Thanks everyone for joining. This is day two of the Wells Fargo TMT Summit here in sunny Southern California. Michael Turrin, the Software Analyst here at Wells. Very pleased to have Confluent's CFO, Rohan Sivaram, with us, for the next session. A good packed group of attendees here, so we may open it up for questions towards the end, but I have a list to get to, and I wanna start high level because I think in a lot of investor conversations, there's still a lot of education going on around data streaming and Confluent, what Kafka is used for and why Confluent. So maybe you can set the stage with just high level, what the technology does, who it's built for, and where points of differentiation sit versus open source. Yeah. For sure. First of all, thanks for having us, Michael. Good to see you as well. Morning, everyone. So I think a great question, and what I thought would be a good idea is actually go back to our founding story. Sure. Our founders, Jay, Jun, and Neha, were working in the infrastructure software team at LinkedIn. Mm-hmm. They realized pretty fast that how complex the data environment can get. Primarily when you think about, when a new person joins LinkedIn, there is, like, hundreds of different actions that need to happen in the back end in real time. And they were candidly just struggling to make it work. And back at the time, there was no out-of-the-box solution to make this happen. So that was essentially the inspiration for Kafka, which was written by them while they were at LinkedIn. Yeah. Subsequently, they open-sourced it. What Kafka does is it's a layer where all data streams from the organization actually resides, and applications can actually pull the stream based on what their needs are. Going back to my LinkedIn example, when, say, someone is searching a particular event, or someone's getting added to the network, or someone's adding another person, there are multiple triggers of events that get... that happen. Right. And, everything's in the Kafka layer, and these applications can seamlessly pull the data. So that's essentially what it is. And fast forward, Confluent was founded, and we've continued to differentiate ourselves from the open source version of Kafka with our cloud product, with our on-prem product, which we can get into, but that's the broad story, Michael. Okay. Super helpful. And then maybe just your background as well, because you recently stepped into the CFO role. So another aspect that investors may be newer to. You spent some time at the Investor Day, and I think investors are starting to kind of build profile, but maybe you can give a little bit of your background, how long you've been with the company and just your focus areas as CFO. Sure. Well, before Confluent, I started my career with Morgan Stanley in their asset management. Spent a few years there, then decided to go back to school. After school, so the last 15+ years, I've been in tech operating roles, and, the last decade has been in high-growth tech. Six years at Palo Alto Networks and about a little over three years here at Confluent. When I left Palo Alto, I was, head of SVP... Head of finance, SVP finance there. And when I joined Confluent three years back, I, I basically started and, built a FP&A Investor Relations, treasury, business operations team ground up. And I was essentially joined at the hip with Steffan with respect to running the financial operations. So... And, you know, my focus areas actually go back to why I joined Confluent, and that's not changed. The reason I joined Confluent three years back was, I'd say, the three Ts. There was a really large TAM, $60 billion+ TAM, and the opportunity, when you couple that with hundreds of thousands of organizations using open source Kafka, very, very compelling. How you're taking advantage of the opportunity matters, and we were doing that with differentiated technology. And and we continued to build a moat from a technology perspective. And of course, last but not least, like, we have an amazing, talented team. So when you combine these three together, there's a compelling opportunity. And when I stand here today and I think about it, the opportunity continues to be the same, and my focus areas has always been, how do you take advantage of this opportunity? And you do that by essentially high level, doing three things. Number one, you're allocating resources and capital in an efficient manner. Mm-hmm. You're doing that to ensure that you're driving durable and efficient growth over a long period of time. The third piece is, you can only drive efficient growth if you have this focus on unit economics and an ROI culture within the company with respect to how you invest dollars. So, you know, making sure that we're focused on the big opportunity and how we are driving it is my focus area. Okay. I'm gonna ask one more high-level question, and then we'll get into some of the details of the most recent earnings results as well. But I think one of the key questions for Confluent, and this is something I've asked Jay in the past around too, is I think the platform story is fairly clear because of the type of industries that you're going after. On the cloud side, I know there's a sort of a just the temporal nature of the company started with platform and built towards cloud. But how do you influence customers who are large Kafka users over to Confluent Cloud? What are the kind of stats, metrics, ROI, TCO, type of statements that you can make? And is that something that the team has gotten better at from your perspective? Maybe just kind of talk through the value proposition of cloud, and the potential to bring over the larger open source users that would be very compatible. Yeah, I mean, that's a great question. When we look at our opportunity, the open source community is a really large