For showing up here after lunch. We got a nice-sized group here. So I will work through some questions, and we'll certainly allow some time for Q&A. And with a group like this, like, we might get a question or two. Oh, that'd be great. Well, we'll see. Yes. Get your questions ready now. Ask questions. Yeah, please. Right. So yeah, Q them up, get them ready. Mm-hmm. We will, we will get to that, eventually. So yeah, with us in this afternoon slot, we've got- Mm ... David Obstler, CFO of Datadog, Yuka Broderick, IR, down in front. Thank you, Yuka, for coming as well. So I guess, David, for you, you know, you guys came off a really strong- There was a lot of concern going into your print, and you guys had really, really nice results. Yeah. Yeah, how do you feel about the macro trends that you saw? Mm. You talked about them kind of post the quarter- Mm ... into October. You know, maybe, bring us through the year, because- Yeah ... it's been a little bit of an uneven year. Yeah. Talk about what you said through October. Yeah, well, we have a cloud-based consumption model. Our revenues are associated with monitoring cloud workloads, and that means that we're correlated broadly to the workloads that are through the hyperscalers, as well as how clients use the platform- Yep ... and all the tools. And we've been for well over a year in a cost management environment- Yep ... Fed, raising rates- Yep ... and things like that. We've been talking for the last year plus about the O word, optimization, and clients managing their cost structure, are not surprising. There was some very caffeinated growth in the period from 2021 into 2022. And many of those companies that were cloud-native and had expanded the most rapidly have taken a crack at their cost structure. Yep. That's because of the changes in their business, that's because of all of you people moving from growth at all costs- Yeah, yeah ... to a balance. Yeah. Thank you. It was gonna happen. And so that resulted in some pressure on our existing customers' use of the platform. I think we talked over a year ago about a cohort of cloud native, rapidly scaled, and some affected industries, and that group had moderated their usage. And what we said last quarter was that we started to see signs of some stabilization. Yep, yep ... in that cohort. And in this quarter, we said that happened. Yep. So, the most intense period of the optimization that we've seen to date was in the middle of Q2. Yep. And that relieved itself a little bit. And then we said, across the whole customer base, there is an overall cost management, so there's more focus on cost. And while the rest of the customer base, even, you know, down to the SMB, hasn't been affected as much, there was an overall sort of management, reducing the rate of growth of consumption of the platform. So, we said on the earnings call that, we're not declaring the end of this period. Yeah. We think there'll still be optimization there, you know, always is, but that some of the most intense areas had abated, and some of them have even began to grow a little bit. Mm. So that's sort of updating- Yeah ... everybody on what we've been through. I just- Mm-hmm ... we had had a keynote, and we talked about- Yeah ... some of these trends. I think, you know, the term that we talked about at lunch was being cloud smart. Smart. Mm-hmm. Yeah, absolutely. You know, and as you talk to, you know- Yeah ... sort of customers, I mean, is- Yeah ... it's a journey, right? But, like- Yeah ... I mean, you said, like, this period of most intense optimization- Mm ... has at least settled out a little bit here. Mm-hmm. You know, when you talk, is there a way to sort of quantitatively think about, you know, if I was spending X, now I'm doing this? Mm ... and, like, this is the new baseline? Or, like, is there an opportunity, do you think, for sort of getting smarter, even with cloud spend? Yeah, yeah, definitely. And that happens all the time. So we've said that cloud allows you one of the benefits of putting your applications on the cloud is that you can control burst up and burst down. Yep. You can manage capacity, and it's much more flexible than a data center model, where you're invested in CapEx, or in some ways, a CapEx model. And so, that's definitely one of the benefits. We find that our customers are always, we're always looking for optimization projects. It's just that in that period of emphasis on growth and not on smart cloud- Yeah ... a lot of the world emphasized speed and putting capacity on, and didn't emphasize what they had done all along, which was optimizing that and looking at, as you say, cloud smart. Yeah. The world before that was cloud smart, you know, for the most part. It looks like, you know, it's returning to that. Yeah. I think the companies that had put an emphasis on their operations all along were cloud smart. Yeah. Interesting. Yeah. You said... So I think you made a comment a second ago, or I know you made it- Mm ... on