Datadog Inc (NASDAQ: DDOG) Q3 2025 Earnings Call dated Nov. 06, 2025
Corporate Participants:
Yuka Broderick — Senior Vice President of Investment Relations.
Olivier Pomel — Co-Founder, CEO & Director
David Obstler — Chief Financial Officer
Analysts:
Kash Rangan — Analyst
Sanjit Singh — Analyst
Raimo Lenschow — Analyst
Mark Murphy — Analyst
Fatima Boolani — Analyst
Eric Health — Analyst
Gray Powell — Analyst
Koji Ikeda — Analyst
Ittai Kidron — Analyst
Andrew Sherman — Analyst
Aleksandr Zukin — Analyst
Ryan MacWilliams — Analyst
Michael Cikos — Analyst
Karl Keirstead — Analyst
Jacob Roberge — Analyst
Presentation:
operator
Good day. Thank you for standing by. Welcome to the third quarter 2025 Datadog earnings conference call. At this time all participants are in listen only mode. After the speaker’s presentation, there will be a question and answer session. To ask a question during this session you will need to press Star one one on your telephone. You’ll only hear an automated message advising your hand is raised to withdraw your question. Please press star 11 again. Please be advised that today’s conference will be recorded. I would like to hand the conference over to your first speaker today, Yuka Broderick, Senior Vice President of Investment Relations.
Please go ahead.
Yuka Broderick — Senior Vice President of Investment Relations.
Thank you. Marvin Good morning and thank you for joining US to review Datadog’s third quarter 2025 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 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 2025 and related notes and assumptions, our gross margins and operating margins, our product capabilities and our ability to capitalize on market opportunities. 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 10Q for the quarter ended June 30, 2025. Additional information will be made available in our upcoming Form 10Q for the fiscal quarter ended September 30, 2025 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 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.data.hq.com with that, I’d like to turn the call over to Olivier.
Olivier Pomel — Co-Founder, CEO & Director
Thanks Suka and thank all of you for joining us this morning to go through Our results for Q3. Let me begin with this quarter’s business drivers. We have seen broad based positive trends in the demand environment with an ongoing strength of cloud migration and digital transformation. Against this backdrop, we executed on a very strong Q3 both in New logo bookings and usage growth of existing customers. As a notable inflection we saw acceleration of year over year revenue growth across our non AI customers and the sequential usage growth for non AI existing customers was the highest we have seen going back to our cores.
This growth was broad based as our customers are adopting more products and getting more value from the datadog platform. We also experienced strong revenue growth for our AI native customers and a broadening contribution to growth among those customers there too, we saw an acceleration of growth in our AI cohort in Q3 when excluding our largest customer. Looking at new business, contributions from new customers increased in Q3 in both the amount of new customer bookings as well as the revenue contribution from new customers and as usual, churn has remained low with gross revenue retention stable in the mid to high 90s, highlighting the mission critical nature of our platform for our customers.
Regarding our Q3 financial performance and key metrics, revenue was $886 million, an increase of 28% year over year and above the high end of our guidance range. We ended Q3 with about 32,000 customers, up from about 29 and 200 a year ago. We also ended with about 4060 customers with an ARR of $100,000 or more, up from about 3490 a year ago. These customers generated about 89% of our ARR and we generated free cash flow of $214 million with a free cash flow margin of 24%. Turning to platform adoption, Our platform strategy continues to resonate in the market.
At the end of Q3, 84% of customers were using two or more products, up from 83% a year ago 54% of customers were using four or more products, up from 49% a year ago. 31% of our customers were using six or more products, up from 26% a year ago, and 16% of our customers were using eight or more products, up from 12% a year ago. Digital Experience is an example of an area with no platform where our rapid piece of innovation is turning into tangible value for our customers. Our Digital Experience products include rum or Reuser Monitoring to observe and improve application behavior in mobile web apps, Synthetics to simulate user flows and proactively detect user facing issues, and Flora analytics to help users connect application behavior to business impact.
Over the years, we built up product breadth and depth in this area and that is being recognized in the Marketplace. For the second year in a row, Datadog has been named a leader in the 2025 Gartner Magic Quadrant for Digital Experience monitoring. We are pleased that today these Digital Experience products together exceed $300 million in ARR and this includes in particular a very fast ramp for product analytics which has already seen adoption by more than 1,000 customers. We also want to call out our security suite of products where we are executing and accelerating growth Security ARR growth was in the mid-50s as a percentage year over year in Q3, up from the mid-40s we mentioned last quarter.
We’re starting to see success in including cloud SIEM in larger deals and we’ll get back to that in a bit in our customer examples. And we’re seeing positive trends beyond cloud siem, including fast uptake of code security and an increasing number of wins in cloud security. Overall, we saw year over year growth acceleration in each one of our security products. Moving on to R and D, we continue to deliver on what is a very ambitious AI roadmap. We are seeing high customer interest in our BITS AI agents, which we announced at our DASH User Conference in June.
We have now onboarded thousands of customers for preview access to the BITS AI SRE agent and as we prepare for general availability we are getting very enthusiastic feedback on the time and cost savings enabled by BITS AI. As one user recently told us, with BITS AI SRE being on call 247 for us, meantime, to resolution for our services has improved significantly. For most cases, the investigation is already taken care of well before our engineers sit down and open their laptops to assess the issue. And this is not an isolated comment. We see the potential here for agents to radically transform observability and operations in LLM observability.