opportunity, hundreds of thousands of organizations using it. And Confluent differentiates from open source on two fronts. First of all, there is this meaningful technology differentiation that we have, and then there is the cost side of it. On the technology side, we like to say that we have a complete data streaming platform, and what that means is it's cloud native, it's complete, and it's everywhere. I'll double-click into each of them because these are important. When I say cloud native, what it means is our technology scales up and down, it's got high SLA, it can be multi-tenant, all the key features. And, for engineers here, you know that it's not an easy thing to build, and you don't get that in open source. So that's number one. Number two, our data streaming platform is complete. What that means is open source is all about streaming, which is critical, but our view, our vision is not just streaming. We've got 120+ connectors and the connectors ecosystem, which brings a lot of data into our platform. We have governance products, which make sure that the right people have access to the right data. And last but not least, we also have stream processing, right? When you kind of combine all of this, we feel that we have meaningful technology differentiation. That's one. On the cost side, obviously, we provide meaningful ROI and TCO, and, you know, we've shared that a bunch of studies out there, which shows that the ROI and TCO we bring. I just want to simplify it. If you are a company using open source Kafka, where are you spending your dollars? You're spending your dollars typically in three categories. The first is you have these infrastructure costs that you're spending your money, and given that this is one of many things that you're doing, your focus is not to optimize and make that infrastructure cost get better. Typically, that's number one. Number two, you're paying for very, very expensive Kafka engineers, and it depends on the size of your open source shop. It could be a handful to 10, 15, 20 engineers, right? The third category is you're also paying for governance and security bolt-on applications. What we do with Confluent Cloud is we're basically providing all these three together as a service to you, and we obviously spend a lot more time in driving efficiencies and making it cheaper for you. Yeah, that's great. So on the Q3 results, before I get into some of the metrics and the puts and takes of what you laid out, I just want to ask kind of a high-level question around how you manage internally through the volatility that we're seeing in the market. I think the volatility has been staggering for many of us across earnings cycles, and it, in many cases, has intensified. So just internally, when you're managing the company and the culture and trying to explain what's happening and keep everyone on the same page, what does that look like, afterwards? I know the company's seen volatility in a few different stages, but maybe you can just give us the sort of the on-the-field perspective of what happens within the company when Q3 results come out and the stock is just seeing sort of a meaningful change in where it's sitting. Yeah. Michael, I'll go back to the point I made around really taking a step back and looking at the opportunity, and reminding the team that we have a special opportunity, large TAM, differentiated product, and we're, I'd say, in pole position to take advantage of this opportunity, not only because of the current products that we have, but because of the vision that we have. And that's important. That's really important to continuously share that perspective. So I'd put that number one. Number two, it's all about controlling the controllables and focusing on what you can control. And from our standpoint, over the next 12-24 months, we have, from a technology standpoint, very important technology unlocks that are gonna come our way, so the focus has to be there. On the go-to-market side, we're going through this consumption transformation, which we might talk about. Yeah. It's not a business model transformation, but it's a go-to-market transformation. We need to be focused, and that's in our control, and we need to flawlessly execute against it. So, while it's not easy, it's important to take yourself out of the noise and focus on the big opportunity at hand, and focus on what we can control. Yeah, that's a good answer. So on some of the Q3 metrics, in terms of cloud revenue, maybe you can just level set for investors who aren't as close to the mechanics of what we. We're used to seeing that Net New ARR sequentially build throughout the year. When we started this year, I think the message was that progression was what was expected. We've seen some puts and takes. I think Q2 was a little stronger, and then Q3 was a little bit lighter. So what are the factors that are kind of altering the trajectory in cloud currently? Yeah. For our Q3 results, at our earnings call, we shared... Essentially, there are two categories. The first category is what I'd call fairly idiosyncratic. Two customers are impacted, and, you know, I'll get into it. And the second category was more around, we've been seeing this slowdown in net new use cases, primarily in the digital native segment. Yeah. So let me start with the first category. The two large customers, we called out that the first was a large gaming customer, and this gaming customer made an independent architectural decision to move out of the cloud and go on-prem, and Confluent was impacted by their independent decision. The reason they made that decision was because they had an outage, which is public, right? Yeah. What that does is, it's a fairly large customer, and you don't get revenue from a cloud perspective from that customer anymore. Right. That's impact number one, which had a partial