the earnings call- Yeah ... about some of the most heavily impacted- Mm-hmm ... customers- Yeah ... are actually starting to, you know, maybe even do a little bit better- Mm ... and show some, like, I don't know, or if you said acceleration, but even better trends there. Maybe talk about, was that because, do you think they optimized almost too much, and now they're kinda coming back? Or what was the dynamic there? Well, yeah, the behavior they're evidencing is they right-sized. Many of them, and we talked about signing contracts, commitments with us- Yep ... and longer term. Many of them found the right equilibrium. One of the great things about our product is it's sort of a must-have utility. So, for the vast, vast majority, and you can see it in the gross retentions, it's not a matter of turning it off, switching- Yep ... insourcing. It's a matter of calibrating the cost. And so we saw that activity... and then we saw a period of more commitment in there, and then I think we said we saw, you know, some modest growth in that group. Yeah. We don't know. We don't know what's gonna happen next, but that likely means that for this cohort, which was the most impacted, the weight down- Yeah ... the decel, and maybe even- Yeah ... to cutting their costs, probably is easing. Hmm. Mm-hmm. You know, one of the things that we look at for you guys, and other consumption- Yeah ... models, everybody, you know, you know, we're on the edge of our chairs when- Mm-hmm ... AWS, Azure, GCP prints. Yeah. You know, when you look at your numbers internally versus- Mm-hmm ... what those guys say- Mm-hmm ... how correlated is... What kind of a correlation do you see? Like, you know, in other words, are you surprised when, I don't know, pick GCP, you know, pick a hyperscaler, when they say they're- Mm-hmm ... you know, sort of, like, more positive or sort of more- Mm-hmm ... negative comments, or is- Well, I would say we're correlated long term, because we're correlated to- Cloud growth ... cloud workloads. Yep. Okay. We're correlated to modern DevOps and cloud workloads. Lift and shift, picking monolithic legacy applications, isn't what Datadog does. Yep. So I would make three comments. One, long term, we're correlated. Two, the cloud, the hyperscalers have a much broader business than these modern workloads. Yep. Most likely, AWS has you know, more of their business in these type of workloads. When you see some others... They announce it, they say there are lots of other things in here. There's Microsoft Office, there's G Suite, et cetera, and we're not correlated to that. So I think it's not perfect, it's directional. Then the other thing is it's not timed perfectly, because the vast majority of the expense is in the cloud- Yep ... it's many times, and what they do on their monitoring and the other parts of it that aren't host-based pricing, can have different timing. So directionally and long-term, it is correlated. Yep. And I know all of yous are trying to get daily correlation- Yeah ... and it's not gonna be that perfect, 'cause the cloud providers don't give you the numbers and be able to do that, and it's not, you know, a one-for-one minute correlation. Excellent. Um- Sorry about that. No, that's good. No, that's, we're always trying to look for those little incremental nuggets. Yeah. Last quarter, you talked about larger customers growing at a slower rate than smaller customers. Mm-hmm. Yeah, maybe talk a little bit about that and, you know, how this long tail of smaller- Mm-hmm ... customer spending may have impacted- Mm-hmm ... you know, kind of net customer additions. Yeah, definitely. So let's go to that first, because that's not a dollar number, that's a net customer. Customer. And then we'll go to- Yeah ... what we call the paying customers. Yes. So essentially, yes, we've had a very... We report net. We've had very similar and consistent gross, and the gross has been at a little bit higher of an average land. We'll talk about that in a second. So underneath of this gross, the net, the gross has been really solid throughout this period. We have a freemium to very low use model, bottoms up, and we have a very long tail, $5 a month- Yep ... et cetera. So what we experienced since the economic difficulty is this very long tail isn't. There's some of them that drop out. I think we said in Q2 that that group accounted for $50,000 of total revenue. Yeah. So this is about getting users to use the product. Yes, they're free, and if they get a certain number of hosts, they flip over into paid, then they might flip. So that's really the gross net story. The low end and everything is something we would watch, but it's more marketing expense. Sure ... trying to get people to use it. Then in terms of size of customer, we've always had the highest net retention and in smaller customers and then in ramping customers, and we've always had net retention in SMB that's been. We said, it's much the same as enterprise. And it has to do 'cause