Confluent, Inc.

Hi, everyone. Welcome to the Confluent Q1 2023 earnings conference call. I'm Shane Z from Investor Relations, and I'm joined by Jay Kreps, co-founder and CEO, and Stephan Tomlinson, CFO. During today's call, management will make forward-looking statements regarding our business, operations, financial performance, and future prospects. including statements regarding our financial guidance for the fiscal second quarter of 2023 and fiscal year 2023. These forelooking statements are subject to risks and uncertainties, which could cause actual results to differ materially from those anticipated by these statements. Further information on risk factors that could cause actual results to differ is included in our most recent Form 10-K filed with the SEC. We assume no obligation to update these statements after today's call except as required by law. Unless stated otherwise, certain financial measures used on today's call are expressed on a non-GAAP basis, and all comparisons are made on a year-over-year basis. We use these non-GAAP financial measures internally to facilitate analysis of our financial and business trends and for internal planning and forecasting purposes. These non-GAAP financial measures have limitations and should not be considered in isolation from or as a substitute for financial information prepared in accordance with GAAP. A reconciliation between these GAAP and non-GAAP financial measures is included in our earnings press release and supplemental financials, which can be found on our Investor Relations website at investors.confluent.io. Please also know that we will host Investor Day 2023 in New York City on Tuesday, June 13. To join in person, please contact IR for the registration information. The program will also be webcast live on our IR website beginning at 1 p.m. Eastern Time. With that, I'll hand the call over to Jay.

Thanks, Shane. Good afternoon, everyone. Welcome to our first quarter earnings call. I'm pleased to report a strong first quarter with results once again exceeding all of our guided metrics. Total revenue grew 38% to $174 million. Confluent Cloud revenue grew 89% to $74 million. and non-gap operating margin improved 18 percentage points. These results are a testament to the mission-critical nature of our platform, our strong TCO value proposition, and the solid execution of our team despite a volatile macroeconomic environment. Over the last year, Confluent has continued to show very strong gross retention, even through a substantial change in the economic environment, including abrupt changes in interest rates, an economic slowdown, a significant drop in funding for private tech companies, and the recent challenges in banking. Environments like this show which products have true durability and which are simply fads or nice to have. I wanted to take the opportunity to explore what drives this durability for Confluent. The first factor is that Confluent serves mission-critical custom software applications. These are high-value projects that customers invest their expensive software engineering resources in. Because of this high investment, the applications tend to target the most valuable use cases and last a long time. We often hear from customers about applications lasting not just years but decades. Naturally, the underlying data platforms used by these applications tend to persist along with them. The second factor is that unlike a database, Confluent isn't just a platform for one app, but acts as an interchange between multiple teams and applications. This is inherent in the core use case of the technology, publishing streams of data so multiple other applications and teams can consume those streams. This kind of multi-team, multi-application platform gets more and more sticky as it gets more heavily used and displays very different dynamics than the platform that each application can choose or abandon independently. The reason for this is very obvious. The migration to another platform would require a coordinated effort across many teams all at once, which becomes harder and harder to imagine as there are more and more producers and consumers building against the streams of data in the platform. By analogy, think of the cost of switching to a new incompatible telephone system. The challenge isn't buying a new phone, it's getting all your friends to do the same thing at the same time so you can still call them. This pattern of cross-team interaction and cross-application interaction is a unique and positive characteristic of data streaming and isn't shared by most other data systems. The third factor of our durability comes from the inherent TCO advantage of our cloud offering. I'm going to dive into this factor at length, as it's critical to understanding the deep technical mode that Confluent has built. Initially, it might seem that a customer, when faced with budgetary pressure, would want to migrate off of the cloud data service back to open source. Open source, after all, is free. Why isn't this happening? It is no doubt in part due to the comprehensive features and functionality