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

Datadog, Inc. (NASDAQ:DDOG) Q3 2023 Earnings Call Transcript November 7, 2023 8:00 AM ET

Company Participants

Yuka Broderick – VP, IR & Strategic Finance

Olivier Pomel – Co-Founder & CEO

David Obstler – CFO

Conference Call Participants

Mark Murphy – JP Morgan

Sanjit Singh – Morgan Stanley

Raimo Lenschow – Barclays Capital

Karl Keirstead – UBS

Matt Hedberg – RBC Capital Markets

Fatima Boolani – Citigroup

Brent Thill – Jefferies

Alex Zukin – Wolfe Research

Jacob Roberge – William Blair

Operator

Good day, and thank you for standing by. Welcome to the Third Quarter 2023 Datadog Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker’s presentation, there will be a question-and-answer session. [Operator Instructions] Please be advised that today’s conference is being recorded.

I would now like to hand the conference over to your speaker today, Yuka Broderick, Vice President of Investor Relations. Please go ahead.

Yuka Broderick

Thank you, Dee. Good morning, and thank you for joining us to review Datadog’s third quarter 2023 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pomel, Datadog’s Co-Founder and CEO; and David Obstler, Datadog’s CFO.

During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the fourth quarter and the fiscal year 2023, and related notes and assumptions, our gross margins and operating margins, our product capabilities, our ability to capitalize on market opportunities, and usage optimization trends. The words anticipate, believe, continue, estimate, expect, intend, will, and similar expressions are intended to identify forward-looking statements or similar indications of future expectations. These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our form 10-Q for the quarter ended June 30th, 2023. Additional information will be made available in our upcoming form 10-Q for the fiscal quarter ended September 30th, 2023 and other filings with the SEC. This information is also available on the Investor Relations section of our website along with a replay of this call.

We will also discuss non-GAAP financial measures which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com.

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

Olivier Pomel

Thanks, Yuka, and thank you all for joining us this morning. We are pleased with our execution in Q3, as we delivered another quarter of profitable growth and robust new logo bookings, and we continue to broaden our platform to have customers become and grow digital businesses.

Let me start with a review of our Q3 financial performance. Revenue was $548 million, an increase of 25% year-over-year and above the high end of our guidance range. We ended with about 26,800 customers, up from about 22,200 last year. We ended the quarter with about 3,130 customers with an ARR of $100,000 or more, up from about 2,600 last year. And these customers generated about 86% of our ARR. And we generated free cash flow of $138 million with a free cash flow margin of 25%.

Turning to platform adoption. Our platform strategy continues to resonate in the market. As of the end of Q3, 82% of customers were using two or more products, up from 80% a year ago, 46% of customers were using four4 or more products, up from 40% a year ago, and 21% of our customers were using six or more products, up from 16% last year.

Now let’s discuss this quarter’s business drivers. In Q3, we saw usage growth of existing customers improve compared to Q2. Overall growth in Q3 was relatively consistent throughout the quarter and comparable to levels we’ve seen in Q1. We are seeing signs that the cloud optimization activity from some of our customers may be moderating. As a reminder, last quarter, we discussed a cohort of customers who began optimizing about a year ago, and we said that they appear to stabilize their usage growth at the end of Q2. That trend has held for the past several months, with that cohort’s usage remaining stable throughout Q3.

Overall, we continue to see impact from optimization in our business, but we believe that the intensity and breadth of optimization we’ve experienced in recent quarters is moderating. Meanwhile, our new logo activity has remained robust. New logo bookings continue to scale and grow year-over-year. And for the second quarter in a row, we closed a record number of new deals with more than $100,000 in annual commitments. With our land and expand model, we expect new logos to turn into much larger customers over time as they lean into the cloud and add up more of our products.

Finally, regarding customer growth, we are pleased with the new logos, new workloads, and new product [indiscernible] we added this quarter. We added a number of exciting new customers in Q3, and I’ll discuss a couple examples later. Note, that our total customer count is largely driven by our long tail of very small customers, while our sales motions are more targeted to the middle and high end of our prospects. And as a reflection of our team’s strong execution, our net ads of customers over $100,000, saw an increase in Q3 compared to Q2.