it's workload-related, and that's most likely because as customers are ramping their workloads in a new product, they're growing faster, and it tends to be net-net. You know, if they're smaller, they're not as ramped and they grow faster. So that's what's been in the company from day one. Everything in this I mentioned, there was the most affected, and then all the cohorts notched down because of cost management, but they maintained their hierarchy and- Hmm ... in spend, meaning the smallest customers and SMB growing the most on a net retention basis. Now, that's... So that's sort of what happened, everything notched down. Excellent. Um- Yeah ... you know, and I guess given that consumption pricing model- Mm-hmm ... do you find, and, and obviously we're seeing more and more- Yeah ... companies adopt that. Yeah. And it feels like that's kind of... Mm-hmm ... accelerate from a new software model perspective. Does that help onboarding, and does that help your onboarding initiative? Mm-hmm ... when you're sort of paying for ROI from that perspective? Definitely. There's no question that land and expand, and essentially we start out always with a free trial, which takes no time to set up, so our clients are using our product, and then they decide, after they run their reports, if they wanna use it, because of the way the platform's set up to not have any implementation. So having that ability to get on really quickly and then manage your commitment flexibly, is one of the great things about cloud. It's not just Datadog, it's also the hyperscalers- Yep ... et cetera. So essentially, they're able to commit conservatively, because these are newer workloads, see how those workloads scale, everybody. We do, you operate with some on-demand for flexibility up and down, and then once you see your workloads, you can recommit. And that's what happens with the hyperscalers in Datadog. It's a very flexible model, and also a model that has been very important to our customers. We also operate in the same thing as the hyperscalers on a commitment, meaning you choose which products, but you can use the platform, so you can essentially switch between products. It's really one product. And you can also decide between reserve instances and flexible. Yep. And so this, again, we didn't invent it, it was the hyperscaler, and it's the way our customers buy. But it provides a lot of flexibility so you don't have to go all the way and build a big data center, you don't have to commit to seats that you may or may not use, and that's how the product gets adopted ubiquitously, and been at the core of Datadog's success. So you started out the year, I believe your revenue guidance. Mm-hmm ... was 25%, and then you lowered it to 23%, and now it's back to 26%- Mm-hmm ... right above where you, I think, initially started. Yeah. Talk a little bit about your guidance philosophy. I know it hasn't changed- Yeah ... but just, you know, help us think about- Yeah ... how you build your guidance- Yeah ... and sort of the assumptions built into Q4. Yeah. Yeah. I mean, a couple things. One, as you progress more in the year, more of the year is baked, and so your variability, once you get to- It's more, yep. ... to Q4, is only about Q4. So you've already have all that. So naturally, if the trends have proven that you're at a 25 or, you know, 26, there's not that much that can happen in the fourth quarter to change that very much. Yep. So that's one thing. So that'll always happen. In terms of guidance, we basically looked at the data sets and the environment, and we haven't changed. We've basically discount the major drivers, which are the net retention or organic growth rate, or usage growth, and the new logos. And we look at the environment and try to take a... It's a risk management exercise. Yep ... try to create a risk-adjusted revenue number. And if the world is better than that, and even better than we had planned for that risk adjustment, then the beat is better than that. And then in Q2, we said we had lower organic or lower usage growth than we had previously, and that would... We'd take that information and say, "Since we don't control this completely, we're gonna risk manage that down," and that will result in guidance getting lowered. It's a risk management exercise- Yeah ... to try to maintain, you know, the cushion. So, I think you said you put more weighting on some of the more recent data points. Mm ... than you did previous, you know, earlier data. You know, I'm curious, when you get into the 2024 budgeting cycle- Mm, mm-hmm ... how long will you maintain that Q2 data point as part of your, sort of your thinking? Because, like, Q- Well, we're looking at the... So, of course, we're not gonna provide guidance off of the COVID period. Sure ... because it isn't as relevant. So we're trying to determine through analytics, through looking at slicing and dicing our customer base by size, by cohort, by cloud native, by product, and looking at the