We recently launched LLM Experiments and Playgrounds for General Availability, helping teams to rapidly iterate on LLM applications and AI agents. We also launched Custom LLM as a Judge Evaluations for General Availability, which lets customers write evaluation prompts to assess application quality and safety. As an illustration of growth and adoption in the past few months, the number of LLM spans customers are sending to Datadog has more than quadrupled and we are seeing a lot of interest in the Datadog MCP Server. Our MCP Server acts as a bridge between Datadog and AI agents such as Codex, Power, OpenAI, Cloud Code, Paranthropic, Cursor, GitHub, Copilot, Gurus by Block and many more.
Our previous customers are using real time production data context to drive troubleshooting, root cause analysis and automation in intelligence. One user told us the Datadog MCP server is a great tool. It enables me to get the last five errors of my app and follow the spans and traces all the way to the root cause. I’ve never been more hooked on datadogs, so we see MCP adoption as a great way to cement datadog even further into our customers workflows. Finally, we continue to see rising customer interest for next gen AI observability with over 5000 customers sending us AI data to one or more of our AI integrations.
On the topic of integrations, we are very proud to now support over 1000 integrations which we believe is unparalleled in our space. By using our integrations, customers collect otherwise disparate data sources across datadog products for deeper analysis. We can see from our customers usage that this is a critical part of the DataDog platform. Over 32,000 customers use more than 50 integrations on average, while customers spending over $1 million annually with us use more than 150. And most importantly, as tech stacks evolve, we continue to update and expand our integrations so our customers can use datadog to deploy new technologies with confidence.
Last but not least, I wanted to give a shout out to our AI research team for the amazing work they have published. Our Soto Open Weight Time Series forecasting model has been one of the top downloads on Hudging Face over the past few months and that is across all categories. It is very impactful as, among other things, the high quality of this work allows us to attract world class AI researchers and engineers. Now let’s move on to sales and marketing. We had a number of great new logo wins in customer expansion this quarter, so I’ll go through a few of them.
First we landed a seven figure annualized deal with a leading European telco, our largest ever land deal in Europe. This company’s previous setup was expensive, inefficient and wasn’t scaling to meet their needs. By using Datadog, they expect to save over $1 million annually on tool costs alone, along with millions of dollars more in reduced operation costs, lower engineering time and avoidance of revenue loss. They will adopt 11 Datadog products to start and we consolidate more than 10 commercial and open source tools. Next we landed a seven figure annualized deal with a leading financial risk and analytics company.
The company’s fragmented tooling has led to major incidents that sometimes took multiple days and hundreds of engineers to resolve. They plan to start with 11 Datadog products including Encore, Cloudsim and Bitsai, and will replace 14 commercial open source and hyperscaler observability tools. Next we landed a seven figure annualized deal with a Fortune 500 technology hardware company. This is an exciting win for new Sorry, this is an exciting win for new go to Market motions targeting the largest and most sophisticated companies in the world. Datadog has been chosen as their Strategic Observability partner and we are displacing commercial tools across observability, Cloud team and incident response.
This customer is starting with 14 Datadog products. Next we signed a seven figure annualized expansion with a Fortune 500 financial services company. This customer had pockets of siloed teams and data including one business unit which manually hosted and maintained 93 separate instances of open source tooling. With this expansion this company will adopt 15 Datadog products including all three pillars in all of their business units. They will also replace their SIEM solution with datadog Cloud SIEM in a seven figure land deal for Cloud theme and by bringing all their telemetry data into the Datadog platform, they expect better insights for their adoption of BITS AI SRE agent today with NV2R security.
Next we signed a seven figure analyze expansion with a Fortun 500 heavy equipment company. With this expansion this customer will replace its open source log solution with Teladoc log management and Flex logs. They plan to adopt LLM Observability and their IT team is using cloud cost management to improve cost visibility and governance. Next we will come back a leading vertical SaaS company with a seven figure analyze deal. By returning to Datadog, this customer benefits from more alignment with OpenTelemetry and will implement the incident and reliability processes that they were unable to execute on previously. Next we signed a seven figure annualized expansion with a major American carmaker.
This customer is adopting Datadog products faster than previously expected and this agreement supports their higher usage. With this expansion they will adopt Datadog’s incident management and on call solutions company wide for a total of 5,000 users who support operational continuity across the business. Finally, we signed a nine figure annualized expansion with a leading AI company. This company has been a long time Datadog customer and has expanded their usage over multiple products, securing better economics for a higher commitment with an early renewal. Speaking of AI customers, we continue to help AI native customers big and small to grow and scale their businesses and we continue to see this group broaden in number and size with more than 500 AI native companies in this group, about 100 of which are spending more than $100,000 annually with Datadog and more than 15 who are spending more than $1 million annually with us.
While we know there’s a lot of attention on this cohort, we primarily see it as an indication of what’s to come as companies of every size and Every single industry incorporate AI into their cloud applications. And that’s it for another very strong quarter from our go to market teams who are now very hard at work as we have a really exciting pipeline for Q4. Before I turn it over to David for a financial review, I want to say a few words on our longer term outlook. There’s no change to our overall view that digital transformation and cloud migration are long term secular growth drivers of our business.