Despite a more cost-conscious demand environment over the past year, our business has continued to grow across product lines, and we are very proud to achieve several key milestones. First, our infrastructure monitoring ARR exceeded $1 billion. Today, our infrastructure products cover monitoring the performance of hosts, networks, containers, Kubernetes deployments, serverless functions, and other aspects of infrastructure in the cloud, as well as a full set of AI and machine learning tools to help our customers separate signal from noise.

Second. Our APM suite, which includes core APM, synthetics, real user monitoring and continuous profiler exceeded $500 million in ARR. And we continue to expand our capabilities in APM, most recently with single step instrumentation, which allows a single engineer to enable APM across all applications without code changes and we achieved advances in mobile app monitoring, including mobile application testing and mobile session replay.

Third, our log management product exceeded $500 million in ARR. We also continue to expand our capabilities in log management, and with Flex logs, customers can easily scale storage and compute separately, allowing for new and very high-volume logging use cases in a cost-effective manner. From the very beginning, my Co-Founder [Alexi] (ph) and I had a vision to create a unified platform that serves end-to-end use cases across datasets, products, and team boundaries. We believe that these ARR milestones and their balance across the three pillars of observability demonstrate that Datadog is unique within the industry in establishing true platform value for customers. And of course, even though these products have become significant in size, we are only just getting started. We will continue to innovate to deliver more solutions for our customers across observability and beyond.

I will add that we have empathy for our customers and their pain points, in part, because we are ourselves users of cloud and next-gen technologies at a meaningful scale. And we extensively deploy a new [indiscernible] solution, which is appropriately known as dog fooding. As an example, we have extensively relied on our cloud cost management product as we expanded its capabilities this past year. And the use of our product has played a large role in delivering cost, performance, and efficiency improvements, optimizing our own cloud usage, and ultimately resulting in expansion of our gross margins in recent quarters.

We also continue to innovate in the DevSecOps space. Our recent expansions in cloud security include Cloud Sim investigator, where customers can visualize logs over long periods of time to conduct security investigations. And within our cloud security management product, we have introduced Cloud Infrastructure Entitlement Management, or CIEM, to help customers prevent identity and access management security issues.

For a few years now, the industry has been talking about the idea of DevSecOps, the breaking down of silos among development, operations, and security teams. And we entered the security space on the premise that DevOps and security teams should share the same data in the same platform. So starting this month, we are making the practice of DevSecOps easy to adopt for all customers by bringing together all the components needed to fully monitor and secure their entire stack with two simple packages.

First, with infrastructure DevSecOps, our customers can observe and secure their entire cloud environment in one package. With a simple per-host price and a single agent deployed, customers get end-to-end visibility into performance, availability, and security issues in one place. And from that one place, teams can also quickly remediate problems using built-in workflows and without any code or configuration changes.

Second, with APM DevSecOps, we take this one step further. Customers can instrument cloud applications for both performance and vulnerability issues in one single package, enabled with the same unified agent used for Infrastructure DevSecOps. APM DevSecOps complements Infrastructure DevSecOps by surfacing open-source and code level security vulnerabilities alongside performance issues.

Finally, we continue to be excited about the opportunity in generative AI and large language models. First, we believe adopting next-gen AI will require the use of cloud and other modern technologies and drive additional growth in cloud workloads. So we are continuing to invest by integrating with more components at every layer of the new AI stack and by developing our own LLM observability products. And while we see signs of AI adoption across large parts of our customer base, in the near term, we continue to see AI-related usage manifest itself most accurately with next-gen AI-native customers, who contributed about 2.5% of our ARR this quarter.

In the mid to long term, we expect customers of all industries and sizes to keep adding value to their products using AI and to get their early exploration — to get from early exploration to development and into production, thus driving larger cloud and observability usage across our customer base.

Besides observing the AI stack, we also expect to keep adding value to our own platform using AI. Datadog’s unified platform and purely SaaS model, combined with strong multi-product adoption by our customers, generates a large amount of deep and precise observability data. We believe combining AI capabilities with this broad data set will allow us to deliver differentiated value to customers. And we are working to productize this differentiated value through recently announced capabilities such as our Bits AI assistant, AI generated synthetic tests, and AI-led error analysis and resolution. And we expect to deliver many more related innovation to customers over time.

