Confluent, Inc.

Hi everyone, welcome to the Confluent Q3 2022 Earnings Conference Call. I'm Shane Z from Investor Relations, and I'm joined by J. Krabs, 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 outlook for the fiscal fourth quarter of 2022, fiscal year 2022, and fiscal year 2023. These four latent statements are subject to risks and uncertainties, which could cause actual results that differ materially from those anticipated by these statements. Further information on risk factors that could cause actual results to differ is included in the most recent Form 10-Q filed with the SEC. We assume no obligation to update these statements after today's call except as required by law. As a reminder, certain financial measures used on today's call are to express on a non-GAAP basis. We use these non-GAAP financial measures internally to facilitate analysis of 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 price release and supplemental financials, which can be found on our investor relations website at investors.confluent.io. And with that, I'll hand the call over to Jay.

Thanks, Shane. Welcome everyone to our third quarter earnings call. I'm pleased to say that Confluent delivered another strong quarter with results exceeding the high end of all our guided metrics. Total revenue grew 48% year over year to 152 million. Confluent Cloud continued to be the fastest growing area of our business with revenue up 112% year over year to 57 million. We are also continuing to increase our operating leverage with a 14 point year over year improvement in non-gap operating margin. Despite the pressure from a more difficult macroeconomic backdrop, we think these strong and consistent results are testament to our ability to drive durable and efficient growth. The rise of data streaming is one of the most fundamental shifts in the world of data. Soon it will be hard to imagine a time when companies didn't have ubiquitous access to real-time data and ability to react to it instantaneously. Apache Kafka has emerged as a de facto standard of this movement. Hundreds of thousands of organizations, including more than 75% of the Fortune 500, use it every day for critical use cases across their business. But there are also incredible things happening within the larger data streaming ecosystem, including an extraordinary number of new use cases and technologies. In October, we hosted Current 2022, the first ever industry event for data streaming. It put Confluent at the center of the ecosystem and brought together over 4,000 attendees, hundreds of ecosystem partners, and more than 50 sponsors to learn, network, and explore the future of data streaming. In today's call, I want to give a view of this emerging data streaming category and explain how it relates to some of the legacy technologies it replaces. We believe data streaming represents a major new data platform that has the potential to be as broad in scope as databases have been. However, many of the legacy products in the space have been quite limited in adoption and scope. How can we square the skyrocketing adoption of Kafka, rapid success of Confluent, and expansive view most technologists have about streaming with the more limited success previous tools in the space have had? To answer that requires a brief excursion through the legacy technologies that Confluent displaces. Today, we could broadly think of three major estates of software and data. First, custom applications that businesses built from scratch and the operational databases that support them. Second, the hundreds of SaaS applications like Salesforce and Workday that address common yet critical needs for business functions. And finally, analytic systems that improve decision-making. Each of these areas has grown a set of ad hoc fragmented tools for integration and a primitive kind of data in motion. Let's review these previous generation of tools and then discuss how it is displaced by data streaming. Custom applications communicate with message queues, database change capture products, ad hoc APIs, and enterprise service buses. These technologies fit the real-time requirements of application workloads, but were impossible to scale, low level, and labor intensive to work with and limited in their application. SAS applications, meanwhile, grew their own set of tools, including proprietary application integration platforms, business process management tools, and bulk file transfers. These tools achieved some success in their domains, but were again limited in scalability, unable to handle complex data transformations or logic, fragile to work with, and disconnected from modern development platforms. Finally, businesses drive data into analytical systems primarily through a combination of legacy ETL or ELT tools, as well as pre-processing and data lakes. These tools support rich transformations but are stuck with slow batch processing that makes the data hours or days late by the time it arrives. These tools are all flawed in different ways. They are either slow and batch-oriented, non-scalable, require significant maintenance from centralized teams, or are unable to work with more sophisticated data and processing. But more importantly, the critical problem is that in a modern company, all three of the major states of data must be highly connected. The custom applications must interconnect with the off-the-shelf applications and the analytics applications. Consider a simple example of a modern retailer. Data about what is selling is needed by dozens or hundreds of custom applications, SaaS applications, and analytics platforms. Having to create point-to-point plumbing across a dozen different tools for each use case is simply not a feasible or scalable approach. Data streaming works by rethinking this problem from the ground up. Whereas the previous generation of tools were ad hoc and limited to a narrow domain, data streaming starts with a broad foundational approach. It takes the core architectural concepts of a database, such as a ledger of changes, transactional guarantees, horizontal scalability, and easy dynamic data transformations, and translates them from the world of data at rest to data in motion. We believe the result is something vastly more general and powerful than any of the previous solutions. It consolidates the fragmented ecosystem of integration tools with a solution that can achieve all the capabilities each of the previous tools could not. It's real time, it's horizontally scalable, it's transactionally correct, and it provides an open, programmable platform. This provides a solution that is better in each of the domains than the previous generation of systems. But its key strength is that it treats data in a reusable manner. A single stream of data can feed all use cases, whether custom applications, SaaS applications, or analytics stores. This allows vastly more simplicity and reuse than previous solutions. But the power of data streaming is well beyond the integration technologies of yesterday. Because it starts with an open, programmable foundation, it is not limited to building pipelines. The stream processing capabilities in Kafka allow any application logic, whether for data transformation or applying smart business rules. This is what has made Confluent a foundation for developing real-time applications that react to the stream of business events continuously. The real-time applications that organizations can build with Confluent are limitless. It includes fraud detection, fleet management, customer 360 platforms, real-time inventory management, and many more. Thus, while each of the legacy technologies was limited in scope and adoption, data streaming has much broader potential as it both consolidates this landscape and expands well beyond it. Indeed, considering