Q3 2025 Datadog Inc Earnings Call
Speaker #2: Good day . Thank you for standing by . Welcome to the third quarter of 2025 . Datadog Earnings Conference Call . At this time , all participants are listen only mode .
Speaker #2: As it is figures , presentation . There will be a question and answer session . To ask a question during the session , you will need to press star one on your telephone .
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Speaker #2: Over to your first speaker today . Yuka Broderick Senior Vice President , Investor Relations . Please go ahead .
Speaker #3: Thank you . Marvin , good morning , and thank you for joining us to review Datadog's third quarter 2020 financial results , which we announced in our press release , issued this morning .
Speaker #3: Joining me on the call today are Olivier Pomel , Datadog 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 fiscal year 2025 , and related notes and assumptions are gross margins and operating margins are product capabilities , and our ability to capitalize on market opportunities .
Speaker #3: 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 .
Speaker #3: 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 .
Speaker #3: For 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 , 2025 .
Speaker #3: Additional information will be made available in our upcoming form 10-q for the fiscal quarter ended September 30th , 2025 and other filings with the SEC .
Speaker #3: This information is also available on the Investor Relations section of our website , along with the 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 .
Speaker #3: With that , I'd like to turn the call over to Olivier . Thank you .
Speaker #4: Catherine , 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 .
Speaker #4: 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 .
Speaker #4: As a notable inflection . We saw acceleration of year over year revenue growth across our known AI customers and the sequential usage growth for Non-ai existing customers was the highest we have seen going back 12 quarters .
Speaker #4: 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 .
Speaker #4: There , too , we saw an acceleration of growth in AI cohort in Q3 when excluding our largest customer . Looking at new business contribution from new customers increased in Q3 in both the amount of new customer bookings as well as the revenue contribution from new customers .
Speaker #4: And as usual , churn has remained low with gross revenue retention stable in the mid to high 90s . Highlighting the critical nature of our platform for our customers .
Speaker #4: 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 .
Speaker #4: 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 IRR of $100,000 or more , up from about 3490 a year ago .
Speaker #4: These customers generated about 89% of our IRR , and we generated free cash flow of $214 million with a free cash flow margin of 24% .
Speaker #4: Turning to plasma adoption , or 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 .
Speaker #4: 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 .
Speaker #4: And 16% of our customers were using more products , up from 12% a year ago . Digital experience is an example of an area with no platform , where our rapid pace of innovation is turning into tangible value for our customers .
Speaker #4: Our digital experience products include rum or reusable monitoring to observe and improve application behavior in mobile and web apps . Synthetics to simulate user flows and proactively detect user facing issues and product analytics to help users connect application behavior to business impact .
Speaker #4: Over the years , we've built out 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 .
Speaker #4: We are pleased that today , this digital experience products together exceed $300 million in IRR , and this includes in particular , a very fast ramp for product analytics , which has already seen adoption by more than 1000 customers .
Speaker #4: We also want to call out our security suite of products where we are executing and accelerating growth , security , IRR growth was in the mid 50s as a percentage year over year .
Speaker #4: In Q3 , up from the mid 40s . We mentioned last quarter . We're starting to see success in including cloud theme in larger deals , and we'll get back to that in a bit .
Speaker #4: In our customer examples , we're seeing positive trends beyond cloud theme , including fast uptake of code security and an increasing number of wins in cloud security .
Speaker #4: Overall , we saw year over year growth acceleration in each one of our security products . Moving on to R&D , we continue to deliver on what is a very ambitious AI roadmap .
Speaker #4: We are seeing high customer interest in our AI agents , which we announced at our user conference in June . We have now onboarded thousands of customers for preview access to the SRA agent , and as we prepare for general availability , we are getting very enthusiastic feedback on the time and cost savings enabled by AI .
Speaker #4: As one user recently told us . With AI being on call 24 over seven 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 .
Speaker #4: And this is not an isolated comment . We see the potential here for our agents to radically transform observability and operations in observability .
Speaker #4: We recently launched Lmx experiments and Playgrounds for general availability , helping teams to rapidly iterate on applications and AI agents . We also launched custom Lmx as a judge .
Speaker #4: 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 LMS spans customers are sending to Datadog has more than quadrupled , and we are seeing a lot of interest in the Datadog Mcpp server or MCP server acts as a bridge between Datadog and agents such as Codex , OpenAI Cloud Code by anthropic cursor , GitHub , Copilot , Gurus by blog , and many more on preview .