Let’s move on to sales and marketing, where we continue to execute on both new logos and existing customers. So let’s discuss some of our wins. First, we signed a seven-figure land over five years with a leading provider of dental care. This company’s legacy monitoring just didn’t cut, and it contributed to delays with their migration to Azure. What concerned them was that, customers noticed poor application performance and were complaining publicly on social media. By adopting six Datadog products, they expect to find and fix the vast majority of incidents internally before their customers are affected. And in signing a five-year deal, this customer showed its confidence in Datadog as a long-term partner in their migration.

Next, we signed a seven-figure land with a South American FinTech company. By moving from basic, built-in cloud monitoring, legacy tooling, and open-source tools to Datadog, this customer expects to significantly reduce costs by spending less on tooling, reducing time to resolution, and giving time back to engineers to innovate on their own products.

Next, we signed an eight figure running all over three years with a major American chain of convenience stores. With this expansion, Datadog will bring all aspects of these customers’ tech systems into one platform, including their application, hybrid clouds, network, in-store IoT technology, point of sale systems, self-serve kiosks, fuel pumps, and corporate infrastructure. This will free up employee time to focus on customer service with expectations to save millions of dollars annually. This customer plans to use six Datadog’s products, replacing three commercial observability tools.

Next, we signed a seven-figure expansion with a major US federal agency. When we first started working with this customer a year ago, Datadog was approved for a limited subset of programs. But as we have demonstrated value and gained internal adoption, this customer is now deploying Datadog across the entire agency. They have adopted six Datadog products, and by doing so, consolidated out of seven tools.

Next, we found a seven-figure expansion with a Fortune 500 industrial company. Customer was concerned with out of control costs with its legacy log management products and was using a dozen of different tools. And when they began using Datadog, they noticed far fewer support tickets submitted to their reliability team. By growing usage with Datadog and expanding to seven products, this customer expects to deliver better service while saving time and reducing costs.

And last, we signed a seven figure expansion with a software business that is part of a tech hyperscaler. This long-time customer has used Datadog for infrastructure metrics and will now expand to adopt seven Datadog products. Datadog will be replacing its commercial APM tool, which wasn’t well adopted by its engineers and led to inefficient troubleshooting, outages, and revenue impact. Our support of OpenTelemetry in particular was key to their decision to expand with Datadog as it makes it possible for APM tracing to be democratized and used across their entire DevOps team. And that’s it for this quarter’s highlight. I’d like to thank our go to market teams for their strong execution in Q3.

Before I turn it over to David for a financial review, let me reiterate our longer term outlook. As we have said throughout this period of cloud optimization and macro uncertainty, our long-term plans have remained unchanged. We continue to believe digital transformation and cloud migration are long-term secular growth drivers of our business and critical motions for every company to deliver value and competitive advantage. So we continue to invest aggressively to broaden our platform and we aim — sorry, and we aim to be our customers mission critical partners as we move to cloud and to modern DevSecOps.

With that, I will turn it over to our CFO, David.

David Obstler

Thanks, Olivier. Q3 revenue was $548 million, up 25% year-over-year and up 7% quarter-over-quarter. To dive into some of the drivers of this Q3 performance, first regarding usage growth. We saw an improvement in usage growth in Q3 versus Q2. The Q3 usage growth was more similar to Q1 and relatively steady throughout the quarter. We had a very healthy start to Q4 in October. While it is too early in the quarter to know for sure what will happen in the next couple of months, the trends we see in early Q4 are stronger than they’ve been for the past year.

Regarding usage growth by customer size, we continue to see larger spending customer growth at a slower rate than smaller spending customers, but usage growth improved for all customer sizes in Q3 relative to Q2. And as Olivier discussed, we believe there are signs that the optimization activity we’ve been seeing is moderating. Last quarter, we discussed the cohort of customers who started optimizing about a year ago. This cohorts usage has been stable — was stable throughout Q3.

