like to have -- to get signal from what customers are willing are not willing to pay for. And that drives a lot of our product innovation. We had a lot of good news this way because customers want to buy products and they scale them a lot. We'll also get bad news. We get customers who don't find there is enough value in a given product or think it should be doing more or I think you should be doing things differently or seems that the packaging doesn't make sense. And we like to have that. The reason why we simplified the pricing there, and we created those new SKUs is really to try and change the motion a little bit and integrate further the observability in the security side and make it easier to bring security into the conversation for these customers. So far, we have some early evidence that it's it seems to reason it, but it's way where we're too weary to call it. We'll need 2, 3 quarters of that to understand the implications of the new packaging.
Yes. And as it relates to net retention, we do not provide guidance, but just the way that we think about it and some of the drivers, we don't provide guidance, sorry, on net retention per se. But essentially, what we said was that Q3 organic growth was similar to what it was in Q1. And we have said previously that in Q2 and Q3 of last year, we had lower than before but higher than the Q1 -- Q4, Q1 and now Q3. So it really is a matter of lapping those comps. The comps have gotten increasingly easy to lap. And we will let everybody know if we do produce an organic growth that's higher this Q4 than it was in Q4 last year, we will have, in this period, trough in net retention and it will begin to head up. So that's sort of how we think about it. In terms of our guidance, that's a different story. As we said, we provide conservatism. So what's implicit in the guidance is something worse than we're experiencing, which would apply a lower organic growth. But in terms of the business trends themselves, it's really a matter of do we lap the Q4 and produce a higher organic growth in this -- in the Q4 coming up than we had in the Q4 last year.
And our next question comes from Brent Thill of Jefferies.
David, I was curious if you could focus on the enterprise traction and what you're seeing and maybe for Olivier. David, I guess, on the customer add, you're 700 and that's lower than your normal accruals out of 1,000-plus per quarter. Can you just talk about is that number being misled because the enterprise traction is higher and that number is, therefore, going to be lower? Could you just drive into that a little bit?
Yes. As a reminder, we have a broad range of customers in the long tail. And similar to what we discussed last quarter, the gross number of ads, so the accumulation and in the enterprise, it was quite strong, was very similar to what we've experienced. And we have a very small tail that has a larger attrition rate doesn't have a lot of dollars attached to it. So the trends continue, which is very strong, as Olivier mentioned, new logo accumulation both in terms of number of new logos and ARR, and that was true when Olivier talk about the enterprise side of it. offset by this tail that has very little dollars associated with it.
Yes. And just to comment on that, remember, the bottom half of our customer represents around 1% of our revenue. and the lower increase in customer number comes from the very, very low end, which is customers that pay us in the tens of dollars a month. And those customers we're getting a little bit less of those to start with. I think that's part of the economical environment. and the churn is a little bit higher than it used to be there, too. So that's why these numbers are bit depressed right now. That being said, we had a record number of new logos over $100,000. We're doing very well in the enterprise. We're doing very well in the new market also. We're also doing very well at the high end of the SMB. So we are very happy with all of the segments we're targeting with our sales and marketing motions today. On the enterprise side, we actually mentioned a few of those very exciting contracts on the core. We get really, really excited when we see very traditional enterprises moving to the cloud and adopting us and consolidate in world to all. David, is -- we consider in the room, David's smiling because he's excited when he sees the dental care company is excited when you see the network of convenience stores where we even instrument the fuel pumps. So these are great developments for us, and we're leaning hard into that.
And our next question comes from Kash Rangan of Goldman Sachs.
I'm sure that you're all smiling at your results. Two things. One is -- with respect to LLM monitoring, which was demo the DASH conference, which was I thought absolutely fascinating. I know you quantified, Oli, 2.5 percentage points of growth coming from general AI workloads. How do we think about the revenue opportunity for LL monitoring that it's at an early stage? And I also have a second question, slightly more controversial that when and if we run it to customers that think they're spending their bills for Datadog are getting to be a little bit on the larger side, that is a sign of success. But how do you ensure that, that success does not work against the company that it opens up the door for price competition from others?
Yes. So on the DevSecOps side, I think it's too early to tell how much the revenue opportunity there is in the tooling specific lab there. When you think of the whole spectrum of tools, the closer you get to the developer side to how are is to monetize and the further you get towards operations and infrastructure, the easier it is to monetize. You can ship things that are very useful and very accretive to our platform because they get you a lot of users, a lot of attention and a lot of stickiness that are harder to monetize. So we'll see where on the spectrum that is. What we know, though, is that broader Generative AI up and down the stack from the components themselves, the GPUs all the way up to the models and the various things that are used to orchestrate them and store the data and move the data around all of that is going to generate a lot of opportunity for us. We said right now, it's conciliated among the AI native largely model providers. But we see that it's going to broaden and concern a lot more of our customers down the road. And your second question was, so when we grow a lot, we are very successful with some customers, how do we not create a long-term issue where they spend a lot of money and that [indiscernible]. Look, it's a great situation to be in to have customers spend a lot of money on you and have to justify that value over time. I think it's very healthy. I think that, again, that would drive innovation and great product development. And our role there is to make sure we have a healthy partnership with customers every single step of the way. And we charge them an order of money to less than what they spend for their cloud infrastructure. Maybe two others are many to less than would spend on their R&D. And so we think we should be in a position of leverage where if we do our jobs right, we show a lot of value for our customers. We send them a lot of money. We make them a lot faster, and we have them generate a lot more revenue. So that's how we see things and we hold ourselves to.