impact in Q3 and a full quarter impact in Q4 and 2024. Yeah. So that's... The second customer is a large customer of ours who are going through a transaction, and they have a commitment, but they're going through a transaction. So the forecasted consumption curve versus the actual consumption curve, there's been a delta. Yeah. That showed up in our Q3 numbers, and that's what we called out. So to your question, this first category is fairly idiosyncratic, and it's customer specific. The second category, the digital native customers who, you know, candidly, they've been under cost pressure over the last 12 months, 18 months, and we're seeing that the deployment of net new use cases there slowed down. Mm-hmm. And these are probably the two drivers that have impacted our results in Q3. And we basically, you know, said that they'll be impacting our Q4 numbers as well, and that's part of our guidance. Super helpful. So a couple of just follow-on questions on that. So the customer that's moving off of cloud entirely, is that something you could recapture as platform? Is that, is that a theoretical possibility for the future for Confluent, or is that not something we should consider? It's a good reminder. I should have mentioned it. We're in active conversations with them as we speak, to help them with their on-prem workloads. Yeah. Yeah. Okay. And then on the, on the net new use case side, is there anything that you've gathered that would support the notion that just data architecture conversations are becoming more complex and longer cycle because of AI? And every company having, I think, more intense focus on prioritizing data-driven decision making, but trying to figure out what to do, given how many different vendors are coming at them with solutions which are not competitive with Confluent, but are in some way adjacent. I'll say that the second category is not pervasive across our customer base. It's mostly in the digital native segment. Yeah. That's an important differentiation, right? That particular segment, in the last 12 odd months, has seen cost pressure, and as a result of that cost pressure, I'd say that we are seeing a slowdown in the net new use cases. I mean, taking a step back, well, the three drivers of consumption revenue, when you think first principles, is existing use cases driving more volume. That's one. Number two, just net new use cases, which candidly is the bigger driver. And the third category is, you know, I was talking about the data streaming platform, selling more complementary of the data streaming platform. And that opportunity is ahead of us because we'll have a series of unlocks in 2024. Okay. When you think big picture and take all of this into account, it's the second category where... That's also a subsegment of our customers. Okay. So just from there, moving on to the—I think—so on the go-to-market changes that you're making, maybe you can just help characterize how significant or less significant those are. Because I think when software investors hear go-to-market changes, they tend to think of sweeping, overarching, significant changes. And I think there's more general caution when those changes happen heading into the end of an annual cycle. So you chose to make the, the changes now, and maybe you can start by just characterizing what those changes are, how significant or insignificant those changes are? You think will prove, and then we can talk about, like, what the forward vision after those could look like. Yeah. When you, when you think about, the go-to-market change, I'll, I'll just say, a couple of, I'd say, points I wanna make before the, before I answer your question. Sure. This is not a business model change. It's a go-to-market change. And the reason I say it is, our cloud business is based on consumption. Rev Rec, how we sell, how our customers consume, no changes there. So what are the changes? Changes are today, when a customer is using and consuming Confluent, they focus on consumption, and they want to commit to the amount that they are consuming. When you compare and contrast that with how we are incentivizing our sales force, we're currently incentivizing our sales force to get the largest ACV deal. Right. And there is this inherent friction in the system. With this change, we are trying to take this friction away by incentivizing our salespeople based on consumption and not bookings and ACV. So in a nutshell, that's the change. And when you think about the change, we're not doing the change in Q4. It's going to happen January 1, 2024. And most of our consumption peers, at some point in their life cycle, have actually gone through this change. Okay. They've had good results. I wanted to call that out as well. From the nuts and bolts of the change, what we're gonna do is this year, we actually dipped our toe in the waters, and for a cloud deal, about 15% of incentive was based on consumption. Okay. We're gonna move from that to 100% incentive based on consumption. Okay. The focus of our reps will be to drive that incremental dollar of consumption. Yeah. So. Thank you. I mean, the reason I asked, and I didn't want to necessarily lead the question is because it would seem like that's very much aligned with what your customers would expect, and maybe in an environment where there's increasing focus on cost, better aligning their expectations with consumption, just removes some friction- Right from decision making. Is that a part of the consideration? Yeah, that is... That is a part of the consideration. And, it's all about focusing on what is the driver of consumption and channelizing all our efforts to that, versus trying to get the-- I mean, you can get the largest commitment from your customer, but we recognize revenue based on consumption. Right. So- Yes, certainly. After you do that, the rep's focus