As we look at our overall customer activity, we continue to see customers optimizing, but with less impact than we experienced in Q2, contributing to our usage growth with existing customers improving in Q3 relative to Q2. While we expect cost management to continue, we believe we are seeing moderation that is still present, but is less intense and less widespread than we experienced in recent quarters. Geographically, we experienced similar sequential revenue growth in North America and in our international markets.

And finally, as regard to retention metrics, our trailing 12 month net revenue retention was in line with our expectations and came in slightly below 120% in Q3. Our trailing 12-month gross revenue retention continues to be stable in the mid to high 90s, a sign of the mission critical nature of our platform for our customers.

Moving on to our financial results. Billings were $607 million up 30% year-over-year. Billings duration increased slightly year-over-year. Remaining Performance Obligations, or RPO, was $1.45 billion, up 54% year-over-year. Current RPO growth was about 30% year-over-year. Over the past couple of quarters, we have seen an increasing preference from our customers to sign multi-year deals, and our weighted average booking duration was up sequentially and year-over-year. We see continued interest in multi-year duration deals in our pipeline as customers seek longer term strategic partnerships with us. We continue to believe that revenue is a better indicator of our business trends than billings and RPO, as those can fluctuate relative to revenues based on the timing of invoice and the duration of customer contracts.

Now let’s review some of the key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. Gross profit in the quarter was $451 million, representing a gross margin of 82.3%. This compares to a gross margin of 81.3% last quarter and 79.7% in the year ago quarter. As Olivier mentioned, we continue to experience efficiencies in cloud costs reflected in our cost of goods sold in the quarter, as our engineering teams pursue cost savings and efficiency projects.

Our Q3 OpEx grew 17% year-over-year, this is a decline from 26% year-over-year growth last quarter. We continued to execute on controlling costs given the uncertain environment. And Q3 operating income was $131 million for a 24% operating margin, up from 21% last quarter and above the 17% in the year-ago quarter. Our margins were higher than we expected in Q3 as our organic growth was higher than in Q2, while our internal optimization and cost management efforts were successful.

Turning to the balance sheet and cash flow statements, we ended the quarter with $2.3 billion in cash, cash equivalents, and marketable securities. And cash flow from operations was $153 million in the quarter. After taking into consideration capital expenditures and capitalized software, free cash flow was $138 million for a free cash flow margin of 25%.

And now for our outlook for the fourth quarter and for the full fiscal year 2023. A reminder, our guidance philosophy remains unchanged. We base our guidance on trends observed in recent months and apply conservativism on these growth trends. For the fourth quarter, we expect revenues to be in the range of $564 million to $568 million, which represents about 20% to 21% growth year-over-year. Non-GAAP operating income is expected to be in the range of $129 million to $133 million. And non-GAAP net income per share is expected to be $0.42 to $0.44 per share, based on approximately 355 million weighted average diluted shares outstanding. For fiscal year 2023, we expect revenues to be in the range of $2.103 billion to $2.107 billion, which represents 26% year-over-year growth. Non-GAAP operating income is expected to be in the range of $453 million to $457 million, and non-GAAP net income per share is expected to be in the range of $1.52 to $1.54 per share based on approximately 351 million weighted average diluted shares outstanding.

Some additional notes for our guidance. First, we expect net interest income and net interest and other income for fiscal 2023 to be approximately $95 million. We expect tax expense in the fiscal year to be $12 million to $14 million. And finally, we expect capital expenditures and capitalized software together to be in the 3% to 4% of revenue range in fiscal 2023. And now regarding 2024. It is too early for us to speak to 2024 revenue growth. We will digest the information we see over the next several months and give you our 2024 revenue guidance next quarter.

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

With that, we will open the call for questions. Operator, let’s begin the Q&A.

Question-and-Answer Session

Operator

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

Mark Murphy

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

Olivier Pomel

Yeah, so it’s a number of companies that — without naming anyone, so they tend to be model providers, but not just on the language side, like model providers on the language, image side, like there’s a number of different — or video side, there’s a number of different types of companies, even some good copilot type companies. These customers all had revenue one year ago, but they’ve been growing a little bit faster than the rest of the customer base recently.

