Confluent, Inc. (CFLT) Earnings Call Transcript & Summary

All right. Welcome, everyone, to the second day of the 26th Annual Credit Suisse Technology Conference. My name is Phil. I'm one of the software analyst. We very excited to have a longtime friend, CFO of Confluent, Steffan Tomlinson, joining us. Steffan, thanks for coming down again. I always appreciate you taking the time out.

My pleasure. Thanks for hosting us.

I'm going to start with the question that I think I've asked every person. I know you're going to be surprised by the first one, but hey, in light of the macroeconomic environment that we're seeing out there. I mean, obviously, there are a lot of cross currents. From your recent customer interactions, obviously, you just also had your Current not that long ago. What are you seeing in terms of how those conversations, let's say, have changed maybe versus the beginning of the year? Where are you seeing the best strength and resiliency people saying, "Hey, look, I need to invest in Confluent now.

Well, it's clear that data streaming and the era of data streaming is here. Customers are increasingly wanting to get all of their applications and data stores connected in real time, and the resiliency of that even in a depressive macro environment is strong. How things have changed? People are, and customers are definitely looking at ROI and TCO in a very meaningful way. And that accrues to our benefit. We've come out with our 10x better than Kafka campaign. We've led with the TCO and ROI. The payback period is less than 6 months for us. And when you look at how just the evolutionary process is working with data streaming, the batch processing that happens in many companies is going by the wayside as companies are trying to get more efficient in their back-end office operations, but more importantly, also how they're interacting with their customers. In this real-time, data streaming platform that we have is really hitting the mark with customers.

Yes. I mean just thinking about the Current, I mean, the -- if I have to describe some of my interactions with your customers is sort of real-time and real-time visibility, it sort of mattered more now than ever. Because of these crosscurrents, your customers are having deal with those, but things are changing so fast, but the old batch way of doing it is like you're too late. And so real-time visibilty and complexity, higher now more than ever, and comes Confluent.

That's right. And the other thing about our platform that is a big differentiator is we're cloud native, which means that everything is built cloud-first, and we're in all three major cloud service providers. We have a complete product offering and we're everywhere. And as customers are looking to deploy solutions, both on-prem, in cloud, in multi-cloud environments, and they're looking for a robust way to have a security profile that's resilient and robust. It's really -- accrues to our benefit that we have such a broad suite of product offering.

Yes. Awesome. Now speaking of products, I want to highlight some of the announcements that were made not that long ago at Current. I'm curious just what the -- I mean, obviously, they're still very new, but sort of what the initial customer feedback or traction has been? I mean the ones that jumped out to me, your Stream Designer, your Stream Governance products -- just provide us some sort of data points of what you're hearing from customers about those? And how do they fit into sort of the broader Confluent story?

Stream Designer is a perfect case in point around how we're democratizing data streaming for the masses. And as you think about what was happening before Stream Designer, engineers would have to go into command line interface, type in code to connect applications and data stores and create streams. That was good. But what's with Stream Designer, we have a graphical user interface, so data scientists and other people in the organization can, with a GUI interface, literally connect streams real-time. And why is that important? Well, all of a sudden, more people can be using our product, more streams can get created. The benefits to the customer are real. And we are not separately monetizing Stream Designer, but what we're seeing is with more streams being added, more streams being created, the usage and the consumption is increasing. And for us -- that's a win for us in a big way. Stream Governance is incredibly important. This is something that we do separately monetize. And if you think about breaking down Stream Governance into some of the fundamentals, you think of Schema Registry as one thing, you think of Stream Lineage. You really need to be able to understand and govern the data that is running through the system. And Stream Governance provides that telemetry to ensure that we are enabling customers to understand where their data is coming, where it's going, the integrity of the data, it hits a lot of those marks.