Speaker #4: Customers are using real time production data to context to drive troubleshooting , root cause analysis , and automation in these agents with one user told us the Datadog, Inc. server is a great tool .
Speaker #4: It enables me to get the last five years of my app and follow the stars and traces all the way to the root cause .
Speaker #4: I have never been more hooked on Datadog . So we see MCP adoption as a great way to cement Datadog , even further into our customers workflows .
Speaker #4: 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 .
Speaker #4: On the topic of integrations , we are very proud to now support over 1000 integrations , which we believe is unparalleled in our space .
Speaker #4: By using our integrations , customer co-led otherwise disparate data sources across products for deeper analysis , we can see from our customers usage that this is a critical part of the Datadog platform .
Speaker #4: Over 32,000 customers use more than 50 integration , an average , while customers spending over $1 million annually with US use more than 150 .
Speaker #4: And most importantly , as tech stacks evolve , we'll continue to update and expand our integrations so our customers can use Datadog to deploy new technologies with confidence .
Speaker #4: Last but not least , I wanted to give a shout out to our AI research team for the amazing work they have published on open Time series forecasting , model has been one of the top downloads on Huggingface over the past few months , and that is across all categories .
Speaker #4: It is very impactful as a other things , the high quality of this work allows us to attract world class AI researchers and engineers .
Speaker #4: Now let's move on to sales and marketing . We had a number of great new logo wins in customer expansions this quarter , so I'll go through a few of them .
Speaker #4: 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 .
Speaker #4: By using Datadog , they expect to save over $1 million annually on tool costs alone , along with millions of dollars must more in reduced operational costs , lower engineering time and avoidance of revenue loss .
Speaker #4: They will adopt 11 Datadog products to start and will consolidate more than ten commercial and open source tools . Next , we landed a seven year annualized deal with a leading financial risk and analytics company .
Speaker #4: 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 products , including On-call Cloud Team and AI , and will replace 14 commercial , open source and Hyperscaler observability tools .
Speaker #4: Next , we landed a seven figure annualized deal with a fortune 500 technology hardware company . This is an exciting win for new .
Speaker #4: Sorry , this is an exciting win for a new go to market . Motions targeting the largest and most sophisticated companies in the world .
Speaker #4: Datadog has been chosen as their strategic observability partner , and we are displacing commercial tools across observability , cloud theme , and incident response .
Speaker #4: This customer is with 14 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 .
Speaker #4: 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 Theme 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 AI agent .
Speaker #4: Today , and security analysis . Next , we signed a seven figure annualized expansion with a fortune 500 heavy equipment company . This expansion , this customer will replace its open source log solution with Datadog Log Management and Flex logs .
Speaker #4: They plan to adopt availability , and their IT team is using cloud cost management to improve cost visibility and governance . Next , we will come back .
Speaker #4: A leading vertical SaaS company with a seven figure analyze deal by returning to Datadog , this customer benefits a more alignment with Opentelemetry and will implement the incident and reliability processes that they were unable to execute on previously .
Speaker #4: 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 supports their higher usage .
Speaker #4: With this expansion , they will adopt Datadog Incident Management and on call solution company wide for a total of 5000 users who support operational continuity across the business .
Speaker #4: 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 higher commitment .
Speaker #4: With an early renewal . Speaking of AI , customers , we continue to help customers big and small , to grow and scale their businesses , and we continue to see this group broaden in number and size .
Speaker #4: With more than 500 companies in this group . But 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 .
Speaker #4: 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 .
Speaker #4: 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 .
Speaker #4: Before I turn it over to David , for a financial review , I want to say a few words on our longer term outlook .
Speaker #4: There is 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 .
Speaker #4: 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 of customers have for AI agents .
Speaker #4: 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 .
Speaker #4: So we are moving fast to help our customers develop , deploy and grow into the cloud , into the AI world . With that , I will turn it over to our CFO , David .
Speaker #4: Thanks , Olivier , to .
Speaker #5: 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 .
Speaker #5: 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 .
Speaker #5: 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 .
Speaker #5: 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 .
Speaker #5: The portion of our year over year revenue growth that related to new customers was about 25% in Q3 , up from 20% in Q2 .
Speaker #5: Next , our AI native customers continue to exhibit rapid growth , while more customers in this group are growing to be sizable , customers .
Speaker #5: 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 year over year .
Speaker #5: 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 .