Meanwhile, we are advancing rapidly in AI where we are incredibly excited about our opportunities. We’re building a comprehensive set of AI observability products to help our customers tackle the higher complexity that comes with the technologies. And we’re building AI into Datadog and I spoke earlier about the excitement our customers have forbids AI agents. The market opportunity in cloud and AI is expected to grow rapidly into the trillions of dollars and companies of every size and industry are looking to adopt AI to deliver value to their customers and drive positive business outcomes. So we are moving fast to help our customers develop, deploy and grow into the cloud and into the AI world.
With that I will turn it over to our CFO David.
David Obstler — Chief Financial Officer
Thanks Olivier. To start, our Q3 revenue was $886 million, up 28% year over year and up 7% quarter over quarter. To dive into some of the drivers of our Q3 revenue growth. First, overall we saw sequential usage growth from existing customers in Q3 that was higher than our expectations and the strongest in 12 quarters. In our non AI native customer base we saw year over year growth acceleration broadly across our business including in new logos and existing customers, both enterprise and SMB. With customers across our spending bands big and small and customers in a wide variety of industries.
Next, we saw strong and accelerating contribution from new customers. New Logo annualized bookings more than doubled year over year and set a new record driven by an increase in average New Logo land size, particularly in enterprise. We believe we are starting to see the benefits of our growth of sales capacity and we are seeing new logos ramping faster, contributing more to revenue growth. The portion of our year over year revenue growth that related to new customers was about 25% in Q3, up from 20% in Q2. Next, our AI native customers continue to exhibit rapid growth while more customers in this group are growing to be sizable customers.
As Olivier discussed, we extended the contract of our largest AI native customer. In addition, we now have more larger AI customers, including 15 of them spending $1 million or more annually with Datadog and about 100 spending more than $100,000 annually. Year over year revenue growth from our AI native customers excluding the largest customer again accelerated in Q3. In Q3 this group represented 12% of our revenue up from 11% last quarter and about 6% in the year ago quarter. I will note that over time we think this metric will become less relevant. As AI usage in production broadens beyond this group of customers, our year over year revenue growth also accelerated amongst our non AI native customers.
In Q3 our revenue growth excluding the AI native customer group was 20% year over year accelerating from 18% year over year in Q2. And we have seen this trend of accelerating growth continue in October. Regarding retention Metrics, our trailing twelve month net revenue retention percentage was 120% similar to last quarter and our trailing twelve month gross revenue retention percentage remained in the mid to high 90s. And now moving on to our financial results, our billings were $893 million up 30% year over year. Our remaining performance obligations are RPO was $2.79 billion up 53% year over year and current RPO growth was in the low 50s percentage year over year.
Our strong bookings contributed to this acceleration of rpo. We continue to believe that revenue is a better indication of our trends in our business than billings in rpo. And now let’s review some of the key income statement results. Unless otherwise otherwise noted, all metrics are non gaap. We have provided a reconciliation of GAAP to non GAAP financials in our earnings release. First, gross profit in the quarter was $719 million and our gross margin was 81.2%. This compares to a gross margin of 80.9% last quarter and 81.1% in the year ago quarter. As previously mentioned, we continue to see the impact of our engineers cost saving efforts in Q3 as they deliver on our cloud efficiency project.
Our Q3 OpEx grew 32%. Excuse me, year over year down from 36% last quarter. We continue to grow our investments to pursue our long term growth opportunities and this OPEX growth is an indication of our execution on our hiring plan. Q3 operating income was $207 million for a 23% operating margin compared to 20% last quarter and 25% in the year ago quarter. And now turning to our balance sheet and cash flow statements, we ended the quarter with $4.1 billion in cash, cash equivalents and marketable securities and cash flow from operations was $251 billion in the quarter.
After taking into consideration capital expenditures in capitalized software, free cash flow was $214 million for a free cash flow margin of 24%. And now for our outlook for the fourth quarter and the fiscal year 2025. First, our guidance philosophy overall remains unchanged. As a reminder, we base our guidance on trends observed in recent months and imply conservatism on these growth trends. So for the fourth quarter, we expect revenue to be in the range of 912 to $916 million, which represents a 24% year over year growth. Non GAAP operating income is expected to be in the range of 216 to $220 million, which implies an operating margin of 24%.
Non GAAP net income per share is expected to be in the range of 54 to $0.56 per share, based on approximately 367 million weighted average diluted shares outstanding. And for the full year fiscal year 2025, we expect revenues to be in the range of 3.386 to $3.390 billion, which represents 26% year over year growth. Non GAAP operating income is expected to be in the range of 754 to $758 million, which implies an operating margin of 22%. And non GAAP net income per share is expected to be in the range of $2 to $2.02 per share, based on 364 million weighted average diluted shares.
And finally, some additional notes on our guidance. We expect net interest and other income for the fiscal year 2025 to be approximately $170 million. We continue to expect cash taxes in 2025 to be about 10 to 20 million dollars, and we continue to apply a 21% non GAAP tax rate for 2025 and going forward. Finally, we expect capital expenditures and capitalized software together to be 4% of revenues in fiscal year 2025. To summarize, we are pleased with our execution in Q3. We are well positioned to help our existing and prospective customers with their cloud migration and digital transformation journeys, including their adoption of AI, and I want to thank datadogs worldwide for their efforts.
And with that, we’ll open the call for questions. Operator, let’s begin the Q and A.
Questions and Answers:
operator
Thank you. At this time, we’ll conduct the question and answer session. As a reminder, to ask a question, you will need to press Star 11 on your telephone and wait for your name to be announced. To withdraw your question, please press star 11 again. Please stand by while we compile the Q and A roster. And our first question comes from the line of Kash Rayan of Goldman Sachs. Your line is now open.