our platform offers. We've talked about this at length in prior earnings calls, but you would imagine that customers might choose to forego better functionality when faced with severe budget pressure. Why isn't this happening? The answer to this may be somewhat counterintuitive. A cloud data service has the opportunity to not just be better than an open source offering, but also be meaningfully cheaper. To understand this, it's important to understand what drives the cost structure of self-managed data systems. This is an analysis we do frequently since we offer both a self-managed software offering and a cloud service. We've worked with thousands of customers, both on-premise and in the cloud, to analyze and compare the cost structure of open source self-managed software and a fully managed cloud service. I'll walk through this analysis and show where our substantial TCO advantage comes from. There are two easily quantifiable areas of spend around a self-managed software system. The first is the cloud infrastructure for running Kafka. This spans compute, storage, networking, and any additional tooling needed to keep Kafka up and running smoothly. These costs tend to increase rapidly, eventually representing the largest portion of cost when usage is at scale. The second is the software engineers and operations people responsible for configuring, deploying and managing Kafka. Like any data system, and particularly like any large-scale distributed data system, Kafka requires full-time staff to manage it. And the cost of these individuals is significant, particularly for people managing Kafka. A 2022 study from Dice.com listed Kafka as the fifth highest paying technical skill. That's great for engineers doing Kafka DevOps, but not so great for companies hiring teams with the experience to operate Kafka as a production data system. These costs will scale up with the usage of the system. The larger tech companies that have built significant streaming platforms around open source Kafka have teams of 20 or more engineers attending to their data streaming platform. It's not inevitable that a cloud service will improve on these costs. After all, if we were running the same open source software and operating in the same way, our costs would be no different from theirs. However, Confluent has rethought the problem from the ground up and has built a deeply differentiated stack that's able to drive compelling savings in both of these areas. I'll start with infrastructure savings. Confluence Cloud has rethought and reimplemented the core protocols for data streaming in a way that is built natively for the cloud to drive significant savings. I'll enumerate a few of these. First, multi-tenancy. Multi-tenancy is the key to SaaS margins, but many investors don't realize that the majority of data systems in the cloud, especially services offered by the cloud providers around open source, aren't actually capable of multi-tenant operations. Our offering runs multi-tenant for the vast majority of customers. This is a very significant re-architecture, touching virtually every tier of the stack, allowing us to pool our thousands of customers on shared infrastructure to drive higher utilization and a serverless experience. Next is elasticity. Our intelligent tiering of data between memory, local storage, and object storage helps manage the costs of stored data and allows instant scalability, enabling higher utilization of compute resources. Next is our facilities for sophisticated data balancing. Confluent uses the real-time performance data of our customer base to intelligently optimize the placement of data and the routing of traffic to maximize performance, utilization, and cost. Finally, networking and data replication. Confluent has optimized the replication of data and the networking stack routing data to drive the cost of networking, the most expensive aspect of cloud operations for streaming. In addition to this, at-scale discounts targeting our unique workload help reduce spend. Confluent is now at a larger scale than most our customers, and we are able to drive discounts targeted to our workload. These significant architectural advantages combined with thousands of small continual optimizations at every layer of the stack help drive our significant cost advantage in operations. Those who have watched our gross margins progress over the last few years have observed this continual progress at work as we've continually driven additional technical improvements and improved utilization for multi-tenant operations as cloud has become a bigger and bigger portion of our revenue base. Next, I want to discuss the advantage that comes from our innovations in at-scale operations. Confluent operates our fleet with a set of tools and practices vastly different from our customers. First, our infrastructure improvements do double duty here. The improvements I outlined previously drive vastly higher utilization, and hence we manage an order of magnitude fewer servers than we otherwise would. But the big difference in our operations is that it is done by software, not people. We