Speaker #5: 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 .
Speaker #5: 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 .
Speaker #5: And we have seen this trend of accelerating growth continue in October $100,000 annually . Regarding retention metrics , our trailing 12 month net revenue retention percentage was 120% .
Speaker #5: Similar to last quarter . And our trailing 12 month gross revenue retention percentage remained in the mid to high 90s . And now moving on to our financial results .
Speaker #5: Our billings were $893 million , up 30% year over year . Our remaining performance obligations , or RPO , was $2.79 billion , up 53% year over year .
Speaker #5: 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 and RPO .
Speaker #5: And now let's review some of the key income statement results . Unless otherwise noted . Otherwise noted all metrics are non-GAAP . We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release .
Speaker #5: 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 .
Speaker #5: As previously mentioned , we continue to see the impact of our engineers cost saving efforts in Q3 as they deliver on our cloud efficiency projects .
Speaker #5: Our Q3 OpEx grew 30% , 32% . Excuse year over year , down from 36% last quarter . We continue to grow our investments to pursue our long term growth opportunities .
Speaker #5: And this opex growth is an indication of our execution on our hiring plans . Q3 operating income was $207 million for a 23% operating margin , compared to 20% last quarter and 25% in the year ago quarter .
Speaker #5: 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 .
Speaker #5: And cash flow from operations was $251 billion in the quarter . After taking into consideration capital expenditures and capitalized software free cash flow was $214 million for free cash flow margin of 24% .
Speaker #5: 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.
Speaker #5: 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 .
Speaker #5: 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 .
Speaker #5: And for the full year fiscal year 2025 , we expect revenues to be in the range of 3.386 to $3.39 billion , which represents 24% 26% year over year growth .
Speaker #5: 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 .
Speaker #5: Based on 364 million weighted average diluted shares . Finally , some additional notes on our guidance . We expect net interest and other income for the fiscal year 2025 to be approximately $170 million .
Speaker #5: We continue to expect cash taxes in 2025 to be about 10 to $20 million . And we continue to apply a 21% non-GAAP tax rate for 2025 .
Speaker #5: And going forward . And finally , we expect capital expenditures and capitalized software together to be 4% of revenues in fiscal year 2025 .
Speaker #5: 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 .
Speaker #5: And I want to thank Datadog's worldwide team for their efforts. And with that, we'll open the call for questions. Operator, let's begin the Q&A.
Speaker #2: 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 one on your telephone and wait for your name to be announced .
Speaker #2: To withdraw your question , please press star one one again . Please stand by while we compile the Q&A roster . And our first question comes on line of Ryan of Goldman Sachs .
Speaker #2: Your line is now open .
Speaker #6: Hi . Thank you very much . Appreciate it . Congratulations on on the spectacular results in the showing of sequential improvement across the board .
Speaker #6: Olivier , I had a question for you . We've talked about GPU modernization versus CPU modernization . So how close 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 .
Speaker #6: That's it for me . Thank you so much .
Speaker #4: Yeah , so so we have products that are that are getting into the market now for GPU monitoring . But these don't these don't generate any significant revenue yet .
Speaker #4: So all the revenues we share like the acceleration etc. . That's not related to us capitalizing more on GPUs . That's the future opportunity .
Speaker #2: Thank you . One moment for our next question . Our next question comes from the line of Sanjit of Morgan Stanley . Your line is now open .
Speaker #7: 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 .
Speaker #7: What are you sort of put the improved performance and growth this quarter on ? You mentioned that the sales productivity or the benefits from some of the sales investments are starting to come online .
Speaker #7: Is there sort of an uplift in sort of the cloud migration trends you're 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 .
Speaker #4: Yeah , I'd say there's three parts to it . One part is the demand environment is not 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 .
Speaker #4: We know which happens from time to time . So that's point number one . Point number two is we've been growing fast . Capacity quite a bit .
Speaker #4: And we've created new go to market motions to go after the kind of customers we were getting before . Like we we've done quite a bit of investment over the past couple of years and we we see that starting to pay off .
Speaker #4: As I said , also , we we feel good about the , the what Q4 in terms of pipeline on the sales side .
Speaker #4: So it's too early to tell yet . We still have to close those deals . But we feel good about the 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 .
Speaker #4: Some of them are early , some of them are a little bit further along . That are really clicking . You know , we see , you know , we have a lot of success with getting large prices to adopt flex logs , for example .