The reason we should be [indiscernible] in this space is, today we see the usage growth related directly to AI coming mostly for these customers that provide models to others. Whereas we see broad usage of AI functionality across the customer base, but at low volumes. And it corresponds to the fact that for most customers or most enterprises really, they’re still in the early stages of developing and shipping AI applications. So for now, the usage is concentrated among the model providers.

Mark Murphy

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

Olivier Pomel

We’ve seen that for a while now that new customers were looking for more integrated platforms, more modern offerings, things that were more cloud-first. And that’s been one of the reasons of our success in the landing largely in brand new applications, brand new environments, brand new cloud initiatives, and then over time consolidating our customers away from whatever they were using in the legacy. We don’t think that it is going to change with the various acquisitions and tech privates that we’ve seen over the past quarter. So we think we’ll just see more of that over time.

One extra thing on your first question, one interesting tidbit if you — as I know many of you are trying to understand what the AI landscape is made of. Interestingly enough, when we look at our cohort of customers that are considered to be AI native and built largely on AI and [indiscernible] AI providers, they tend to be on different clouds. What we see is that, the majority of these companies actually have a lot of their usage on AWS. Today, the larger part of the usage, the larger of these customers are on Azure. So we see really several different adoption trends there that I think are interesting to the broader market.

Mark Murphy

Thank you for that insight, I appreciate it.

Operator

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

Sanjit Singh

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

Olivier Pomel

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

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

Sanjit Singh

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

Olivier Pomel

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

Sanjit Singh

Appreciate the thoughts, Olivier. Thank you.

Operator

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

Raimo Lenschow

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

Olivier Pomel

So we think the trends of vendor consolidation will continue. So basically customers are getting more sophisticated, more mature in their needs. They’re getting further into the cloud and they are, as part of that, they will want to act less as integrators and 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 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 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 a couple 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 the rate of adoption of new observability platforms, new products from us. We’ve done well, we scaled the new logo acquisition, we scaled the new product DASH, so that has been a constant throughout the optimization phase.

In terms of the users growth and customers scaling new workloads, I don’t think we’re back to the exuberant times of 2021, but maybe we’re reverting back to the mean of what was happening before that.

Raimo Lenschow

Okay, makes sense. And if I can squeeze one quick one in. 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 grows like maybe wasn’t quite where you wanted it to be. Just any comments there? I know you can’t guide.

David Obstler

Yeah, 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 it now, 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 long-term opportunities.

Raimo Lenschow

Okay. Perfect. Thank you.

David Obstler

Thanks.

Operator

Thank you. One moment for our next question. And our next question comes from Karl Keirstead of UBS.

Karl Keirstead

Thanks so much. Maybe David, I’ll direct this to you. I was intrigued by your comment that the fourth quarter or 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? Thanks so much.

David Obstler

I think it’s just essentially what we tried to do in the last couple quarters is to caution everybody that we still expect that there will be continued 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.

Olivier Pomel

Yes. And just to add color on that. So yes, we had the healthy start to Q4. We see trends that are not 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 is typically a drop of usage at the very end of the quarter with the holidays. And that drop in different years 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.

David Obstler

Let me just add because this question has been talked about. Like last quarter, we didn’t take the strength of October into account, we took the exact same guidance approach, which was to take the weighted average historical trends and discount, apply conservativism. So like last quarter, we had said that the first quarter looked a little more stable. We didn’t take that into consideration our guidance and we have stuck to the exact same guidance methodology which is to act with that conservatism.

Olivier Pomel

I want to think too, just to comment on the — because I know a lot of you are trying to understand how we fit with respect to the large cloud providers and what trends correspond to theirs. Remember that while our trends are similar in the long run, 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. We have a mix of cloud providers 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.

Karl Keirstead

Okay. Very helpful and congrats on the nice results.

Olivier Pomel

Thank you.

Operator

Thank you. One moment for our next question. And our next question comes from Matt Hedberg of RBC.