data, we get a report every morning. So we're just basically every week aggregating that and trying to see what we think is the state of play. It can't be perfect. We don't control it, but there's not a formula. We're essentially risk managing what we think is the environment, and so we'll use not just... As we said, we're not using October or September, we're using all of it, a data set. I don't know how to answer the question because it changes over time, whether that's four quarters or five quarters or three quarters. It has to do with how trends are moving. I- Mm. Okay, so that's... I guess, yeah, that's a help. I'm trying not to disintermediate myself and lose a job. If we can create an AI CFO- Yeah ... I'm gone. Yeah. I'm trying to, you know- Yeah, there's a human element to this. ... put a little human element to this. Sure, of course. But I might do that for a while. Yeah. Yeah. So I guess the point of... Yeah. That, yeah, well, I'm sure there's somebody working on that. Yeah, probably. Yeah. That'd be great, yeah. Yeah. I won't tell, you know, I have it, but I won't tell anybody- Right ... for a while, and then, yeah. So I guess I Yeah. You know, I mean, 'cause when I think about that Q2 data point- Yeah, yeah ... obviously there was some negativity in that quarter. Mm-hmm. I guess the question is, like, you know, does, that's, it feels like it's gonna be part of your thought process- Mm ... for some time. Mm. At some point, it's gonna be some so far- Yeah ... removed, that you'll be like, "Okay, you know"- It's whether that was an aberration, a bottom related to... and you only know that as your time series develops. Yeah. At that point, this is part of our philosophy. We said, "The world's uncertain. This could be the trend, right, going forward." So we took down our guidance, assuming that. Yeah. Now, what we do next year will be based on have we had enough of a time series and the analytics around customer base and usage to feel confident that we have sort of a stable or increasing set of metrics- Sure ... and then we'll discount from there. I see. That's what we're doing. Okay. Yeah. From- Mm. That's helpful. Yeah. From a Q4 perspective, let's just say- Yeah ... things just kind of stay status quo. Yeah. That still implies... I mean, based off of your discounted assumption- Mm-hmm ... that's, that's still a beat scenario, if, if- Well, everything- so basically what we would do is we always take the status quo- Yeah ... and discount it. Discount it, yeah. That's what I mean, you know, let's call it risk management, rather than be. You know? But basically, that's what we're doing. We're basically taking the assumptions that we see in the business, and we're building in conservatism, which if things don't change, if they stay where they are, builds in a beat. Yeah. Okay. Yeah. Bigger beat if things get better. Worse beat if they don't. Yeah. Yeah. Yeah. Yeah. Well, let's keep focused on things getting better. I have to do that for you. I have to basically-... I have to look at her and go, "Some that," you know, kind of thing, but- All right. No, that's a helpful perspective. Yeah, yeah. you recently announced two new, DevSecOps packages- Mm-hmm, mm-hmm ... which I thought was really interesting. Yeah. How do you think about... I mean, it, the- Mm-hmm ... it's, they're just brand new, so it's probably- Mm-hmm ... you don't have much data on it yet. Yeah. Like, how do you think about things like that driving the model? Mm-hmm. Like, how do you- Yeah ... how do you think about that as a driver? Yeah. So essentially, thinking back, if you look at, on the website, you'll see that the philosophy of pricing of Datadog is to use the nomenclature, host, test, data, and to put functionality on top. So for instance, if you're buying infrastructure and you want something that has more containers, or you want, network, or if you're buying APM and you want, code profiling, or you want... You know, so that, that is the way our customers buy. And they like that because they basically can think, "I'm buying infrastructure." It's really infrastructure, APM, and logs, right? "But I'm getting this functionality." So, in the past couple years we've been sort of building this product line and getting to the point where we could do, more than put it out there and having certain customers use it. This is a mark that we are confident enough to bundle it, still focused, in this case, on DevSecOps. But the way they buy and the way we've conditioned them is to buy as this host fee plus incremental amounts. Yeah, yeah. And so it's still too early. We have some good, you know, feedback, and we talk to clients about it, but essentially this is a packaging that is consistent with the way we've packaged the customer base, made possible by the number of use cases covered, having extended, so it can be more broadly- Okay ... sold through. Yeah, that makes sense. What it does to the sales, we obviously did it because we thought it was a good move to enhance the sales pace. We'll have to see. Yeah. Too early. Yeah, yeah. Yeah. One other... I wanna go back to pricing- Yeah ... 