Speaker #4: We have a lot of success from new products , products such as analytics that we mentioned on the call . We're seeing some large land deals with our cloud team .
Speaker #4: So all of that is contributing to the picture you're seeing today .
Speaker #7: And Is there any work you think Datadog has to do to sort of infiltrate that 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 into their solutions .
Speaker #7: 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 the as part of their sort of value proposition .
Speaker #7: I'd love to get your perspective on that.
Speaker #4: Yeah . I mean , there's absolutely no doubt to us that the customers will , will need and want a unified platform for observability for all of these .
Speaker #4: 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 want themselves , also has its own management console and observability console you're not going to log into , you know , 70 or indicates of customers we mentioned , like they use integrations for the small customers , hundred and 50 for the latter ones .
Speaker #4: 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 .
Speaker #4: But 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 , you know , web hosting and your database and your , you know , everything else that you have in your stack .
Speaker #4: So all of that in the end will be attached to observability .
Speaker #7: Very clear . Thank you very much .
Speaker #2: Thank you . One moment for our next question . Our next question comes from the line of Raimo Chow of Barclays . Your line is now open .
Speaker #8: Perfect . Congrats for me as well . That sounded sounded like an amazing quarter and nice to see it coming together . The on the AI side .
Speaker #8: And I don't want to talk about the 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 .
Speaker #8: How do I have to think about the nature of those ? Is this kind of are those kind of especially the bigger ones ?
Speaker #8: Is this those kind of model builders ? But then even 15 is a big number and , you know , over 100 sounds like this , 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 ?
Speaker #8: Because it does sound quite exciting and much more broader than we thought . Thank you .
Speaker #4: It's actually fairly broad , you know , so there is there is model vendors , there's models , you know , models that can be the models that can be , you know , it can be sound generation , it can be all of the various parts of the stack .
Speaker #4: 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 , you know , and everything in the in that range , some of these are very new companies .
Speaker #4: Some of these are not very new companies . Some of these started , you know , five , seven , eight years ago .
Speaker #4: And we're sort of not necessarily alienated from from day one , but very quickly , like what would give them the growth they see today with the the pivot to AI .
Speaker #4: So we see a little bit of that . We have companies that are other parts of the stack in AI . You know , on the side of the serving side , the , the , the other components of the infrastructure .
Speaker #4: And , and we have other companies that are purely applications built with AI . So we have a bit of everything in there , it's actually fairly representative of the of the space .
Speaker #8: Okay . Perfect . That's exciting . Thank you .
Speaker #2: Thank you . One moment for our next question . Our next question comes from the line of Mark Murphy of JP Morgan . Your line is now open .
Speaker #9: Thank you so much . You had mentioned the expansion of the contract with your largest AI native customer , and I believe you , you said better economics for a higher commitment .
Speaker #9: Can you speak to that ? Because I would assume a 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 than than have a quick follow up .
Speaker #4: Yeah . I mean , look , this is without getting into the detail of any specific customer like this is the motion is always the same .
Speaker #4: Customers grow , they commit to more , they get , they get better prices . So you see , you know , like again talking about customers in general , you see growth of usage drops in revenue as customers renew and get higher commit and a better price .
Speaker #4: And then usually growth after that for those customers , that's the , the , the motion that we've had with about 30,000 customers so far .
Speaker #9: Okay . The the what I'm sorry . So the better economics part of it is just where it's going to be netting out like 12 months down the road .
Speaker #9: Is that what you mean ?
Speaker #4: Whether the better economics means , you know , you commit to more , you get a better price . You know , and as we remember , we have a usage model .
Speaker #4: So we charge people every month on what they use at the price they use at the price . We agreed . So if you get better economics and your usage is somewhat similar month to month from month to the two , less , but the overall backdrop of our business is increased consumption .
Speaker #9: Okay . And then as a quick follow up , Olivier , the acceleration that you saw in security growth is pretty noticeable to , you know , 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 into security .
Speaker #9: Business is 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 ?
Speaker #9: So that all the security teams and the ops teams are working with the with the same set of metrics and logs and traces ?
Speaker #4: Look , I think it's a 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 .
Speaker #4: The the big wins we mentioned on security that we mentioned a couple of weeks in the cloud team . These tend to be more related to product maturity .
Speaker #4: 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 , you know , how to properly go to market for security .
Speaker #4: And I think we , we , we see things clicking in the way that that is exciting .
Speaker #9: Thank you .