Kash Rangan
Hi. Thank you very much, Appreciate it. Congratulations on the spectacular results and the showing of sequential improvement across the board. Olivia, had a question for you. We’ve talked about GPU monetization versus CPU monetization. So how closer are we to the point where you can confidently expand and get your share of the customer wallet when it comes to whether it’s training, workload, inferencing workload on the GPU clusters which are becoming more prevalent and increasingly larger part of the compute build out in the future? That’s it for me. Thank you so much.
Olivier Pomel
Yeah, so we have products that are getting into the market now for GPU monitoring, but these don’t generate any significant revenue yet. So all the revenues we share, like the acceleration, etc. That’s not related to us capitalizing more on GPUs. That’s a future opportunity.
operator
Thank you. One moment for our next question. Our next question comes from the line of Sanjit Singh of Morgan Stanley. The line is not open.
Sanjit Singh
Yeah, thank you for taking the questions. And congrats on the acceleration in growth this quarter. Olivier, I wanted to talk about some of those enterprise trends you’re seeing in sort of your non AI cohort. What do you sort of put the improved performance and growth this quarter on? You mentioned that the sales productivity or the benefit from some of the sales investments is starting to come online. Is there sort of an uplift in sort of the cloud migration trends? Are you starting to see enterprise build more AI applications? I just love to get your perspective on the underlying trends in the enterprise and the mid market business.
Olivier Pomel
Yeah, I said there’s three parts to it. One part is the demand environment is positive in general. I don’t know that we see massive acceleration of cloud migration, but at least the environment is not pushing the other way. We know which happens from time to time. But that’s point number one. Point number two is we’ve been growing sales capacity quite a bit and we’ve created new go to market motions, you know, to grow up to the kind of customers we were not getting before. We’ve done quite a bit of investment over the past couple of years and we see that starting to pay off.
As I said. Also we feel good about Q4 in terms of pipeline on the sales side. So it’s too early to tell yet. We still have to close the deal, but we feel good about the scaling of our go to market. And point number three is we have a number of products that we’ve been developing over the years, some of them early, some of them a little bit further along that are really clicking. We see we have a lot of success with getting larger prices to adopt Flex Logs, for example. We have a lot of success.
Some of new products such as product analytics that we mentioned on the call, we’re seeing some large lens deals. So all of that is contributing to the picture you’re seeing today.
Sanjit Singh
And just as a follow up on the AI observability opportunity, when you look at some of the independent software vendors that are releasing agentic solutions, agentic portfolios, a number of them are including observability as part of their value proposition. Is there any work you think Datadog has to do to infiltrate that market or make sure that customers look to Datadog as that agentic monitoring capability as some of these independent software vendors try to bundle in observability into their solutions? I’d love to hear your perspective on that.
Olivier Pomel
Yeah, I mean there’s absolutely no doubt to us that the customers will need more unified platform for observability for this. There’s two parts to that. One is historically every single piece of software we integrate with, whether that’s SaaS or things that customers run themselves, also has its own management console and observability console. But you’re not going to log into 17 or indicator customers. We mentioned they use 60 integrations for the smaller customers, 150 integrations for the larger ones. It’s not practical to actually go and manage that separately. So we think all of that belongs in a central place and that’s the historical trend we’ve seen.
We also think that you can’t separate the AI parts from the non AI parts of the business. So you know, you’re not going to look at your agent separately that you do at your web hosting and your database and your, you know, everything else you have in your stack. So all of that in the end will be attached to observability.
Sanjit Singh
Very clear. Thank you very much.
operator
Thank you. One moment for our next question. Our next question comes from Raimo Lenschow of Barclays. Your line is now open.
Raimo Lenschow
Perfect. Congrats for me as well. It sounded like an amazing quarter and nice to see it coming together on the AI side. And I don’t want to talk about the big customer, but more the. The other ones. Like 15 customers over 1 million, that’s like a big number. And 100 over 100,000. How do I have to think about the nature of those? Is this kind of. Are those kind of, especially the bigger ones, those kind of model builders. But then even 15 is a big number and over 100. Sounds like this whole new application world that we’ve all been kind of waiting for starting to come together.
Is that kind of what’s going on there? Because it does sound quite exciting and much more broader than we thought. Thank you.
Olivier Pomel
It’s actually fairly broad, you know, so there is model vendors, there’s models, you know, models that can be the LLMs, models that can be, you know, video, it can be sound generation, can be all of the various parts of the stack you see as independent companies. It can be quite a few companies that do that work on the coding side, you know, so coding assistance and vibe coders and everything in that range. Some of these are very new companies, some of these are not very new companies. Some of these started five, seven, eight years ago.
And we’re sort of not necessarily AI native from day one, but very quickly would give them the growth they see today with the people to AI. So we see a bit of that. We have companies that are other parts of the stack in AI on the say the certified, the other components of the infrastructure, and we have other companies that are purely applications built with AI. So we have a bit of everything in there. Like it’s actually fairly representative of the space.
Raimo Lenschow
Okay, perfect. That’s exciting. Thank you.
operator
Thank you. One moment for our next question. Our next question comes from the line of Mark Murphy of J.P. morgan. Your line is now open.
Mark Murphy
Thank you so much. You had mentioned the expansion of the contract with your largest AI native customer. And I believe you said better economics for a higher commitment. Can you speak to that? Because I would assume a higher commitment would carry a volume based discount. I’m just trying to understand if for some reason, if that was not the case here, what did you mean by better economics and then have a quick follow up?