'cause I forgot- Yeah ... to ask it to you. There's a real tie to ROI with what you guys do. Mm-hmm. Yeah. You know, a lot of us, you know, we'll talk to customers and they'll say, "Well, I love Datadog- Mm-hmm ... but, gee, it gets, it's like my Datadog spend just gets really big. Mm-hmm. How do you think about, like, thinking about those strategic customers? Mm-hmm ... do you wanna provide... I mean, it's not shelfware, right? Mm-hmm. So, like, how are those conversations with customers that all of a sudden starts- Yeah ... spending $5-$10 million a year with you guys, and like, I, you know- Yeah ... "I love it, but I don't want it to go to 20"- Yeah ... right? Or for what, pick a number. But, like, how are those conversations? We do it in so many ways, and we've always done it. So basically, we wanna price transparently. We have a CS group and a technical account management group that have always worked with clients to help them use the product. We've developed additional SKUs where TAM where we essentially go in and we help a client use it correctly. Much of the ramping unintended is due to user error or not setting it right. So we try to help clients get to the right spend. We also have pricing that's based on volume, reserve, and term. Yep. We also have a whole group, like you're saying, that goes in and helps the client understand the return on investment. We do analysis versus other vendors, open source, and you know, and having slower remediation. I think in our script, we had, you know, a number of things- Yeah ... that where we said, "You know, the return on this is quite high. Yeah. So we've always... And we've gotten better at it, helping clients understand how to get return, and also how to use our expanding product set to get the most return. So it's, helping our clients long-term is why we have that gross retention rate- Yeah, sure ... in the very high 90s, and why essentially clients, you know, don't generally leave us. They generally work on trying to use the platform more. Yeah efficiently. The other nugget that I think... I think it was a new nugget for Q3. Mm-hmm. You said 2%, 2.5% of your ARR- Mm-hmm ... was from gen AI companies. Yeah. You know, talk a little bit more about that, 'cause I think it's a great number. Yeah. But also, you know, for companies that aren't like, you know, a bank like RBC- Right ... you know, how are we, you know, thinking about Datadog? Yeah ... from a gen AI perspective- Yeah ... as well? So, I think we gave the metric for the first time last time, when we announced, you know, at our product line at DASH. So there's three things. The first and most immediate is there are a number of modern software companies that are developing tools in the AI stack. You know, a number of them, and they are essentially delivering software and services to clients, and that's one of our expertise area, is in monitoring- Mm. Yeah ... client-facing, modern development software. So those would be the technology companies. That's the 2.5. Yes. Okay? That's been growing very rapidly, so it's always nice to have sectors- Yes ... where your product fit is really, really good, and the way you, you model, and so that's one. The second thing would be that we have developed, we, we've announced and are building out a number of LLM monitoring modules in our platform, and we're building integrations. And that's where, you know, and RBC or something, if, if and when they are injecting-... AI into client-facing, real-time software. It's not about the marketing department- Yeah -generating, you know, collateral. That's, that's not what we really are. Yeah. But that is looking like very early that there are use of these integrations, that's model-level monitoring and how it interacts with the software. And that, we think, although it's too early to give you a number, is going to result in an increase in workloads that we're monitoring. So we're building the platform for that. So that's number two. I don't think there's, as Oli would say, "It's too early. Yeah. It does not having- Sure ... a major effect on our numbers right now. And the third would be in the platform itself, to introduce more AI capabilities, including our chatbot, our- Yep ... you know, Bits. Yep. As well as things like, self-remediation or auto-remediation. That is platform which we have, as we've done this over the years, gotten broader adoption on the platform, you know, more client retention, and more market share in the market as we've done that. So those are the three ways we think we can monetize this opportunity. Sure. Mm-hmm. When you think about... You didn't guide to 2024, and I don't- you're not gonna give- Yeah ... guidance today. But if you were thinking about building blocks- Mm-hmm ... or sitting in our shoes- Yeah ... how do we think about sort of like, the major drivers to