Speaker #2: Thank you . One moment for next question . Our next question comes from the line of Fatima Bellini of Sydney . Your line is now open .
Speaker #10: 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 .
Speaker #10: Ali , how do Agentic advancements in general detract or enhance the value proposition here ? And I'm very simplistically thinking about the the core nature and value proposition of the on call product , intelligently routing requests for remediation .
Speaker #10: 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 .
Speaker #4: Well , I mean , look , if you if you zoom out , we we entered the field with on call because we wanted to own the end to end incident resolution .
Speaker #4: So we wanted because before that we were detecting the incidents and sending alerts . And then we were pretty much where the resolution happened after that .
Speaker #4: You know , customers were spending their time in deadlock to diagnose and understand what was going on . So we wanted to own the full cycle .
Speaker #4: And we thought that with AI in particular , we'd have the ability to do things if we if we owned the whole cycle that we couldn't , we couldn't do otherwise .
Speaker #4: So what you see right now is , I mean , this resonates with customers , you know , they are adopting the product .
Speaker #4: We've mentioned , like some exciting customers with , you know , like , you know , one with 5000 seats , you , which is very exciting .
Speaker #4: But in the future , there's many more things we can do . And we're working on for that product . You know , if we if we if we both detect the incident and notify , we can do some sort of things such as even predicting the incident and notifying early or rerouting early or , you know , or telling people before the incident actually takes place , you know , how they can potentially fix it .
Speaker #4: So these are all things we're working on . I mean , look , if you look at the the various product enhancements we've made , whether it's SRT or the , the time series forecasting model , we've released , when when you assemble all that , you get to a very , very interesting picture of what we can do in the future .
Speaker #4: So we're excited about that . Our customer excited about the vision . There too . And that's why these products are successful .
Speaker #10: 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 ?
Speaker #10: And I mean , I suspect it's because it's a trailing 12 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 .
Speaker #10: Thank you .
Speaker #5: Yeah , you've nailed it . It's a trailing 12 months . It's a number that's rounded . It has the dynamics 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 .
Speaker #5: So you know , if that continues as you go into a trailing 12 month metric , you see a directional movement .
Speaker #11: Thank you .
Speaker #2: Thank you . Our next question . Our next question comes from the line of Eric Heath of KeyBanc . Your line is now open .
Speaker #12: Hey , great . Thanks for taking the question . I'll eat . 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 AI and how meaningful this can be for 2026 as a differentiator versus competition , and also as a revenue contributor ?
Speaker #12: Thanks .
Speaker #4: Yeah . So I mean , look , it's it's super exciting . The the feedback is very good on it . The I mean , we've been collecting all the .
Speaker #4: So I read one quote , but you know we have you know , dozens that look just like that . That was sent to us by customers .
Speaker #4: And so that's very , very exciting . The we also started , I think , some customers commit to it to just to show value and to make sure we're on to the right product mix .
Speaker #4: And so we we feel good that this is something that is high quality and we can monetize in terms of the impact for next year .
Speaker #4: On the packaging side , I'm not completely sure yet whether the biggest impact will be seen from what we charge for itself or for the rest of the platform that it gets benefits from the differentiation of its .
Speaker #4: 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 .
Speaker #4: So anything that drives 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 this is differentiating .
Speaker #4: 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 .
Speaker #4: We have many , many teams now working on deepening to making sure it goes further into the resolution doesn't just point to the issue , but fixes the code that all these kind of things working hard on that .
Speaker #4: We're also working on , 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 observability , systems that are not Datadog .
Speaker #4: So we can cut across to other systems like customers are using . So we're very , very aggressively developing Bsri . It's a it's resonating very well in the market .
Speaker #2: Thank you . One moment for next question . Our next question comes from the line of Greg Powell of Btig . Your line is now open .
Speaker #13: 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 .
Speaker #13: 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 ?
Speaker #13: And then just how do you feel about the sustainability of those drivers as you as you look forward ?
Speaker #4: I mean , look , the so first , I apologize for delivering on the on the results . We might do it again , but we'll see the I think the biggest surprise for us has been that the so AI in general has or AI adoption has grown faster than we thought it would at the beginning of the year .
Speaker #4: So we've seen that across our AI cohort . We've seen also that we we got some of our new products and new like the changes we are making on the on the go to market side to perhaps earlier than we would have thought otherwise .