Olivier Pomel
Yeah, yeah, I mean, look, this is without getting to the detail of any specific customer that this is. The motion is always the same, like you know, customers grow, they commit to more, they get, they get better prices. So you see again, talking about customers in general, you see growth of usage, drops in revenue as customers renew and get higher comment and a better price and then usually growth after that for those customers. You know, that’s the motion that we’ve had with about 30,000 customers so far.
Mark Murphy
Okay. So the better economics part of it is where it’s going to be netting out like 12 months down the road. Is that what you mean?
Olivier Pomel
Well, the bigger economics means, you know, you commit tomorrow, you get a better price. You know, and as we remember we have a Usage model. So we charge people every month on what they use at the price, at the price we agreed. So if you get better economics and your usage is somewhat similar month to month from month to next compared to per less. But the overall backdrop of our business is increased consumption.
Mark Murphy
Okay, and then as a quick follow up, Olivier, the acceleration that you saw in security growth is pretty noticeable too. We recall, I think about six months ago you had ramped up and engaged a lot more with channel partners, which is a key ingredient to grow in a security business. Is it a function of that or is there a mindset change happening out there where customers want observability to be the central point of collection so that all the security teams and the ops teams are working with the same set of metrics and logs and traces?
Olivier Pomel
Look, I think it’s a number of things definitely we’ve been investing in the channel and that’s certainly helpful to the security business as a whole. The big wins we mentioned on security that we mentioned a couple of wins in Cloud C. These tend to be more related to product maturity, the strength of our underlying platform, especially when it comes to technology like flex logs for example, and the fact also that we’ve been learning how to properly go to market for security. And I think we see things clicking in a way that is exciting.
Raimo Lenschow
Thank you.
operator
Thank you. One moment for our next question. Our next question comes to the line of Fatima Boolani Airline is now open.
Fatima Boolani
Good morning, thank you for taking my questions. Ali, I’ll start with you and have a follow up for Dave on the on call product. Ali, how do agentic advancements in general detract or enhance the value proposition here? And I’m very simplistically thinking about the core nature and value proposition of the on call product. Intelligently routing requests for remediation. Right. So how do you just broader advancements in AI help beef up and or detract your ability to monetize this product? And then just a follow up for David, please.
Olivier Pomel
Well, I mean look, if you zoom out, we entered the field with Onco because we wanted to own the end to end incident resolution. So we wanted, before that we were detecting the incidents and setting the alerts and then we were pretty much where the resolution happened. After that, you know, customers were spending their time in DAT op to diagnose and understand what was going on. So we wanted to own the full cycle and we thought that with AI in particular, we’d have the ability to do things if we own the whole cycle that we couldn’t do otherwise.
So what you see right now is, I mean, this resonance with customers, they adopting the product. We’ve mentioned some exciting customers with one with 5,000 seats for encore, which is very exciting. But in the future there’s many more things we can do and working on for that product. If we both detect incident and notify, we can do some subtle things such as even predicting the incident and notifying early or rerouting early or telling people before the incident actually takes place how they can potentially fix it. So these are all things we’re working on. I mean look, if you look at the various product announcements we’ve made, whether that’s BITSAI SRE or the time series forecasting model we’ve released, when you assemble all that, you get to a very, very interesting picture of what we can do in the future.
So we’re excited by that. Our customers are excited about the vision there too. And that’s why these products are successful.
Fatima Boolani
Appreciate that. David, on net retention rates, why aren’t we necessarily seeing more upward pressure on the metric? Just given the strength of expansionary bookings that you alluded to in the quarter from the install base and I mean I suspect it’s because it’s a trailing twelve month metric, but any directional color, you can just share on that and any high level commentary on some of the non AI native net retention rate trend behavior. Thank you.
David Obstler
Yeah, you’ve nailed it. It’s a trailing 12 months. It’s, you know, a number that’s rounded. It has the dynamic that you might expect in that the growth of the non AI natives has been, as we mentioned, a combination of landing and expanding at higher rates than we’ve seen in recent quarters. So you know, if that continues as you go into a trailing twelve month metric, you see a directional movement.
Fatima Boolani
Thank you.
operator
Thank you. One moment for next question. Our next question comes from the line of Eric Health of KeyBank. Your line is now open.
Eric Health
Hey, great. Thanks for taking the question, Ollie. David, Bits AI seemed like a really exciting thing out of dash and I know it’s still in preview but you mentioned there’s a lot of interest there. So I’m just curious how you think about the agentic opportunity with bits AI and how meaningful this can be for 2026 as a differentiator versus competition and, and also as a revenue contributor. Thanks.
Olivier Pomel
Yeah, so I mean look, it’s super exciting. The feedback’s very good on it. I mean we’ve been collecting all the. So I read one code, you know, we have dozens that look just like that that was sent to us by customers. And so that’s very, very exciting. We also started having some customers buy and come to it just to show value and to make sure we’re onto the right product mix. And so we feel good that this is something that is high quality and we can monetize. In terms of the impact for next year on the packaging side, I’m not completely sure yet whether the biggest impact will be seen from what we charge for BITS AI itself or for the rest of the platform that gets benefits from the differentiation of BITS AI.
