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

Good afternoon, everyone. I'm Rob Owens with Piper Sandler. I'd like to welcome management team from Confluent for our next session. Joining me from the company is its CFO, Steffan Tomlinson. Steffan, welcome. Good to see you.

Great to see you. Thanks so much for having me.

Absolutely. So first off, congrats on the recent IPO in June. And I guess given that you're newly public, some investors are still really learning the story. So for those not familiar, can you give us the quick elevator pitch? What's the problem you're solving? Who uses your product? And how do they use it?

Sure. As you know, data in today's modern businesses, it's in constant motion. And data flows between applications, systems and IoT devices, sensors, just across a variety of environments. And the problem is that the bulk of the data infrastructure that exists today is focused on storing data and not harnessing it. And the issue is because the data continually flows across businesses, you really need a central nervous system to tie it all together. So Confluent was founded to solve this problem, and we pioneered a new category of data infrastructure, focused on data and motion to enable organizations across virtually every industry to run their business in real time. And the end result is really a rich front-end customer experience in an efficient real-time back-end operations.

So maybe then digging into data in motion, a few examples in practice of how this would work.

Take an online grocery store in shopping as one example. Every click by a consumer on the customer-facing app triggers streams of data across different systems that need to be connected and continuously processed, and it needs to be done because you need to have real-time tracking on delivery ETAs, grocery recommendations and customized promotions, real-time pricing and real-time inventory management as well. So that's one use case. And if you think about banking as another use case, you have fraud detection capabilities, capital inflow, capital trade monitoring. All of these things that happen on the back end of a bank and also the front-end experience with the consumer, all of those need to be -- all of those events and data streams need to be managed in real time. And so those are 2 examples that help underscore what the Confluent opportunity and system is doing. And it's really fundamental to what we call data in motion. It's broadly used across many industries and verticals. And if you think about managing pipelines, micro services, security, fraud detection, Customer 360, the use case is just very long about how we can go in and help companies be the best that they can be.

So truly a planned digital transformation of what we're seeing with the remaking of the consumer experience, the enterprise experience.

For sure. And digital transformation, it's an overused term, but it's definitely a reality. And we play a part in that. If you think about just thematically, the move from batch processing that needs to happen in the old world to real time, Confluent is front and center in that transformation around running businesses in real time. And that is a real core element of digital transformation. And so we play in that theme in a very big way.

Sure. And maybe a little bit on the origins of the company, Kafka, and then where Kafka ends and Confluent begins?

Kafka was created by 3 folks, and they were the 3 factors of Confluent. So Jay and Jun and Neha were engineers at LinkedIn. And they were trying to make LinkedIn run in real time, and they looked at existing off-the-shelf software and services, and they were all falling short. So they ended up creating an open-source software technology, which they named Kafka. They released it out into the wild. And in a very short period of time, it's become the de facto of open-source standard for real-time streaming and event streaming. And as they saw this adoption that was happening in the wild really take off, and today, there are hundreds of thousands of organizations using Kafka. They left LinkedIn and founded Confluent. And at first, the nature of Confluent was to provide professional services and support to have a commercialized version of Kafka. But that was in the very early days. Today, we have a very rich, rich product and feature set for both Confluent platform, which is our on-prem software and more importantly, Confluent Cloud, which is running basically Confluent and Kafka in the cloud on all 3 cloud providers, and we are a cloud-native company now. And I would say that like where Confluent begins and Kafka ends, it's really about being cloud native, complete and everywhere. And let me just take 30 seconds on each of those. So Confluent is the only company that offers true cloud native Kafka solution. It's serverless, it's elastic and customers pay for what they use. And we offer it on AWS, Azure and GCP. From a completeness standpoint, we have the most complete offering in the market. We have over 120 prebuilt connectors. We have an advanced stream processing capability with ksqlDB. And we have enterprise-grade security and data governance features that help customers manage their data securely. And then finally, on the everywhere dynamic, we can use -- and customers can use our products anywhere and everywhere, meaning on-prem, in the public cloud or in the hybrid and multi-cloud environments. So customers don't have to be locked into a single environment or a single cloud vendor. And so those 3 attributes: cloud-native, complete and everywhere, really differentiate our offering from not only Kafka, but from the other offerings that are in the space.

So how do those open-source routes that are in Kafka impact your go-to-market strategy?

Well, it's a great attribute of our business model. The open-source Kafka adoption that happens is very developer-led and it's frictionless. A developer at any company can go to the Apache Foundation and download Kafka, and really start in earnest with a particular project. And that type of viral adoption has spread to, as I said previously, like over -- it's a few hundred thousand organizations that are using Kafka. And that was the original approach for the company to really embrace the developer-led sale. And we're staying true to that as we go forward, but we're also adding an enterprise class go-to-market motion to have a top-down message as well to VPs and executives and the C-level at these organizations that are running Kafka and/or Confluent. And having a developer-led sale complemented by an enterprise class go-to-market organization is a very powerful combination. And it's helping us unlock opportunity that we haven't seen before. One of the things that's powering our go-to-market strategy is the people that we've hired over the past couple of years. So Erica Schultz is our President of Field Operations. She has built out a very strong enterprise class go-to-market team. She recently added Larry Shurtz, who's our Chief Revenue Officer from salesforce.com. And then on the marketing side, we hired Stephanie Buscemi, who was previously the Chief Marketing Officer of salesforce.com as well, and she's come in, and we are really putting together an enterprise class go-to-market machine to complement the developer-led sales. So we have it at both ends of the spectrum, and we believe that is a winning strategy to drive future growth and profitability over the long term.