Yes. Awesome. And then that was the thing with Stream Designer that also jumped in May to just talking to customer who's getting their initial feedback when launch was sort of like the virtuous cycle, it's like the more streams, the more data. Basically, the more value they can get out of Confluent as their heart, their central nervous system. But this is just a way to get more streams, more value in there, into the Confluent Cloud. So it's a very cool product. And I guess let's stay on the Confluent Cloud, just theme for a moment. Now you talked about maybe a 2 to 3 percentage point increase per quarter in just cloud mix when you think about next year. What do you think about driving that? How much of this is sort of land versus expand versus some of these new products? What is driving that mix higher?

Yes, it's a combination. But what we've seen profile-wise is the last, call it, multiple quarters, greater than 50% of net new ACV has been cloud. And that has been a shift over time that we've seen. In this last quarter, over 60% was cloud. So net new ACV that's landing is cloud-based. And that net new ACV will turn into consumption over time. And then you also have the benefit of customers that are existing Confluent Cloud customers that are seeing increased usage and increased consumption relative to their committed contracts. So it's both a land and expand dynamic that is driving the revenue share shift to cloud, which goes right to the heart of the 2 to 3 percentage point per quarter, comment that I made on the last earnings call.

Got it. And sticking with the cloud theme, this is a question I get a lot, so I want to post it to you is that, sort of the role of the hyperscalers viewpoint so that you run on all the 3 major clouds, but those hyperscalers also do have our competitors, too. So can you talk about sort of the differentiation and sort of why customers select you?

Well, the cloud service providers are great partners of ours. First and foremost, there is a level of coopetition. The coopetition really comes in the form of each of the cloud service providers has a competing product. But as you do a technical comparison, whether or not we're looking at AWS' product offering or Azure's or GCP's, none of them really hit the 3 main components that we talk about being cloud-native, having a complete offering and being everywhere. And I can dive into each of those in a moment. But what I can tell you is when customers are looking for choice, they really want to ensure that they are buying what's best technically, and then what it can operate seamlessly with their cloud service provider. We are on each of the 3 cloud service providers' marketplaces. There's a level of technical integration that we have with each of the 3 cloud service providers. The 3 CSPs really value our relationship because we have driven tons of workloads to their infrastructure. And the name of the game for each of the cloud service providers is to have as many workloads as possible getting into their infrastructure, and we facilitate that in a meaningful way. The other thing is, as you think about just like the product offerings in general, the fact that we're a multi-cloud in nature is a big differentiator relative to the other offerings that are out there. We have innovated on security feature functionality. We've innovated with Stream Designer and Stream Governance. These are things that are increasing our technical lead against the other competitors in the space. And the fact that we're cloud native, the cloud native aspect of it is incredibly important because this isn't just about putting open-source Kafka into the cloud. This is about instrumenting and architecting a full-service cloud offering that is very robust in nature. Yes. And so as you think about just the levels of differentiation, we compare very favorably. And ultimately, the cloud service providers are great go-to-market partners for us. Each of the cloud service providers enable their reps to retire quota when they sell us and they also enable their customers to burn down their committed contracts when they're selling Confluent.

Yes. I mean I thought there was a big announcement earlier this year, that strategic collaboration agreement with AWS, because that was always the question, it was like, the overhang of the hyperscalers like, actually, this is not just any sort of agreement is strategic collaboration agreement, dual commitment, real marketing dollars, real R&D dollars. And I think, Jay, I think he said it best to be the best cloud to run Confluent Cloud, and that is their differentiated point, the workloads that you can bring along, and that they want to differentiate by being the best cloud to run Confluent Cloud.

That's right.

So I thought that was super interesting, very different, call it, reality from sometimes a narrative that's out there. So the -- but let's stick with this too, because the other question I get on from a competition perspective is your advantage over, call it, the traditional like database players, even the ones that are in a cloud. Snowflake, Databricks, who say that they have real-time streaming as a functionality as part of their offering, but the question is, is it really just micro batching ahead and how is that different than sort of what Confluent is doing?