I think that’s more of a broader question of packaging and monetization of AI. And remember that we have a product that is usage based, so anything that drives usage up and adoption from customers is good for us and is very, very monetizable. But what we can tell is this is differentiating, this is good. It works significantly better than anything else we’ve seen or heard of in the market. And we’re doubling down on it. We have many, many teams now working on deepening BCISRES to making sure it goes further into the resolution, doesn’t just point to the issue, but fixes the code, all these kind of things, working hard on that.
We’re also working on breadth, you know, making sure that we train it on many more types of data, many types of sources, sometimes even systems that are observed, systems that are not Datadog, so we can cut across to other systems our customers are using. So we’re very, very aggressively developing bcisi. It’s resonating very well in the market.
operator
Thank you. One moment for next question. Our next question comes from Lynne of Gray Powell of btig. Your line is now open.
Gray Powell
Oh, great. Thanks for taking the question and congratulations on the, on the great results. So maybe just like taking a step back, if we go back to the beginning of the year, DataDog was expecting 19% revenue growth. It looks like you’re tracking something over 26% growth now. And that’s just the high end of your guidance. So I guess my question is, what surprised you the most this year? And then just how do you feel about the sustainability of those drivers as you look forward?
Olivier Pomel
I mean, look the. So first I apologize for over delivering on the results. We might do it again, but we’ll see. I think the biggest surprise for us has been that so AI in general has, or AI adoption has grown faster than we thought it would at the beginning of the year. So we’ve seen that across our AI cohort. We’ve seen also that we got some of our new products and the changes we are making on the go to market side to click perhaps earlier than we would have thought otherwise. So all in all we saw the leading part of the business with AI grow faster.
Not the lagging, but the slower growing, more traditional part of the business also accelerate and that gives us where we are today.
David Obstler
And I’d add we have a good demand environment and we’ve been investing whether it be in the products that Ali’s been talking about or in the sales capacity. We made clear that we were in investment mode and we’re seeing those investments pay off.
Gray Powell
All right, that’s helpful. Thank you.
operator
Thank you for Next question. Our next question comes from the line of Koji Ikeda of Bank of America securities. Your line is now open. Yeah.
Koji Ikeda
Hey guys, thanks so much for taking the question. Just one for me here. I wanted to ask a question on the inflection and the non AI native growth and how to think about the areas of strength in this cohort. Is it coming from your largest enterprises? Is it coming from a certain type of customer? Is there a common theme in the workloads that you’re seeing or the products that are being added on that is driving that strength or is it just really just broad based? What I’m trying to get at here is I’m really trying to understand more the durability of this growth and collection.
Thank you.
Olivier Pomel
So it is broad based and I think again speaks to a couple of things. It speaks to the fact that in general the demand environment is good though I would say there’s been a very, very high growth of hyperscaler revenue over the past or an acceleration for the hyperscalers in general. A lot of that is GPU related. But the growth we’re seeing here and the acceleration we’re seeing here is largely not GPU related, a little bit of it, but not a ton of it. So that’s not exactly what you’ve seen with some of the other vendors there.
One reason this is broad based is these are the same products we sell to all customers and this is largely the same go to market organization that we have a few segments but and we’ve been doing well executing there. I think we’ve invested quite a bit in product and we will keep doing it and we see the results of that.
David Obstler
Yeah, I’ll add that it’s across the customer base enterprise SMB. And when we look at it, it’s not just an AI SMB. If you remove those AI comp, you still see a strengthening SMB demand cycle going on. And unlike in previous periods, it also is across spending ranges. We’re not seeing larger spenders or smaller spenders. We’re just seeing a broad trend of improved demand across the spending trends.
Olivier Pomel
Remember that for us, SMB is any company of less than 1,000 employees. It includes a lot of very legitimate and growing businesses. It’s not.
Koji Ikeda
Thank you,
Ittai Kidron
thank you. One moment for our next question. Our next question comes from line of Ittai Kidron of Oppenheimer and company. Your line is now open.
Ittai Kidron
Thanks and congrats guys. Really great numbers. Ollie, in your answer to one of the questions and kind of going into the drivers behind the upside, you talked about sales capacity increase. You did talk a bunch about sales efficiency. Is there a way you can give us some color on where do you stand on percent of salespeople that are hitting quota? Where does that ratio stand relative to historical patterns for you guys? And as you approach 26 year old, do you anticipate any material changes in the comp structure? Just given the breadth of product and their list of opportunities, how do you get people focused?
Olivier Pomel
Yeah, so we feel good about the sales productivity in general. And the rule generally is you grow by scaling capacity and maintaining productivity. It’s hard to drive both up at the same time. And remember, if you want to grow to 10x, you can do that by scaling it. You can’t really do it by improving productivity. So you have to scale. And we’ve been doing that and we’ve been successful at it so far in terms of the compliance. Look, we keep changing the way we compensate and the way we manage the salesforce in general to make sure we have the right focus.
One of the gifts of a business model like ours is that we have a very heavy land and expand model and so we get a lot of growth from leading customers. The challenge in create, on the other hand is how do we get to focus the sales force on the newer customers, the smaller ones and the new ones? Because it is more work to get an extra dollar for a smaller customer or for a new one than it is on an existing one that they already have Scale. And so a lot of the tweaks we met through our plans relate to that.
Who do we grow, who do we make sure we direct our attention and we reward people for what is going to generate the most long term growth for us. And we’ve made a number of changes. I won’t go through them, these are internal changes. But we have a number of changes this year. We see a number of them pay off. Another thing I mentioned on the call was we mentioned the wins for one of our new go to market motions and that’s specifically getting in place multi year plans to go after some larger customers that are tougher to land than what we’ve done in the past.