And so double-clicking then on that viral growth that comes from the developer, is there a certain breakpoint there either in terms of scale or complexity or the addition of more applications? I'm sure the answer is yes, yes, yes, for all of the above, but that really sends someone from Kafka to Confluent?

It really starts with the project that the developer is working on. And as they move from project to platform, meaning they're adding multiple projects in multiple applications, there becomes a level of complexity and primarily security and data governance that you just can't get from the open-source offering, which is why the commercialized version of Confluent with the cloud needs of complete and everywhere themes I talked about are really differentiating factors. And so when you start moving mission-critical workloads into the system, you really need security and data governance and other things around it, and that's where the break point is typically from migrating from open-source Kafka to a Confluent.

Right. And I believe based on conversations in your recent conference call that during COVID, where obviously, companies were looking to save money, you actually had someone churn off of Confluent onto Kafka only to realize they couldn't support it back to Confluent. And while it kind of remains in the net dollar retention base, more concerned, I guess, about why that was the case, why people can't support it themselves, why there's layers of complexity. So not to reveal the customer or anything, but could you help us understand why something like that might happen where people try to save some money in the short run, how it impacts our business in the long run and they've come back?

Well, that one customer in particular that we had mentioned was in a heavily impacted industry and that was impacted by COVID. So they had originally started with Kafka. They moved to Confluent and then their budgets literally got slashed and they were in cost saving mode and they ended up downgrading back to Kafka. Now downgrading back to Kafka doesn't happen very often. But if it does, and the company is still trying to have the level of sophistication and the feature and functionality. They're just not going to get it from Kafka. And they don't have this company in particular, didn't have the time and energy to go back and engineer incremental feature and functionality, which is why they're coming back into the fold for Confluent. So there are going to be some dynamics along the way where we're going to see some companies down shift, but that is a minority instance. The vast majority in the target-rich environment we're talking about is these hundreds of thousands of Kafka organizations that are using Kafka, those are target-rich opportunities for us to go convert over time from open source to Confluent. And we've seen that in our results. Our growth this last quarter actually reaccelerated, and we saw really strong growth with our Confluent Cloud offering, growing 200% year-over-year. Now it accounts for 22% of revenues. And so the opportunity around conversion of open source to Confluent is the far greater opportunity than any customer downgrading from Confluent to Kafka.

Sure. And you mentioned target-rich environment. So maybe we can double-click on how should investors even begin to think about a TAM for your opportunity?

Because we're a category-creating company, there's no third party that you can just say, “Oh, this is what data in motion looks like.” So we've constructed our own TAM. It's a $50 billion TAM today, growing to $91 billion over the next few years. But that $50 billion TAM today is made up before, Gartner defined components app infrastructure, middleware, data quality and integration, BI and analytics. And the fourth one is escaping me, excuse me. And app infrastructure, middleware, data integration, quality tools, BI and analytics and database, obviously, excuse me. And so we take fractions of each of those markets, and we've constructed that $50 billion market. And the way that we've constructed it is we look at the purchasing power and where we're getting budget from out of each of those 4 market opportunities. And we're taking as an example of like a fraction of the database market that's being put into the TAM. We're taking proportionally more app infrastructure and middleware and data integration and data quality tools, those 2 markets -- market segments are more pronounced in our market analysis. So those are the 4 market segments that roll into us. And given just the overall market, anticipated market growth that Gartner has anticipated for those 4 segments, plus our product road map, we anticipate that overall market to grow to about $90 billion in the next few years.

And not dissimilar to some other infrastructure companies having open-source components, you've got the platform, which people can download and you've got the cloud version as well. Can you talk a little about the puts and takes between the 2, where you typically see adoption? And I think in your case, these are not cannibalistic. These are actually somewhat complementary too. So maybe you can articulate what's going on there?