Speaker #4: So all in all , you know , we saw the leading part of the business with AI growth after the the , the , not the lagging , but the slower growing , more traditional pottery business also accelerate .
Speaker #4: And that gets us where we are today .
Speaker #5: 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 .
Speaker #5: We made clear that we were in investment mode and we're seeing those investments pay off .
Speaker #13: All right . That's helpful . Thank you .
Speaker #2: Thank you . Moment for next question . Our next question comes online of Koji Akita of Bank of America Securities . Your line is now open .
Speaker #14: Yeah . Hey guys . Thanks so much for taking the question . Just one from me here . I wanted to ask a question on the inflection .
Speaker #14: The non-AI native growth and how to think about the areas of strength in this cohort. Is it coming from your largest enterprises?
Speaker #14: 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 ?
Speaker #14: What I'm trying to get at here is I'm really trying to understand more the durability of this growth inflection . Thank you .
Speaker #4: So so it is it is broad based . And I think again it speaks to a couple of things . It speaks to the fact that in general the demand environment is good though I would say , you know , there's been a very , very high growth of hyperscaler revenue over the past or an acceleration for the hyperscalers in general .
Speaker #4: 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 .
Speaker #4: There's 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.
Speaker #4: They're 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 that we have a few segments , but and we've been doing well at executing there , I think we we've , we've invested quite a bit in product and we keep and we will keep doing it .
Speaker #4: And we see the results of that .
Speaker #5: Yeah , I want to add I'll add that it's across the customer base , enterprise , SMB . And when we look at it , it's not it's not just an AI , SMB .
Speaker #5: If you remove those AI companies , you still still see a strengthening SMB demand cycle going on . And unlike in previous periods , it also is across spending ranges .
Speaker #5: We're not seeing larger spenders or smaller spenders . We're just seeing a broad trend of improved demand across the spending trends .
Speaker #4: Remember that for us , SMB is any company of less than a thousand employees . So it's it includes a a lot of very legitimate and growing businesses .
Speaker #4: You know , it's it's not it's not yet .
Speaker #14: Thank you .
Speaker #2: Thank you . One moment for our next question . Our next question comes from the line of Ittai Kidron of Oppenheimer . And call .
Speaker #2: Your line is now open .
Speaker #15: Thanks and congrats , guys . Really great numbers all in your answer to one of the questions and kind of going into the drivers behind the upside , you talked about sales capacity increase .
Speaker #15: You didn't talk much about sales efficiencies . There a way you can give us some color on where do you stand on percent of salespeople that are hitting quota ?
Speaker #15: Where does that ratio stand relative to historical patterns for you guys ? And as you approach 26 year , do you anticipate any material changes in the comp structure just given the breadth of product and the list of opportunities ?
Speaker #15: How do you get people focused ?
Speaker #4: Yeah . So look , we feel good about about the sales productivity in general , you know , and the rule generally is you grow by scaling capacity and maintaining productivity .
Speaker #4: It's hard to drive both up at the same time . And remember , if you want to grow to ten x you can do that by scaling it .
Speaker #4: 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 .
Speaker #4: Look we keep changing the the way we're we compensate and the way we manage the sales force in general to make sure we have the right focus .
Speaker #4: One of the gifts of a business like ours is that we see we have a very heavy landing expand model , and so we get a lot of growth from leasing customers .
Speaker #4: The challenge in X , on the other hand , is how do we get to focus the sales force on the newer customers ?
Speaker #4: The smaller ones and the the new ones , because it is more work to get an extra dollar for smaller customer or from a new one than it is from an existing one that they already has scale .
Speaker #4: And so a lot of the the tweaks we make to our compliance relate to that . How 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 .
Speaker #4: And we've met a number of changes . I won't go through them . These are internal changes , but a number of changes this year we see a number of them pay off .
Speaker #4: Another thing I mentioned on the call was we mentioned the wind for one of our new go to market motions , and that 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 .
Speaker #4: And sometimes it takes more than a year to land certain types of customers . And the problem is , if your compliance only has a one year horizon , like it doesn't give a great incentive for the sales force to go after those customers .
Speaker #4: And so we cordoned off a few of those companies who have special plans to go after that . And we started are starting to see success with that too .
Speaker #4: This is just an example .
Speaker #15: Appreciate it .
Speaker #2: Thank you . One moment for next question . Our next question comes from the line of Andrew Sherman of TD is now open .
Speaker #16: 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 .