Well, first off, Snowflake and Databricks and other companies in the next-generation technology stack, they're great partners of ours. The fact that they're leaning into streaming is really more of an ingestion engine for their infrastructure. That's actually good for us because the more prevalent you have data streaming, the more mind share it gets, there's a virtuous cycle. But there is a very big difference between what the database companies or the analytics companies are doing relative to streaming versus what we're doing. They're doing more about ingesting into their platform versus what we're doing, which is at a layer lower and also connecting multiple applications and multiple systems and really running a central nervous system. So there's a big differentiation between the two, but the thematic point around data streaming, data availability real time, that is something that accrues to our benefit.

Yes. 100%. Let's switch gears a little bit and talk about verticals because I thought this is one of my big takeaways from Current as well. Now the technology vertical, we've been sort of obviously highly focused on that because they are big users of Kafka. I remember when you went public as sort of 10 out of 10 of the biggest tech companies are users of Kafka and -- whether it's typically self-managed, open source Kafka, abundance of engineering talent here to run that. But I feel like you've started to see a pivot, particularly within that vertical, realizing that, hey, look, DIY-ing, Kafka doesn't necessarily scale. And so are you seeing that cohort, in particular, take back to, call it, Confluent and thinking about actually Confluent Cloud being a cost saver relative to DIY-ing it?

We are starting to see that. And it's almost kind of a -- it's a sign of the times, I would say, where companies who have large do-it-yourself Kafka implementations, they're going through a reckoning where they're looking at the number of engineering people that they have, the server infrastructure that they have to run, the security bolt-on applications that they have to put into their system, the complexity of managing a large do-it-yourself Kafka implementation is -- it's hard to manage, and it's costly. As I referenced earlier, we've come out with this 10x better than Kafka campaign which you really look at ROI and TCO and payback periods, we scan very, very favorably relative to yourself Kafka. And for the large digital native companies that are out there, they're reconsidering the do-it-yourself approach. And part of that is due to the sign of the times that we're in. With budgets tightening, with more focus on ROI and TCO, if we can roll out a 10x better solution on multiple dimensions, it became -- it becomes a very compelling business opportunity for us. Are we going to see people convert overnight? No. It's going to take a while, especially for these large implementations. And you referenced our user conference Current. We had New Relic on stage. And New Relic is a top Kafka user in the world, and they basically got to the point where they had a very large engineering team, large infrastructure, became very costly and just very complex to manage the updates that just -- like the operational complexity of it was off the charts, and they also wanted multi-cloud. And the reason why they ended up choosing Confluent and Confluent Cloud in particular, is the ROI and TCO and the fully managed services offering that we bring to the table. And we believe that we can go after other large digital native companies out there with a very similar like sales and marketing approach. And as we look towards FY '23 and FY '24, while we haven't had exposure to the large digital natives, we think that there's an opportunity to really go after them, and that should be a growth vector for us.

Yes. No, it's funny because we're talking about them because obviously, they call it tech sector exposure has not been great for some other software companies recently, but it was awesome for a little while, but now the digital natives going the wrong way for us like, actually, you guys are sort of the opposite. You've already seeded usage with Kafka now as opportunity when budgets get tied to increasingly monetize. And so, kind of the opposite play.

Yes, it is the opposite. I agree.

Yes. So everybody write that down. But actually I want to talk outside of the tech vertical. Is there -- are there any industries -- are you seeing a lot of momentum right now within financial services, retail, et cetera. Is there something where it's like, call it, what the value of the Confluent provider is really registering right now?

Certainly, in the financial services vertical, a lot of those companies that we have counted as customers were typically Confluent platform-only customers. And what we're seeing with some of the largest banks is a real change in approach around evaluating Confluent Cloud to be additive to their environment. And that's something that will be an expansion opportunity for us outside of the financial services vertical, in health care and manufacturing. We've also seen very good adoption where a lot of those companies had been very Kafka-only. We've rolled out use cases for those verticals that we're starting to see some traction on. But I'll tell you, across every vertical that's out there, it's data streaming is a horizontally applicable technology. And it's incumbent upon us to be very forthright around use case and leading with use case in order to ensure that we can not only have land customers, but then expand once we get in. We've talked about this before. I'm very agnostic around land size. What I care about is the type of customers we're landing, because once we land, we have a demonstrated ability to expand. And that shows up in our net retention rates, and we look at both gross expansion and gross retention, Confluent Cloud, and then also our hybrid customers who are running both cloud and platform tend to be great customers for us over time.