will obviously come back to consumption and making sure your customer is successful. So why, why focus on driving and getting the biggest deal? So that's another point I wanted to just hit on. Does this at all change the type of sales rep? Based on what you said, it sounds like no, but does this – is it the same sales rep that was going after a bookings number, going after a consumption number, mapped similarly, or does it change the profile of sort of go-to-market sales reps that you would consider? I wouldn't say a huge change. I mean, in the last reported quarter, north of 40% of our revenue was coming from cloud- Yeah -and consumption. So that rhythm, that DNA, has been building in the company for the last couple of years. So, I wouldn't say that there's going to be a major change, but anytime there is a go-to-market change, you can expect, a small part of your sales force, you know, might weed out. And, you know, we've kind of baked in that implication of that change- Okay. -into our guidance for 2024. Okay. Yeah. Helpful. As the CFO, does that impact the visibility that you have into a customer spend, or do you have enough cohort analysis and kind of data to make an educated guess around similar customers, similar profile, consumption patterns, and mapping those all together? Maybe you can just touch a little bit on if that alters visibility at all for CFO and forecasting, and then we can get into assumptions used in the prelim targets. Yeah. When you look at our business, the part of the business that comes from on-prem Confluent Platform, there are no changes. Yeah. So, you know, that's give or take, you know, just shy of 50%. That'll continue to be there. Yeah. For the cloud business, I think over the last few years, we've gone through this big change with respect to how we forecast, how we manage, and it's a big change because in a traditional world, you start with bookings, and then you have your rev rec rules, and you come up with revenue. In a consumption world, you actually start with revenue, and we've built that DNA within the company, where we're forecasting consumption at a customer level. And, I'll tell you, it's, it's difficult to just forecast based on spreadsheets. We have our data science team driving predictive models to figure out, you know, what the consumption patterns could look like. Yeah. Right? And then you have the qualitative inputs from the field for the larger customers. Again, going back to net new use cases, et cetera. So you triangulate all of these factors to come up with a point of view. And I'll tell you, as a CFO, I definitely focus on the health of our install base, and our gross retention rates, ever since we've been a public company, has been north of 90%, which obviously helps from an overall baseline setting as we look ahead. Yeah... That's great. Yeah. I mean, at this point, it seems like the key question that investors are focusing in on is just the prelim targets that you framed for next year, the 22% growth targets. What went into those, if those are likely to prove conservative? And I think that's—you're gonna get a lot of questions on it for the foreseeable future. We are as well. And so maybe you can use this as a forum to just go back to the assumptions that you used in those forecasts, if there are layers of conservatism because of some of the things we touched on there today that might not have been there in years past, and your sort of confidence and what can drive you towards those targets, or ideally above, if the company executes. Yeah. I'll start off with my overall guidance philosophy, which is, which has been very consistent with how we've done it in the past, which is making sure you're setting prudent but achievable guidance, and you're doing that by providing good visibility into the drivers of the business to the investor community, and that's not changed. And that was our approach as we looked at our 2024 guidance. And again, it goes back to the three drivers that we've been touching on. So I wouldn't get into the details, but I'll just touch on them, right? Number one is the two customers. Again, idiosyncratic, but will have a fuller impact in 2024, right? The net new use cases from digital native, we expect that impact to go into 2024. The consumption transformation that we just touched on, that is something... It's a change. At any time you have a go-to-market change, you just need to be prudent. Yeah. So we've built in that adjustment period, we are gonna see probably the first six odd months of next year into our numbers. And so these are the three numbers, and that's how we thought about... I'll say that exiting next year, we'll obviously have a series of product unlocks, and that starts with our stream processing product, which is going to GA in Q1 next year. There'll be a series of networking and security unlocks that are gonna happen. And we'll have FedRAMP, we'll have, you know, obviously more momentum in the marketplace around AI. So we see a reasonable amount of tailwinds for us as we exit Q4 of 2024, and that gives us confidence that we can bridge to the 30% medium-term target that we have. Very helpful. And so on the Flink stream processing opportunity, is it your guidance philosophy because it's not yet available to kind of remove assumptions from that in terms of contribution for next year? Yeah, we're, we're not assuming a huge amount of contribution next year, and we expect to GA the product in Q1. And anytime you have infrastructure software products, you need to build applications. And, you know, I, I touched on it during Analyst Day. Rough and tough, it takes about six months for, for you to get value and get up to speed. Okay. So if you do the math, you're in Q4. Yeah. Exiting next year, we are gonna start seeing momentum on the Flink side. Helpful. We have seven