Speaker #16: Curious to hear how that team's ramping to productivity . Did that help drive some of the strong new logo bookings ? And can this contribute even more next year ?
Speaker #16: Thanks .
Speaker #4: Yeah . I mean , look , the team 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 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 the landing .
Speaker #4: A customer , even if it's for a small amount and and I think we've done we've done well . I mean , again , we can comment on that again after the next quarter when we have a full year of of our new plans that have been validated .
Speaker #4: But we're so far we feel very good about it .
Speaker #2: Thank you . Our next question . Our next question comes the line of Alex Zukin of Wolfe Research . Line is now open .
Speaker #17: Yeah . Hey , guys . Thanks for taking my question . And congrats on dropping some truly inspiring quotes in the script . Maybe one for you .
Speaker #17: And then How long do you think we should think about the duration of this trend of this Non-ai acceleration ?
Speaker #17: 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 , RPO , Crpo , those were again , really , really strong .
Speaker #4: Well , you know , we our consumption business . So we the hardest thing to understand is what the future is going to look like for consumption .
Speaker #4: The way I would say it is , we feel very good about it at the mid term , long term . Now it ebbs and flows in a given month or quarter .
Speaker #4: That's harder to tell . And again , that's what we've seen through the lives of the company . So 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 .
Speaker #4: But it reaccelerate after that and we see that going on for a very long time .
Speaker #17: Okay . And then maybe David , for you , you know , look , gross profit , dollar acceleration while you're seeing your largest customer , you know , kind of get better unit economics is also inspiring to see .
Speaker #17: 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 ?
Speaker #5: Yeah , there's a couple of things I think we mentioned that , you know , we've been focused and have focused over the many years on the efficiency of our cloud platform .
Speaker #5: 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 , you know , distributed in terms of volumes .
Speaker #5: So as customers get larger and maybe get volume discounts , we have a number . You know , a lot of customers coming in at smaller .
Speaker #5: So that balance there and then and then in terms of 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 -80 .
Speaker #5: 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 .
Speaker #5: 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.
Speaker #5: And then , you know , developing operations and strategies around that .
Speaker #17: Perfect . Thank you guys . Yeah .
Speaker #2: Thank you . One moment for next question . Our next question comes from the line of Ryan McWilliams of Wells Fargo . Your line is now open .
Speaker #18: Hey , thanks for taking the question . Just one for me on the large AI contract expansion that you provide a commentary on .
Speaker #18: Is there any way we can think about the contribution change from this customer over the next few quarters ? Thanks .
Speaker #5: 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 .
Speaker #5: Generally , I think as Ali mentioned , you know , on our larger customers , we have a motion of the expansion of volume .
Speaker #5: And then we talk when we work on the term and and , and the volume based pricing . But we don't give , guidance like that on individual customers .
Speaker #5: .
Speaker #18: Fair enough . Yes .
Speaker #2: Thank you . One moment for our next question . Our next question comes from the line of Mike Cycles of Needham . Your line is now open .
Speaker #19: Great . Thanks for taking the questions , guys . I just wanted to come back to it . Ali , for the Non-ai native strength .
Speaker #19: I know we've we've kind of hit on this a number of times . Whether it's roadmap , sales , capacity , execution , but like kudos on the numbers here .
Speaker #19: I'm just trying to get a better sense of the why now , is it just is it just a composite of all those different pieces clicking together this quarter , or is there anything more to unpack there ?
Speaker #19: And then I have a follow up for David .
Speaker #4: Again , I don't think there's a there's a lot more to it back there . And I know it's a it's boring in a way , but you , it's also the way we've been growing for the past 15 years really .
Speaker #4: So that's a that's a you know , I would call it the usual .
Speaker #19: Awesome , awesome here . Okay . And then and for the follow up to David , David , I don't want to take anything away from the Q3 results .
Speaker #19: You guys just posted . And we obviously have the the strong guide here for Q4 . But I just can't imagine myself a month from now starting to get inbounds from certain folks asking about the holiday season .
Speaker #19: 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 here ?
Speaker #4: Yeah .
Speaker #5: 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 our guidance .
Speaker #5: We're I think , evolved a lot over the years and sort of days . Adjusted types of days , etc. . And so we would be incorporating that like we've incorporated in other years if are differences in this calendar period , we incorporate that .
Speaker #5: As always .
Speaker #19: Very helpful . Thank you guys .
Speaker #2: 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 .