orchestrate rollouts with a sophisticated feedback-driven system that allows safe rollouts across thousands of machines and hours. We are able to automatically detect and remediate the kinds of rare problems that become common at scale. And we have real-time monitoring and checks for every aspect of the integrity of the system. These capabilities provide us with a dramatic advantage in the cost of human management. For example, in our Kafka service, the centerpiece of our offering, Confluent has less than five Kafka engineers on call for our tens of thousands of production Kafka clusters. This gives us a cost structure for operations that we believe is over a thousand times better than our customers. The combination of these savings across infrastructure and operations allows us to offer our service at a price point that makes our product not just better, but also cheaper. We think that's a winning combination, especially in times like these. We've gone to great lengths to ensure we are TCO positive across the customer journey, from their first use case to large-scale central nervous system. We believe this TCO advantage is not just a factor in driving retention, it will also help us drive far greater monetization of the user base of open source Kafka. This is a point often missed by investors looking to make analogies from on-premise open source models to the cloud, which in fact are quite different. Traditional on-premise open source business models offer a premium product, better features for more money. As a result, they typically are able to capture only a fraction of the open source users as paying customers. A cloud product, however, isn't just replacing the free software. It's also replacing the expensive infrastructure and people costs. This is driving a general mindset shift among software engineers and IT departments who are increasingly looking for managed services first, trying to avoid ongoing operations wherever possible. As this shift takes place, we think there is an opportunity to grow from our modest penetration into the hundreds of thousands of open source Kafka users to a much more complete coverage. This higher conversion rate is already apparent, despite being a much newer offering and despite the much higher bar of maturity for a cloud service. Today, Confluent Cloud is already used by more than six times as many customers as Confluent Platform, our self-managed software offer. In fact, we are so confident in this value proposition that we invite prospects to come and take an assessment where we jointly do analysis with them to prove to them that choosing Confluent will be a more economical decision than self-supporting open source Kafka on their own. A great example of the TCO benefits of Confluent for a customer in the earlier stages of the customer journey is a SaaS-based billing startup that helps companies scale their consumption, subscription, and hybrid pricing models. This customer's data and billing platform is built on Kafka to compute usage and invoices in real time for millions of end customers. and is scaling rapidly to accommodate expected growth. But they quickly found that managing open-source Kafka was costly and diverted expensive engineering talent from innovation to low-level infrastructure management. With Confluent Cloud, they're able to reallocate at least 60% of their engineers' time managing Kafka to delivering new product innovation without over-provisioning infrastructure. As a result, they've reduced deployment times from months to weeks while reducing the total cost of managing open-source Kafka. On the other end of the spectrum is a large Q1 deal with a top 10 U.S. bank. Confluent powers thousands of this customer's applications across hundreds of teams, spanning digital, fraud, payments, analytics, and more. The bank is now going all in on the cloud, undertaking a massive cloud migration to operate more efficiently and introduce new innovation to their customers faster. To accelerate their cloud migration, they closed a seven-figure Confluent Cloud deal to connect their data from on-premise environments to the cloud. Despite the turmoil in the banking industry, this customer accelerated their cloud transformation with Confluent, another example of the many use cases that make data streaming a critical tool for modern organizations, even amid macro uncertainty. We are very excited about the opportunity for similar expansion in other customers as the financial services sector moves to the cloud. In closing, the significant product and cost advantages of our platform put us in a strong position to tap into the hundreds of thousands of users of Kafka with a product that is more than 10 times better and meaningfully cheaper than open source. These dynamics put us in the enviable position as the leader of a $60 billion market opportunity. I look forward to seeing many of you at our Investor Day, where among other things, we'll dive deeper into the significant product innovation driving the success of our platform. With that, I'll turn the call over to Stefan to walk through the financials.