And our next question comes from Alex Zukin of Wolfe Research.
Congrats on a great quarter. Maybe just two quick ones for me. Olivier, you mentioned the federal opportunity or you mentioned the federal activity in the quarter with a deal that was pretty interesting. That's something that we picked up is an area of excitement for you guys. Can you maybe just talk about what the opportunity there is over the next 12 months and beyond, maybe stack-ranked as a priority for you guys. And then I've got a quick follow-up.
So I missed the domain you're talking about, sorry. Feds. So that's definitely an area of investment for us. It's -- to look, we're happy with 2 things happening with the fact that we're moving further and further into the various level of certifications needed. We're happy with the early success with some agencies where we are spreading and in those government agencies and getting to go some of those world to all. But we are only scratching the surface of what we can do inside and there's a level we need to do. Some of it on the certification side, on the product side, and some of it on the go-to-market side and making sure we have all the parts of the motion working. So we -- I expect that to be one of the main areas of investment on the go-to-market side. Next year in terms of new markets we're going after.
Perfect. And then maybe on the -- back on the AI question. I guess maybe just we drill a little bit deeper within those AI native companies, the criticality of their database users, meaning are you seeing something different where -- in a world where these applications become more prevalent, there's the opportunity to kind of expand wallet share of observability becomes even more important. And how should we think about the growth opportunities from those types of workloads in either 2024 or 2025?
Yes. So in general, the more complexity there is, the more useful observability, the more you see his value from writing code to actually understanding it and observing it. So to caricature if you -- if you spend a whole year writing 5 lines of code that are really very deep, you actually know those 5 lines pretty well, maybe you don't observe because you'll see you understand exactly how they work and what's going on with them. On the other hand, if thanks to all the major advances of technology and all of the very super source AI and you can just very quickly generate thousands of lines of code, ship them and start operating them, you actually have no idea hwo these work what they do. And you need a lot of tooling observability to actually understand that and keep driving that and secure it and do everything you need to do with it over time. So we think that overall, this increases in productivity are going to favor observability.. In terms of the future growth of AI, look, I think like everyone, we're trying to guess how transformative it's going to be. It looks like it's going to be pretty is, if you judge from just internally, how much of that technology we are adopting a how much is the productivity impact, it seems to be having. So again, today, we only see a tiny bit of it, which is early adoption by model providers and a lot of companies that are trying to scale up and experiment and figure out who it applies to their businesses and what they can ship to use the technology. But we think it's going to drive a lot of growth in the years to come.
And our next question comes from Jake Roberge of William Blair.
Congrats on the great results. Olivier, you called out the 2.5 points from AI native customers a few times, but you've also said that the broader customer base should start adding AI workloads to our platform over time. When do you think that actually takes place and the broader customer base starts to impact that AI growth in more earnest?
We don't know. And I think it's too early to tell. For one part, there's some uncertainty in terms of -- these customers are being to figure out what it is they are going to ship to their own customers. I think everybody is trying to learn that right now and experiment it. And -- but the other part is also that right now, the innovation is largely concentrated among the model providers. And so it's rational right now for most customers to rely on those instead of they're deploying their own infrastructure. Again, we think it's slightly going to change. We see a lot of demand in interest in other ways to host models and run models and customers and all those things like that. But today, that's the -- these are the trends of the market today basically.
Okay. Helpful. And then just a follow-up on the optimization front. It sounds like the early optimizers took about a year to complete those initiatives. But what type of time lines are you seeing from kind of the second or third layer of customers that started their optimizations later in the game. Have those also started to stabilize given they weren't as large as the early optimizers? Just trying to kind of parse out the customer base there.
Yes. So we don't really know for sure. That's also why we are careful not to call an end to it forever. I would say that for customers that are not part of this initial cohort, there's less of an overhang. So the customers that were the early optimizers and that had the most acute optimization tended to be cloud native, so all in on the cloud, very heavy on IT spend in general and the -- substantially all of their IT being in the cloud. They tended to be also companies that were slightly high growth but low profitability that needed to pivot their financials over a fairly short amount of time. I think if you look at the rest of the customer base, they are mostly not in that situation. So we expect the behavior to be different.
Thank you. This concludes the question-and-answer session. I would now like to turn it back to CEO, Olivier Pomel for closing remarks.
Thank you very much. I want to thank everyone for attending the call today. I also want to take the opportunity to thank our customers for their trust. We know these are trying times with all the macro uncertainty and we thank them for their trust. I also want to thank our employees, all the Datadogs for a quarter of hard work and great successes. And on these good words, we'll all get back to work and get busy for the end of the year. So thank you very much.
This concludes today's conference call. Thank you for participating, and you may now disconnect.