And you know, sometimes it takes more than a year to land certain types of customers. And the problem is if your comp plan only has a one year horizon, like it doesn’t give a great incentive for the sales force to go after those customers. And so we cordoned off a few of those companies who have special plans to go after that and we signed starting to see success with that too. This is just an example.
Ittai Kidron
Appreciate it.
operator
Thank you. One moment for next question. Our next question comes from the line of Andrew Sherman of TD Cowen. Lines now open.
Andrew Sherman
Oh great. Thank you and congrats. I know you have a team focused on the Fortune 500 where there’s still a lot of white space for you. Curious to hear how that team’s ramping to productivity. Does that help drive some of the strong new logo bookings and can this contribute even more next year? Thanks.
Olivier Pomel
Yeah, I mean look, the tip is not new, right? I mean we’ve been focusing on that for many years and we’re tracking well. One thing I was mentioning just before was one challenge even in the Fortune 500 is to make sure that we focus on landing new customers, you know, and make sure that there’s the right amount of sales attention and reward for lending a customer, even if it’s for a small amount. And I think we’ve done well. Again, we can comment on that again after the next quarter when we have a full year of our new clients that have been validated.
But so far we feel very good about it.
operator
Thank you. One moment for our next question. Our next question comes from the line of Alex Zulkin of Wolfe Research. Your line is now open.
Aleksandr Zukin
Yeah. Hey guys, thanks for taking my question and congrats on dropping some truly inspiring quotes in the script. Maybe Ali one for you and then I have a quick follow up for David. Just the duration of this acceleration of the non AI cohort. It seems like from all your forward looking metrics, whether it’s Billings, RPOs, CRPO, those were again really, really strong. How long do you think we should think about the duration of this trend, of this non AI acceleration?
Olivier Pomel
Well, you know, we’re a consumption business, so we the hardest thing to understand is what the future is going to look like for consumption. The way I would Say it is. We feel very good about it at the midterm long term now it ebbs and flows in a given month or quarter, that’s harder to tell. And again that’s what we’ve seen through the life of the company. So what we feel very confident about though is the motion in general for digital transformation and cloud migration is steady and sometimes it slows down a little bit, but it reaccelerates after that.
And we see that going on for a very long time.
Aleksandr Zukin
And then maybe David, for you, look, gross profit dollar acceleration while you’re seeing your largest customer kind of get better unit economics is also inspiring to see. How should we think about the progression of gross margins and gross profit dollar growth, particularly as you continue to also see the AI cohort acceleration?
David Obstler
Yeah, there’s a couple things I think we’ve mentioned that we’ve been focused and have focused over the many years on the efficiency of our cloud platform. We have significant engineering efforts around cost of sales and delivery of value and so we’ve been able to deliver on that. We also have a very broad customer base of distributed in terms of volumes. So as customers get larger and maybe get volume discounts, we have a number, you know, a lot of customers coming in at smaller so that balance there. And then in terms of. The sort. Of the future repeat what we’ve always said that we’ve been running the company with a gross margin plus or minus 80. You know, we’ve given that range and not changed it and we watch it and it gives us signals in terms of efficiency, how we’re operating. It gives us signals in pricing and things like that. And wouldn’t change the comments we made over the many years about looking at that and then developing operations and strategies around that.
Aleksandr Zukin
Perfect. Thank you guys.
operator
Thank you. One moment for next question. Our next question comes from the line of Ryan MacWilliams of Wells Fargo. Your line is now open.
Ryan MacWilliams
Hey, thanks for taking the question. Just one for me on the large AI contract expansion that you provided commentary on. Is there any way we can think about the contribution change from this customer over the next few quarters? Thanks.
David Obstler
No, I mean we don’t provide that kind of information on individual customers. We’re trying to give a picture of the overall business generally. I think as Ali mentioned, on our larger customers we have a motion of the expansion of volume and then we work on the term and the volume based pricing, but we don’t give guidance like that on individual customers.
Ryan MacWilliams
Fair enough.
operator
Thank you. One moment for our next question. Our next Question goes on. Light of Mike Cikos of Needham, your line is now open.
Michael Cikos
Great. Thanks for taking the questions guys. I just wanted to come back to it. Ali for the non AI native strength. I know we’ve kind of hit on this a number of times, whether it’s roadmap sales capacity execution, but, but kudos on the numbers here. I’m just trying to get a better sense of the why now? Is it just a composite of all those different pieces clicking together this quarter or is there anything more to unpack there? And then I have a follow up for David.
Olivier Pomel
Again, I don’t think there’s a lot more to unpack there and I know it’s boring in a way, but it’s also the way we’ve been growing for the, the past 15 years of the week. So that’s, I would call it the usual.
Michael Cikos
Awesome, awesome to hear. Okay. And then for the follow up to David. David, I don’t want to take anything away from the Q3 results you guys just posted and we obviously have the strong guide here for Q4, but I just can imagine myself a month from now starting to get inbounds from certain folks asking about the holiday season and the fact that we have holidays landing on weekdays in Q4 here. Can you just kind of discuss how you thought about constructing guidance for this Q4 year?