Yes. That's great. Let's switch gears a little bit and talk about go-to-market. I wonder if you can -- I kind of want to frame this in sort of the context of productivity and capacity. And so I can -- because, obviously, there was -- you've done a lot of hiring, you've been leaning into it. At Current, at the Analyst Day, you talked about the ramp versus ramping reps. So maybe walk us through how you're sort of thinking about kind of the go forward of sort of where you are in go-to-market capacity, productivity, what's impacting that?

Yes. Well, for starters, let me just give you a little bit of background. All the way going back to 2020, when we paused hiring due to COVID, 2021 was a year of catch-up investment where we added a fair number of sales folks and customers, and employees across the board. In 2022, what we've seen is the cohort of salespeople that we hired in 2021, those folks are going to be exiting 2022 fully ramped. And from an overall population standpoint, our quota-carrying salespeople will have proportionally more fully-ramped salespeople than ramping salespeople exiting 2022. So for 2023, we're going to continue to invest in the business for sure, but it's going to be at a more moderated pace than what we did in 2022. And specifically for go-to-market in the sales organization, we're going to be very, very tactical around where we're going to be adding the new quota-carrying heads in regions that have a strong demand signal for Kafka. And there are also some accounts that could use more complement salespeople, because the opportunity is so large. We mentioned before we have the cohorts of companies that are spending $5 million and $10 million of ARR. Those have been growing over time. And so satisfying those customers and servicing those customers will take more go-to-market resources, but the payback is incredibly high.

Yes, totally. How do you -- when you think about the marketplaces because this is a question I get a lot. How do you think about being in sort of the hyperscalers marketplace, it's viewpoint, you're being able to burn down credits, how does that layer into sort of the traditional sort of go-to-market model? How much leverage do you think you'll get over -- get off of that over time?

Even though we've had tremendous traction with the 3 cloud service providers, marketplaces, we feel like we're like -- I don't know, maybe the first inning, but [indiscernible].

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Yes. And where I think we actually get leverage out of that is as the sales people from the 3 CSPs are looking to sell data streaming services, that will be a lift to us because a lot of that will be complement. There are also resellers and channel partners that will be going through some of the CSPs programs that will be a lift to us as well. And as we think about continuing to have deeper technical integration with the 3 CSPs in terms of strategic collaboration agreements, that will also drive what I would just call, like less reliance on accounting executives having to touch every account. There can be pay-as-you-go, there can be other like aspects to our business model that become more efficient drivers of leverage going forward.

Yes. Great. All right. Let's talk about TAM because that was obviously something that was highlighted at the Analyst Day. You have $60 billion TAM that you talked about. And one of the things that jumped out was like the potential over $10 million plus, as you talked about a $5 million plus ARR, companies in the Fortune 500. How do you think about sort of, how do you get there? Because obviously, you've got some big customers right now. And in fact, we've talked about there's the $1 million-plus customers you have for sort of a company of your size, you're sort of an outlier in terms of how big your customers get and how fast, and so in a good way outlier, but it's pretty impressive. But how do you think about that next level? What gets you to that $5 million, $10 million? What do you need to see from a customer to get there?

Well, we've outlined this customer growth and go-to-market journey. That's a 5-stage process. The initial stage is literally pay-as-you-go. It's customer swiping a credit card or starting with a free trial, then swiping a credit card without even talking to a salesperson. But as you go up to that curve of the journey, when customers are running multiple mission-critical applications that start to stitch together the fabric of the infrastructure of the company that they work at, where they have the applications and data stores and databases connected into our data streaming platform, that's when you start to see the real lift. And the final stage is really when we become the central nervous system where ultimately, nearly all applications and databases and data stores are connected into our data streaming platform. And when that happens, that's when you get to these $5 million-plus, $10 million-plus ARR customers with very high gross retention metrics.