We look at our opportunity and we look at our customer segmentation in a couple of different ways. The first way is we see our enterprise customers and our commercial customers. Our commercial customers really start with Confluent Cloud. And the reason why that's the case is Confluent Cloud is a fully managed hosted offering, and it's very easy for customers to get started. And in the commercial segment, you have customers who don't have the time, energy, budget to have a dedicated engineering team to try to run Kafka. So they come to Confluent and they start with Confluent Cloud. And there's great product market fit there. And so that is that is a dynamic that has helped our Confluent Cloud growth very well. And then on the enterprise side of the house, historically, the enterprise side would start with Confluent platform. So they would download Confluent platform, they would start using it. And what we've seen in those instances is the enterprise customers, when they're moving workloads to the cloud, they are buying Confluent Cloud and it's additive, not cannibalistic to the overall purchasing environment of the company. And so when we see our net expansion rate, net retention rate increase, we're really seeing customers who are adopting both for Confluent platform customers, they're continuing to spend on Confluent platform and they're spending on Confluent Cloud, because to be the central nervous system, you have to be everywhere where the company's data is. The other thing that we see from a feature and functionality standpoint is we are a cloud-first company and -- we're not a cloud-only company, we're a cloud-first company. And we've devoted lots of engineering resources to make sure that our Confluent Cloud offering is on par with Confluent platform. And that's been a journey. And the prior couple of years of development effort for Confluent Cloud has paid off, because now we're effectively at feature parity and we're adding more feature functionality to both products, but really with a focus on Confluent Cloud, and that's starting to pay off, as you've seen in the Confluent Cloud revenue growth, again, greater than 200% last quarter. And also the customer adoption, we make it very easy for customers to swipe a credit card and get going with Confluent Cloud. It's a frictionless onboarding process. And that customer onboarding is great, because once we get our foot in the door, we have our land and expand model that enables us to grow and scale.

And what are the different pricing dynamics between the 2 when you look at the platform versus the cloud version?

Confluent platform is priced on a per node or per server basis. So it's pretty straightforward. And then on the Confluent Cloud side of the house, it's based off of rewrite and storage and anticipated amount of workloads, et cetera. And so we are very much priced -- we're not breaking any new ground around how we price our products at all. Now the rev rec on each of those is different. So Confluent platform when we do a deal, there's a portion that gets recognized upfront and the vast majority gets recognized ratably over the contract term. For Confluent Cloud, the rev rec is based off of consumption. And so the faster that we can get companies ramped onto the consumption curve, the better it will be for both the customer and for us.

And on the per server side, I'm guessing that expands with capacity, with number of projects, geographic location? Or are those the dynamics that would start to scale to more and more servers?

It would, yes. The more applications that get hooked into Confluent platform, the more servers you need and then also geography as well.

Great. And let's dive into the model a little bit in terms of growth and profitability. And it's your first quarter out to shoot. So I'm sure you'll go back to the kind of road show deck relative to how you answered the question, but how should people think about growth and profitability? And then you have this inflection that happened within that last quarter, and you mentioned in your comments earlier, an accelerating growth rate. So maybe you can speak to is that the market is where post-COVID and spending is normalizing? It's hard to even say post-COVID, because who knows where we're going. #1, is that some of the sales capacity additions that you've been adding?

The acceleration of growth that we saw has been a byproduct of a lot of the investments we've been making along the way. And the sales capacity that we brought on a year ago is now becoming fully ramped for sure. And how we manage growth and profitability as you rightly mentioned in our IPO road show, we provided a framework to really help investors understand how we're going to be managing it. And it's not a time-based growth and profitability framework. It's really based off of top line growth. And as we are -- as we have revenue growth above 30%, we're planning on delivering annual operating margin improvement starting in FY '22. And we've laid out both a midterm target model and a long-term target model. In that midterm target model, we're looking at roughly, call it, 5% non-GAAP operating margin and 10% free cash flow margin. And that's over time and is a glide path from like FY '22 as we're going to start to show operating margin improvement starting in FY '22. And then longer term, when growth starts to moderate, we have a long-term operating margin goal of 20% to 25% with free cash flow being above 25%. And we feel good about that model, and it's the type of structure that enables us to invest for top line growth, but also show the fact that we have the ability to drive operating margin improvement, but we're not stretching to get to maximum profitability in the short term. We want to ensure that we have -- that we're investing to capture market share. We're going to let profitability drop to the bottom line along the way to show that annual operating margin improvement. But the TAM is so large and the opportunity is so big and the unit economics support our investment thesis that that growth and profitability framework is really going to help provide the guidepost for us going forward.

Great. And then obviously, aspirational goals relative to where you can grow, it feels like a very big market, but it's going to take some headcount to get there. And this seems to be one of the bigger challenges for a lot of the hyper growers down in the valley. So help us understand hiring, how hiring trends have been, where you're finding people?

There's definitely a war for talent for sure. And depending on the type of role that we're recruiting for, we see a lot of talent coming from software companies, from the sales organizations, like great software companies that are out there. We're able to show our prospective sales candidates that if they want to come to a business that is growing at a much like larger, higher pace than their prior company, they can come to Confluent and really make a difference. From an engineering standpoint, the fact that we're a founder-led company with Jay and Jun is the CTO. Jun has been -- Jun and Jay have been great in terms of attracting candidates from again, software companies, but also from the cloud providers as well. And it's in the ecosystem of highly talented people. They can choose where to go to work. So we are trying to provide an environment where people can -- they believe in the vision of running businesses in real time, being part of digital transformation and being part of a company that's really helping change the way businesses are run. And that's actually one of the biggest reasons why people come to Confluent. They believe in the mission, and they also look at the results and the combination of those 2 things make it an attractive place to work.

Well, Steffan, congratulations, and it seems like a very compelling opportunity. Best of luck to you and thank you for your time today.

Thank you so much, Rob. Take care.

Yes.