Thanks, Jay. We kicked off fiscal year 2023 beating our guided metrics, delivering high revenue growth and strong margin improvements in the first quarter. These results demonstrate another quarter of consistent execution from our team in a tougher economic environment. Turning to the results, RPO for the first quarter was $742.6 million, up 35%. Current RPO, estimated to be 64% of RPO, was $477 million, up 44% and accelerated from last quarter. Growth in RPO, while healthy, was impacted by a decline in average contract duration, additional budget scrutiny which elongated our deal cycle, and a tough comp against the eight-figure TCV deal closed a year ago. Moving on to NRR, starting this fiscal year, we moved to consumption-based NRR for Confluent Cloud, which provides better alignment and insight to the underlying consumption trends of our cloud business. Total NRR for Q1 was above 130%, and gross retention was above 90%. NRR for both cloud and hybrid customers remained higher than the company average, and NRR for cloud was the highest. We added 160 net new customers, ending the quarter with approximately 4,690 total customers, up 14%. The growth in our large customer base continued to be robust, driven by use case expansion. We added 60 customers with 100K or more in ARR, bringing the total to 1,075 customers, up 34%. These large customers contributed more than 85% of total revenue in the quarter. We also added eight customers with $1 million or more in ARR, bringing the total to 135 customers, up 53%. We've included historical results for NRR and customer count relating to the ARR methodology change in our IRR presentation on our website. Turning to the P&L, total revenue grew 38% to $174.3 million. Subscription revenue grew 41% to $160.6 million and accounted for 92% of total revenue. Within subscription, Confluent Platform revenue grew 16% to 86.9 million and accounted for 50% of total revenue. Confluent Platform outperformed relative to our expectations and was driven by a strong performance in the public sector vertical. Confluent Cloud exceeded 50% of total new ACV bookings for the sixth consecutive quarter. Cloud revenue grew 89% to 73.6 million, representing a sequential increase of 5.3 million, exceeding our guidance. Cloud accounted for 42% of total revenue compared to 41% last quarter. The modest increase in cloud revenue mix relative to historical trends was due to the outperformance in Confluent Platform in the quarter. Turning to the geographic mix of revenue, revenue from the US grew 32% to $103.9 million. Revenue from outside the US grew 49% to $70.4 million. Moving on to the rest of the income statement, I'll be referring to non-GAAP results unless stated otherwise. Total gross margin was 72.2%, up 250 basis points, and modestly above our target range of 70 to 72%. Subscription gross margin was 77.5%, up 200 basis points. Our healthy gross margins were driven by the continued improvement in the unit economics and scaling of our cloud offering, offset by a continued revenue mix shift to cloud. Turning to profitability and cash flow, operating margin improved 18 percentage points to negative 23.1%, representing our third consecutive quarter of more than 10 points in improvement. Q1 operating margin was driven by our revenue outperformance, which we let flow through to the bottom line and our continued focus on driving efficiency across the company. We drove improvement in every category of our operating expenses with the most pronounced progress made again in sales and marketing, improving 11 percentage points. Net loss per share was negative nine cents using 291.9 million basic and diluted weighted average shares outstanding. fully diluted share count under the Treasury stock method was approximately $350.1 million. Free cash flow margin declined one percentage point to negative 47.5%. As expected and discussed on our last earnings call, free cash flow in Q1 was negatively impacted by charges related to our restructuring, the IMROC acquisition, ESPP, and our corporate bonus payout. We ended the fourth quarter with $1.85 billion in cash, cash equivalents, and marketable securities. Now I'll turn to our outlook. The demand environment for data streaming and the solutions we're offering to the market continues to be robust, even in a choppy macro environment where it's taking longer to close deals. Mid last year, we were early to flag the increase in the volatility of the business environment and incorporate those dynamics into our outlook. Looking out to Q2 and the balance of the year, we're expecting to deliver on the commitments we outlined on our last call. We are assuming there's a continuation of additional budget scrutiny and there'll be no improvement in the business environment through the remainder of this year. We'll continue to proactively allocate capital to drive efficient growth and are managing the rate and pace of investments. For the second quarter of 2023, we expect revenue to be in the range of 181 to 183 million, representing growth of 30 to 31%. Cloud sequential revenue add to be in the range of 7.5 to 8 million. we continue to expect cloud sequential revenue add to increase every quarter for the rest of 2023. Non-GAAP operating margin to be approximately negative 16% and non-GAAP net loss per share to be in the range of negative 8 cents to negative 6 cents using approximately 297 million weighted average shares outstanding. For the full year 2023, we expect revenue to be in the range of 760 to 765 million, representing growth of 30 to 31%. non-GAAP operating margin to be approximately negative 14% to negative 13% and non-GAAP net loss per share in the range of negative 20 cents to negative 14 cents using approximately 300 million weighted average shares outstanding. Additionally, for Q4 23, we expect to deliver 48 to 50% of total revenue from cloud and achieve breakeven for non-GAAP operating margin. The timing for free cashflow breakeven will roughly mirror that of our operating margin. In closing, I'm pleased with a strong start to fiscal year 2023. While the macroeconomic environment remains challenging, we're continuing to deliver innovation and value to our customers, which would not be possible without the excellent performance of the members of our team. Looking forward, we remain focused on driving efficient growth and building a profitable business. Now, Jay and I will take your questions.