Matt Hedberg

Great. Thanks for taking my question, guys, and I’ll offer my congratulations as well. You know, Ollie, I wanted to double-click on some of the improved usage trends. You know, can you provide us with an overview on how some of your large, sort of strategic customers think about optimization as really part of an ongoing IT spending strategy, coupled with what’s driving some of this increased usage. 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 their view on the level of monitoring needed. I think they tried to save money wherever they could save it. By far the biggest area they can save in their cloud infrastructure is their cloud bill 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 savings to be had there, but these savings flow down to us. We charge commercial rate to the size of our customer infrastructure. They also try to save what they could in the observability specifically. And usually there’s always a bit of that you can cut. You can always sample certain things a bit more. You can retain your logs a bit less. You can remove some of the debug log, things like that can drive your costs up, but don’t necessarily generate a ton of value. And that’s a 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 negotiations and things like that where they try to understand what they’re going to need for the next two or three years.

The big difference over the past year has been that everybody’s 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 where they can reduce and then growing workloads and maybe creating a little bit more mess over time as well, and then optimizing again on the regular basis. Not everyone at the same time.

Matt Hedberg

Super. Thanks a lot guys. Great color, Ollie. Congrats again.

Operator

Thank you. One moment for our next question. And our next question comes from Fatima Boolani of Citi.

Fatima Boolani

Good morning. Thank you for taking my questions. One for Ollie and one for Dave, if I may. Olivier, the packaging and pricing motions that you discussed for the DevSecOps solutions that 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 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 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 expansion rates or net retention rates as you’re thinking about it in the guidance? Thank you.

Olivier Pomel

Yes, so on the ELA, so in general, look, we’re always very open to new approaches in packaging. We try to see how things are consumed from the customer side, what makes the most sense to them. Now, ELA and things like that are very difficult for — 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 fit all for them. We also, philosophically, we like to have, to get signal from what customers are willing or not willing to pay for, and that drives a lot of our product innovation. We get a lot of good news this way because customers want to buy products and they scale them a lot. We 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 think it should be doing things differently or think 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 validity and the security side and make it easier to bring security into the conversation for these customers. Again, so far we have some early evidence that it seems to resonate, but it’s way, way, way too early to call it. We need two, three quarters of that to understand the implications of the new packaging.

David Obstler

Yeah, 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 had said previously that in Q2 and Q3 of last year, we had lower than before but higher than that 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 that 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 conservativism. 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 the Q4 coming up than we had in the Q4 last year.

Fatima Boolani

Thank you. I appreciate the detail.

Operator

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

Brent Thill

Good morning. David, I was curious if you could focus on the enterprise traction and what you’re seeing, maybe for Olivier. And David, I guess on the customer ad, you’re 700, and that’s lower than your normal cruise altitude 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? Thanks.

Olivier Pomel

Yeah, as a reminder, we have a broad range of customers with a long tail. And similar to what we discussed last quarter, the gross number of ads, so the accumulation in the enterprise, it was quite strong. It was very similar to what we’ve experienced. And we have a very small pale that has a large attrition rate but 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, [NARR] (ph), and that was true when Olivier talked about the enterprise side of it, offset by this tail that has very little dollars associated with it.

Olivier Pomel

Yeah, and just to comment on that, remember the bottom half of our customer represent 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. Those customers, we’re getting a little bit less of those to start with. I think that’s part of the economic environment and the churn is a little bit higher than it used to be there too. So that’s why this number is a little 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. 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 call. We get really, really excited when we see very traditional enterprises moving to the cloud and adopting us and concentrating on us in a [indiscernible]. David is there — we can’t see it. In the room David is smiling because he’s excited when he sees the dental care companies, he’s excited when he sees 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.

Operator

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

Kash Rangan

Hello. Thank you very much. Good to see you. I’m sure that you’re all smiling at your results. Two things. One is, with respect to LLM monitoring, which was demoed at the DASH conference, which was, I thought, absolutely fascinating. I know you quantified, Ollie, at 2.5 percentage points of growth coming from generative AI workloads. How do we think about the revenue option for LLM monitoring at an early stage? I also have a second question, slightly more controversial. If we run into customers that think they’re spending their bills for Datadog or 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. Thank you so much and congrats.