next year? Obviously, we're all looking at maybe, you know, if cloud consumption has bottomed- Mm-hmm ... and maybe starts to improve. Yeah. That obviously is a good thing. But how would you suggest we think about modeling- Mm-hmm ... without guiding us? Yeah, I mean, it's basically, it's basically a Net Retention, plus the layering in of new customers, and modeling out, the as they come up to speed. Yep. I think we have numbers, you know, in our disclosure. I think this time in our queue, it was 60%-65% of revenue growth comes from existing customers, and 35. So it's a model that would then vary the net retention, resulting in that 65% moving, and then developing your own view on logos- Yep ... and what the average size of that from what you've seen, and that would be the way we would build a model, and then have many cases off that. Sure. Yeah. Helpful. I'm gonna pause here a second. Sure. Is there a question out there? Yeah, go ahead. Where do you view the Datadog in the... 'Cause we're seeing, like, cybersecurity- Mm-hmm ... coming to the space with CrowdStrike. Mm-hmm. We're also seeing, like, ITSM with ServiceNow. Mm-hmm. This morning, there was GitHub saying they also wanna get in, into observability. Yeah. So where do you see Datadog fitting into this space? Yeah, I think it's question is do, what do they mean by it? Like, we say ITSM, we're not trying to get into caseload or human capital. ITSM, for us, is the ability—it's DevOps, and it's the ability to use our product to more efficiently. So that's what we say. Like, if we just said, "ITSM," you would say, "Oh, you're gonna go in the ServiceNow." I'm just being very, like, black and white with you, and I think that's what a lot of other companies don't do. Because in our end market, which is essentially monitoring real-time, customer-facing applications that are run on the cloud using DevOps, most of these other companies mean something else, and they're not in the market. In security, we also don't mean, we also don't mean, endpoint, we don't mean network, we don't mean so many. We mean essentially using security signals in building and putting software in production for our DevOps, so DevSecOps. So a lot of others mean something else. So I think it's really getting under and understanding what is your end market, and what are you trying to do, and are you successful at it? The rest of it, we could do, like, it would be much the same thing. Like, "Okay, let's just go into ServiceNow's market." Yeah, of course, we could. We could create a company, add 10,000 employees, or build from scratch, but we're not doing that. And most of those others aren't doing it either, what they're saying. They're just using a lot of words. Okay. Maybe just on that- Yeah ... competitive question, there's $4 billion- Yeah ... of Splunk ARR that, you know- Yep ... who knows what- Yeah ... what's gonna happen to that in the future? How do you, what do you guys think about that, in terms of, like, how that, how their customer base aligns- Mm ... with yours- Yeah ... and how big of an opportunity that could be? We're not in their market, their vast majority market. We're not in that centralized security SIEM. Yep. We're not in that market. It's a complete different architecture. Because our architecture is to be able to be in real time and, and be, have access and use, and they're, they're not. So they have, you know, some business that we compete with them on, where they've gone into, into Cloud SIEM, but, And it's not whether they deliver their security SIEM in the cloud or on-premise. The vast majority of their market is not our end market. Some of it is, and we've been, you know, winning in that part, you know, for a while. So, it's, it's mainly a different market. Okay. Mm-hmm. Maybe in the last 30 seconds here- Yeah ... that went, that went quick. You know, we're gonna we're sitting here next year. Mm-hmm. Let's fast-forward a year. What are we gonna be talking about next? Like, what are some of the most important trends that we should watch when we're sitting here, this point next year, and we're like, you know, asking you questions about? Yeah, yeah. So it would be, number one would be the growth of cloud workloads, modern cloud workloads, as an underpinning for the business. That's the most important. Number two would be our market share in the platform, and our ability to continue to win the full platform. So our ability to consolidate and win. Mm. Number three, let's say, would be what's happened with AI. Yeah. You know, how real is it? And lastly, would be the success of DevSecOps. Yeah. Those would be the things- A lot of drivers. Yeah. Those are the drivers. Yeah. Excellent. Yeah. Well, that was too quick. I have- Yeah ... intended more questions, but- Okay, no problem. ... we could keep going. Thanks a lot. Paul from RBC, David, thank you. Thank you. Appreciate it. Thank you. Thank you. Thanks a lot. Thanks for- Thanks for great questions. Thank you, everybody.