minutes left. I'm gonna turn it over to the group and see if anyone has a question. You can raise your hand. I think we have mics and that capability, if you'd like. Up front. You can go ahead. You... Yeah. Should I repeat the question or- Yeah. Yeah. Yeah, yeah. I mean, I think question is around how do you get the quotas right, given the change? Yeah, it's a great question, and when you think about what are the quotas gonna be, the quotas are going to be consumption. And like I mentioned to Michael, we are currently forecasting consumption at a customer level, purely based on that's how you need to do it. So from an internal operations perspective, how we are forecasting the business does not change. So our visibility will not change from a business perspective. So we feel good that, you know, we are in a good position operationally to set the right quotas. And that's... That obviously we're gonna learn as we go, but where we stand today, you know, it's not gonna be a huge change from an internal operations perspective with respect to how we set quotas. Having said that, how we run the business, it's gonna be different. Like, this year, a definition of a pipeline is, you know, bookings, and next year, the definition of a pipeline is going to be net new use cases. So, you know, those are changes that we are working on and making sure that we'll be ready as we get into January 2024. Last one on margin. Yeah. You've driven... I mean, that—so that became a point of focus when the, sort of, the macro changed, and Confluent has shown good progress on free cash flow. I think on the cloud gross margins and what we get to from implied shows significant improvements there as well. How do you think about sources of future leverage there? And do some of the changes you're making on the go-to-market side impact the ways that we should think about margin progression, at least in the sort of, the near term? Yeah. If you, if you look at the last seven odd quarters for us, we've we've improved our margins by 35+ points. And when you look at our guidance for Q4, we've said that we'll be op margin neutral. And when you look at our guidance for 2024, we've said that for the full year, we're going to be we'll break even from an op margin perspective. And when you compare guidance versus guidance, that's another nine-point of improvement full year. So we've we've seen a big trajectory from a margin improvement perspective, and you don't see this kind of improvement if you're not intentional about it and if you don't have the buy-in from the company. So I think that's something that we've bought in, that we need to be driving efficient growth. So, you know, that's how we are seeing a trajectory. So going back to your question around sources of leverage, I think clearly if you look at last seven quarters, go-to-market has been a contributor of sources of leverage. As you look ahead, we expect to see that go-to-market will contribute from a leverage perspective. And, you know, we're getting to a size where the partner ecosystem over, say, the next 12-24 months, will contribute from that perspective because you get the attention of the SIs and GSIs. So that's one area. Obviously by removing the friction from the consumption transformation, you expect to see productivity improvement. That's going to be another source of leverage. I'll be remiss if I don't mention, you touched on it, like our cloud margin improvements over the last 12 months, 18 months has been great, although we don't report the number. But, you know, again, making sure that we continue to drive that focus will be important. Yeah, that's great. Just a few minutes left, so I'm gonna turn it back to you for closing thoughts. But I think what's important is to kind of think through the three-year or the five-year tailwinds that keep you enthusiastic around the Confluent opportunity. You touched on AI. We haven't touched on it in this conversation. So maybe between Flink and stream processing and potential other tailwinds that you see, what are the tech trends that have you excited and kind of viewing Confluent as this growing into a significant and expanding market opportunity as you initially characterized it? Yeah. I think today, when I look at the world, every company is a software company, and every company is a data company. So success of these companies will depend on how well they are able to harness their data, and the power of data will show up. And we're a key player in making sure companies can do that efficiently, companies can do that economically, and companies can do that in a safe manner. So, that's the biggest trend that we see. Now, if you kind of look under that, like a couple of microtrends, clearly cloud and the move to cloud, the digitization there is going to help. Right. AI is going to help. If you go one level deeper, you know, we're not just about streaming, we're about a platform. And we didn't spend a lot of time, but stream processing is very, very critical. It's about how you use your streams of data matter. I'll give you a simple example. If you are a travel company and your agents have a stream of data on flight times, and then there is another stream of data coming based on weather, and there's another stream of data based on customer information, you can combine all these three streams with stream processing and provide meaningful insights specific to specific customers around flight times, correlating to weather, correlating to, you know- Yeah. What, how it could impact them. So it's very powerful. And spend today, when you look at companies, there's a large amount of spend happening in stream processing. So that's another area of opportunity that we see. That's great. Lots to keep busy with. Appreciate all the details in the conversation, Rohan. Yeah. Thanks for joining. Thank you.