Olivier Pomel

Yes, on the LLM Ops side, I think it’s too early to tell how much revenue opportunity there is in the tooling specific to LLM Ops. When you think of the whole spectrum of tools, the closer you get to the developer side, the harder it is to monetize, and the further you get towards operations and infrastructure, the easier it is to monetize. We can ship things that are very useful and very accretive to your platform because they get you a lot of user, a lot of attention, and a lot of stickiness that are harder to monetize. So we’ll see where on the spectrum that is. We know though is that the broader generative AI up and down the stack, you know, from the components themselves or 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 concentrated 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 gets competition? 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’s what drives 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 on magnitude less than what they spend for their cloud infrastructure. Maybe two orders of magnitude less than what they 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 save 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 how we hold ourselves to.

Operator

Thank you. One moment for our next question. And our next question comes from Alex Zukin of Wolfe Research.

Alex Zukin

Hey, guys. Thanks for taking the question, and 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. Is that something that we picked up as 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 stock rank is a priority for you guys? And then I’ve got a quick follow up.

Olivier Pomel

So I missed the domain you’re talking about.

David Obstler

Fed.

Olivier Pomel

Oh, Fed. So that’s definitely an area of investment for us. It’s a — look, we are happy with two things. Happy 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 [indiscernible] agencies and now getting to grow some of those world to world. But we’re only scratching the surface of what we can do inside. And there’s a lot more we need to do. Some of it on the certification side and the product side, and some of it on the go-to-market side and making sure we have all of the parts of the motion working. So 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.

Kash Rangan

And then maybe on the — back on the AI question. I guess maybe just drill a little bit deeper within those AI native companies, the criticality of their data guide uses? 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 as observability becomes even more important? And how should we think about the growth opportunities from those types of workloads in either 2024 or 2025?

Olivier Pomel

Yeah, so, in general, the more complexity there is, the more useful observability is, the more you shift value from writing code to actually understanding it and observing it. So to caricature, if you spend a whole year writing five lines of code that are really, really deep, you actually know those five lines really well. Maybe you don’t know the ability for it 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 various open source and AI, and you can just very quickly generate thousands of lines of code, ship them and start operating them, you actually have no idea how these work, what they do, and you’ll need a lot of tooling and observability to actually understand that and keep track on that and secure it and do everything you need to do with it all the time. So we think that overall, these 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. Looks like it’s going to be pretty transformative if you adjust from just internally how much of that technology we are adopting and how much of a productivity impact it seems to be having. So, again, today we’re only seeing a tiny, tiny bit of it, which is early adoption by mobile providers and a lot of companies that are trying to scale up and experiment and figure out how 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.

Kash Rangan

Okay. Thank you guys.

Operator

Thank you. One moment for our next question. And our next question comes from Jake Roberge of William Blair.

Jacob Roberge

Hey, thanks for taking the questions and I’ll echo my 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 your platform over time. When do you think that actually takes place in the broader customer base starts to impact that AI growth in more earnest?

Olivier Pomel

We don’t know. And I think it’s too early to tell. So for one part, there’s some uncertainty in terms of these customers having to figure out what it is they’re going to ship to their own customers. I think everybody is trying to learn that right now and experiment it. But the other part is also that right now the innovation is largely concentrated among the mobile providers. And so, it’s rational right now for most customers to rely on those instead of deploying their own infrastructure. Again, we think it’s likely going to change. We see a lot of demand and interest in other ways to host models and run models and custom models and things like that. But today that’s the other trends of the market today basically.

Jacob Roberge

Okay, helpful. And then just to follow up on the optimization front, it sounds like the early optimizers took about a year to complete those initiatives. But what type of timelines 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.

Olivier Pomel

Yeah, so we don’t really know for sure. That’s also why we’re careful not to go and enter this forever. I would say 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 optimizations tended to be cloud-native, so all in on the cloud, very heavy on IT spending in general, and substantially all of their IT being in the cloud. These tended to be also companies that were fairly 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’re mostly not in that situation. So we expect the behavior to be different.

Operator

Thank you. This concludes the question and answer session. I would now like to turn it back to CEO, Olivier Pomel for closing remarks.

Olivier Pomel

Thank you very much. I want to thank everyone for attending the call today. I also want to take a minute to thank our customers for their trust. And 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 Datadog’s 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.

Operator

This concludes today’s conference call. Thank you for participating and you may now disconnect.