Yes. No, totally. I mean it's funny. I'd almost describe it as -- I was talking to somebody at Current. It was almost like a 2-step process, so to speak, because it's like, okay, this is go live with Confluent Cloud. There's that initial very fast ramp, potentially getting big fast and getting value out of that. But then there's sort of the second step function, maybe third if you pilot onwards, say, actually, that was pretty awesome. This ramped really fast. But if we put this in there, these extra streams, those streams can provide exponentially more value than all of a sudden you do get to that $5 million to $10 million-type customer. And so -- but it's the proof point on that first one that ramps fast.

Yes. And that's the key. I mean, first off, the time to value for customers is incredibly important because once you make it a decision on implementing a new technology, if you don't see the value in a relatively short period of time, the enthusiasm for that purchase wanes. So the fact that we have a robust portfolio of connectors -- as an example, we have over 120 pre-built connectors. And for those of you who aren't familiar with why connectors are important. If you don't have a connector that connects an application into our system, you would have to write one. And if you're writing a connector, that takes a lot of development hours, et cetera, with these pre-built connectors, it's plug-and-play. So the more connectors that we have, the easier it is for people to get started and to realize value.

Got it. Now one thing just looking at your P&L, Confluent continues to invest in R&D and product development. What trends are you trying to get ahead of, or maybe even sort of just simply solidify your market position? Like what are the priorities?

Well, we're cloud-first, for sure. That doesn't mean we're cloud only, because where we sit in the next-generation technology stack of vendors, we have to be both on-prem and in the cloud. To be a true central nervous system, you have to be where a customer's data resides. But from an engineering prioritization standpoint, we are cloud first. And so what does that mean? Well, feature velocity and development cycles are focused on cloud-related products, Stream Designer, Stream Governance are two examples. We're going to continue to invest in those areas. We're going to continue to invest in security. You cannot deploy a mission-critical application or have a central nervous system based off of a data streaming platform that isn't secure. So think of role-based access control. Think of a whole bunch of other things that go into the security profile of the product offering. That's going to be extending our lead. And then as we move further up the stack, we have investments we've been making in ksqlDB, and in that area. So we're going to continue to make investments there for sure. And some of them will be separately monetized like Stream Governance -- Advanced Stream Governance. Others will be part and parcel of the offering, which will drive the incremental usage and consumption, which we'll get paid for at the end of the day.

Okay. That makes sense. All right. So last question in the last couple of minutes we have here. Okay, let's say we're sitting back up here 2, 3 years from now. what do you think we're going to look back on and say, hey, look this trend, maybe this product, this technology was more impactful to Confluent's customers than people were giving a credit for back in 2022?

I think it starts with data streaming as a new paradigm that's out there. There have been many attempts at this over the years. But really what Jay and Neha and Jun, their original thought around creating Kafka, which then evolved into Confluent, the prevalence of data streaming across all environments over the next 3 years is something that if we were sitting here in 2025, I would think that, that would be like the de facto standard. And I can't imagine any new application or data -- kind of data profile that isn't real time in nature being deployed over the next 3 years. I think that is the standard going forward. The second thing is, as it relates specifically to Confluent, the ROI and the TCO value proposition that we bring to the table, will continue to resonate with customers, both in a challenging macro environment. And then at some point in the future when...

You're coming out of the other side...

You're coming out the other side, it's still going to resonate. And that's really a testament to the product and engineering work that we're doing and our ability to articulate from a go-to-market standpoint, the positioning and the value add that we bring to the table.

Awesome. Very excited. Well, we'll talk about that in 3 years. We'll write that down, we'll revisit it. So -- but I agree with you. I think that's where the future is heading, and excited to watch the Confluent story evolve with it. Awesome. Well, thank you, my friend. I appreciate you coming down as always. Thank you so much.

Thank you so much. Appreciate it.