Speaker #20: Okay . Great . Thank you . I'll ask one for for David and one for Olivier . David , first of all , congratulations on the extension of the the larger contract .
Speaker #20: I think everybody on the line is applauding that . I know you're reticent to get into any details , but maybe I could try .
Speaker #20: 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 from that deal , which I presume landed in your Crpo number ?
Speaker #20: 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 ?
Speaker #20: 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 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 , is a training clusters , perhaps that near-term opportunity is more limited .
Speaker #20: Thank you both .
Speaker #5: Yeah . On the first point , I think , you know , we give a lot of examples and , you know , our motion , which our customers would be following , including that one would be we fix out annual plus commits .
Speaker #5: We're not commenting on individual contracts here , but it would follow a typical path to other types of of of contracts . So that's what we would do .
Speaker #5: Yeah .
Speaker #4: And . On the , on OCI look 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 etc.
Speaker #4: , 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 .
Speaker #4: So the opportunity there is more remote today . But it's you know , , one company uses that . It's a not fantastic opportunity to productize .
Speaker #4: But if you know again 50 companies start using that , then that really becomes a commercial opportunity . And so we're very much plugged into all of that .
Speaker #4: And we go basically where our customers are .
Speaker #5: I think I you mentioned about the RPO . No , I think in this case , we mentioned that this current and the and the total is roughly the same .
Speaker #5: And there wouldn't be anything in that contract that would have been , you know , materially around those numbers , those those numbers .
Speaker #5: I think we mentioned are produced from the bookings growth more generally and not from that particular contract .
Speaker #20: Okay . Thank you .
Speaker #2: Thank you . One moment for our next question . Our next question comes from the line of Jake Roberge of William Blair . Your line is now open .
Speaker #21: Yeah . Thanks for taking the question . Just on the recent go to market investments , obviously it seems like there's been a lot of traction thus far with those .
Speaker #21: So I'm curious if there are any areas like security or the new logos or up market that that you could look to , to lean even deeper into , just , just given the growth that you've seen here ?
Speaker #4: Yes , definitely . And there are some things we we didn't do this year that we were definitely going to do next year .
Speaker #4: 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 of planning for next year .
Speaker #4: And you know , we're we basically will keep scaling what's what's working . Stop doing some of the things that , you know , are not conclusive .
Speaker #4: And then try a few more things . That's the that's the way it works . You know , the interestingly enough , building a go to market is not that different from building software like you .
Speaker #4: You experiment , you gather data , you see what's working , what's not working , and and you build a systems .
Speaker #21: 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 , to kind of the ramp of security flex logs ?
Speaker #21: I know obviously , much earlier days , but just how it compared when those were were still largely in the preview phase .
Speaker #4: I mean , look , the the agent is , is it really has a real factor for customers , you know , so what works really well is and we've seen that in a lot of times , like they , they we set it up for them .
Speaker #4: It's running on their alerts and they go through an outage and they still go through the motions . So they still go , they still set up a bridge and they have 20 people and they spend two hours .
Speaker #4: And in the end they have an idea of what went wrong . And then they go to that and they see , oh , well , there's a there's an investigation that had run and you know , three minutes into the outage , it got the same conclusion that we got two hours later with 20 people on the call .
Speaker #4: And that completely eye opening for customers when they see that . And we have that's why we get many quotes about it . So now , you know , there's more we need to do there .
Speaker #4: Customers say , oh , this is great . Now can it make the fix for me ? Can you do this ? Can you do that ?
Speaker #4: Can you support that other system ? That right now you can't actually set it up for ? So we we we have a very , very full roadmap of , of things we need to do .
Speaker #4: And we're doubling down on it . We also shipped I mean , this one is in preview , but we shipped a , a security agent that looks at vulnerabilities and looks at security signals and those three are like basically look at the Chinese .
Speaker #4: What might be benign 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 products , because the combination of the theme that runs extremely efficiently on top of observability data that runs a very efficiently on top of flex logs , but also says an immense amount of time by getting 90% of the issues out of the way with automated investigations , that's extremely attractive to customers .
Speaker #4: 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 .
Speaker #4: Whether that's on the planning side , the product building side or on the sales side where I said we have a really , really .
Speaker #4: Exciting pipeline . And so we have a lot to do . I want to thank the team for the hard work . There .
Speaker #4: I also am looking forward to meeting a lot of our existing new customers at AWS Reinvent in a few weeks , and I'll see you all there .
Speaker #4: Thank you all .