David Obstler
Yeah, we have years of experience of analyzing the day by day patterns in the holidays. We know that the holiday period ends up in the usage side because of vacation holidays and we incorporate that into to our guidance. We’re I think evolved a lot over the years and sort of days, adjusted types of days, et cetera. And so we would be incorporating that like we’ve incorporated in other years. If there are differences in this calendar period, we incorporate that. As always.
Michael Cikos
Very helpful. Thank you guys.
operator
Thank you. One moment for our next question. Our next question comes from the line of Karl Keirstead of ubs. Your line is now open.
Karl Keirstead
Okay, great. Thank you. I’ll ask one for David and one for Olivier. David, first of all, congratulations on the extension of the larger contract. I think everybody on the line is applauding that. I know you’re reticent to get into any details, but maybe I could try. Are you able to clarify whether that was a one year deal or multi year and then related to that, David, what is the contribution to CRPO from that deal which I presume landed in your CRPO number? If it is a one year deal, does the entirety of that contract contribute to the sequential CRPO performance in the quarter.
So that’s it for you, David and then Olivier, maybe I’ll just ask both at once. Some of the very large AI natives are beginning to diversify to utilizing Oracle’s OCI and Stargate. And I’m wondering what’s the opportunity for Datadog to essentially follow that behavior and begin scaling on Oracle Stargate or because a lot of what Oracle is doing with the AI natives is training clusters, perhaps that near term opportunity is more limited. Thank you both.
David Obstler
Yeah, on the first point I think we give a lot of examples and our motion which our customers would be following, including that one would be we fix out annual plus commits. We’re not commenting on individual contracts here, but it would follow a typical path to other types of, of contracts. So that’s what we would do.
Olivier Pomel
Yeah, and on oci, look, this is, we’ve built an OCI integration and we see more demand from customers on oci, you know, some of the things we see like the targets, et cetera, like these are extremely custom built out. Like, I don’t know, you know, they’re not necessarily exactly cloud because they’re custom built for specific customers. So the opportunity there is more remote today. But it’s, you know, again one company is that it’s a not fantastic opportunity to productize. But if, you know, 10, 15, 20, 50 companies start using that, then that really becomes a commercial opportunity.
And so we’re very much plugged into all of that and we go basically where our customers are.
David Obstler
I think you mentioned about the rpo. No, I think in this case we mentioned the current and the total is roughly the same and there wouldn’t be anything in that contract that would have been materially around those numbers. Those numbers I think we mentioned are produced from the bookings growth more generally and not from that particular contract.
Karl Keirstead
Okay, thank you.
operator
Thank you. One moment for our next question. Our next question comes from the line of Jake Roberge of William Blair. Your line is not open.
Jacob Roberge
Yeah, thanks for taking the question. Just on the recent go to market investments obviously seems like there’s been a lot of traction thus far with those. So I’m curious if there are any areas like security or the new logos or upmarket that you could look to lean even deeper into just, just given the growth that you’ve seen here.
Olivier Pomel
Yes, definitely. And that’s something we, we didn’t do this year that we were definitely going to do next year. You know, so there’s a, there’s a number of things where, you know, it’s, we’re in Q4, right. So we’re in the middle of planning for next year and you know, we basically will keep scaling what’s working, stop doing some of the things that you know are not conclusive and then try a few more things. That’s the way it works. Interestingly enough, building a go to market is not that different from building software. You experiment, you gather data, you see what’s working, what’s not working and you build the systems.
Jacob Roberge
That’S helpful. And then just on the new bits AI agents, can you just talk about the early feedback that you’ve gotten for those solutions and maybe how the engagement with those agents has compared to kind of the ramp of security flex logs. I know obviously much earlier days, but just how it compared when those were still largely in the preview phase.
Olivier Pomel
I mean look, the bit CISR agent is it really has a woo factor for customers. So what works really well is and we’ve seen that number of times like we set it up for them, it’s running on their alert and they go through an outage and they still go through the motion. So they still go, they still set up a bridge and they have 20 people and they spend two hours and in the end they have an idea of what went wrong and then they go to that organ, they see, oh well, there’s an investigation that had run and three minutes into the outage it got the same conclusion that we got two hours later with 20 people on the call and that completely eye opening for customers when they see that.
And we have. So that’s why we get many quotes about it. So now, you know, there’s more we need to do there. Like you know, customers say oh this is great now can you make this fix for me? Can you do this? Can you do that? Can you support an other system that right now you can’t actually set it up for? So we have a very, very full roadmap of things we need to do and we’re doubling down on it. We also shipped, I mean this one is in preview but we shipped a security agent that looks at vulnerabilities and looks at security signals and those three apps that basically look at trying to investigate what might be denying or what might be a real issue.
We also are getting very, very positive feedback for that. And in fact that’s what helped us win some large land deals for cloud SIEM products. You know, because the combination of the SIEM that runs extremely efficiently on top of observability data that runs very efficiently on top of flex log. But also saves an immense amount of time by getting 90% of the issues out of the way with automated investigations. That’s extremely attractive to customers. All right. And I think with that we’re going to close the call. So before we go, I just want to give one quick shout out to the team because I know as I said earlier, we have quite a lot going on in Q4, whether it’s on the planning side, the product building side or on the sales side where I said we have a really, really exciting pipeline and so we have a lot to do.
I want to thank the team for the hardware there. I also am looking forward to meeting a lot of our existing and new customers at AWS Re Invent in a few weeks and I’ll see you all there. Thank you all.
operator
Thank you for your participation in today’s conference. This does conclude the program. You may now disconnect