the three estates of data I mentioned before, the custom applications, SaaS applications, and analytic systems, it's worth noting that each of these is a repository of stored data, that is, data at rest. However, equally important is the data in motion that Confluent is providing the underlying platform and foundation for. We believe this data in motion represents a fourth estate of data which will be equally critical to the operation of a modern business. This background provides a good framework for contextualizing a few exciting product releases from Confluent. While Confluent has revolutionized the underlying infrastructure for integration with data streaming, some of the legacy tools still had one advantage. Whereas Confluent was primarily a programmatic tool, many of the legacy tools were low-code or no-code GUIs, which, while limited in power, were easy to learn and use. This is what makes me so excited for our recent announcement of Stream Designer. Stream Designer brings a dead simple UI for building pipelines, familiar from other integration tools, but it does it on top of our modern data streaming platform. Stream Designer is the first drag and drop visual builder to rapidly build and deploy streaming pipelines natively on Kafka. It integrates with the core capabilities of our platform, Kafka, Connect, stream processing and governance to make building mission critical data pipelines simple. Stream Designer also makes deploying streaming data pipelines accessible to more people throughout an organization, including people less familiar with Kafka. Users with different skill sets don't have to give up the power of the underlying infrastructure either. They can seamlessly switch between the UI, code editor, and a command line interface to quickly and declaratively build data pipelines. Back in 2021, we mentioned the wide variety of up-the-stack use cases we are uniquely positioned to address. Stream Designer represents our first step in that direction and lets us serve the set of use cases broadly characterized as data pipelines. This isn't the end of the story, though. By having one layer where data flows throughout the organization, this enables Confluent to add additional value. As data streaming use cases grow and real-time data flows more freely across the business, it's critical that this data can easily be discovered, understood, and governed in real-time. Stream Governance Advanced does exactly that. The newest capability in our Stream Governance suite makes governing mission-critical workloads at any scale more reliable with a 99.95% uptime. And the ability to add user-generated business context makes it easier to find the data that's needed to power new use cases. Now customers can more easily scale the power of data streaming from individual projects to central nervous systems for their business. Taken together, Stream Designer and Stream Governance Advanced are powerful examples of the fundamental paradigm shift occurring with data streaming. They also show our unique ability to build out-of-the-box solutions on top of our platform that reach a broader set of customers, accelerate their adoption, and grow our addressable market over time. What was once thought of as different software categories are today consolidating into one much more general, powerful, and valuable market – data streaming platforms. Next, I'd like to touch on something I mentioned in my opening remarks. Confluent is set up to drive durable and efficient growth. We've seen fantastic momentum to date, but what's most exciting is our approximately $60 billion market opportunity in front of us. We've started to demonstrate both the breadth and depth of this opportunity. The breadth is captured by the massive adoption of Kafka, which provides a large installed base for new customer acquisition through self-service on Confluent Cloud. This is foundational to our strategy of converting open source users and landing Greenfield customers in high volume. We've also shown the depth of the value of these opportunities with our ability to expand rapidly after we land a customer. This is evident in our best-in-class large customer ratio, where 22% of our customers have an ARR of 100K or more. But at the same time, we believe there are strong expansion opportunities with our largest customers still, including those with ARR of 10 million or more, particularly as we make it easier to connect and consume data throughout the platform. We also continue to benefit from the secular move to the public cloud, particularly in an environment where there's increased pressure for organizations to run their businesses more efficiently. Our cloud native platform significantly simplifies operational complexities and reduces total cost of ownership, saving valuable engineering resources allocated to manually building and managing lower level infrastructure tools like Kafka. A new Q3 customer is a great example of the cost savings of Confluent Cloud. Armus is a leading cybersecurity platform for connected devices that enables its customers to discover and secure their IT, cloud, IoT, and edge assets in real time. Today, Armus tracks over 3 billion devices for its customers, from printers, laptops, and mobile devices to connected medical devices and factory equipment. Kafka is a central part of their business, responsible for ingesting data bidirectionally from billions of devices to provide real-time protection and policy enforcement. But with the rapid growth of its business and the proliferation of connected devices, the cost and overhead of managing open-source Kafka was unwieldy. This quarter, Armus turned to Confluent Cloud for a cloud-native Kafka service that can scale alongside its business. Confluent will be the central nervous system for Armus' data streaming platform, managing data from billions of devices in real-time. all while enabling them to reassign 70% of the expensive engineering talent previously focused on Kafka to projects that move the needle for the business. The durability of our growth is also reflected in our ability to rapidly expand once we land a customer. A great illustration of this dynamic is one of our largest Confluent Cloud customers. As one of the highest trafficked job websites in the world, this customer sends more than 4.5 gigabytes per second through Confluent Cloud every day. Kafka was a no-brainer choice to start their data in motion journey, but they soon found themselves spending too much developer time managing Kafka. Our commercial relationship started with a small deal in 2020 for a single use case in a single business unit. As that pilot proved successful, we landed a $1 million plus deal that expanded Confluent Cloud to more business units across the company. Inspired by our platform's extensive capabilities and an accelerated move to the cloud, our customer reimagined their data architecture in 2021, leading to our first multi-million dollar deal with this customer. As Confluent became a critical unified data layer across the organization, their annual spend surpassed $8 million. As you can see, what often starts as a small land for a single use case can rapidly expand to a large customer in just two years time. But we believe we are still at the beginning of a great partnership as use cases and streaming data become more pervasive throughout the organization. Turning to efficiency. On a year-over-year basis, we improved non-gap operating margin by 14 points in Q3 and 8 points in Q2. We are pleased with the substantial margin improvements we've driven this quarter and excited that there are significant opportunities to continue these improvements. We're making substantial progress in creating strong connective tissue between our product-led and enterprise sales motions to help accelerate our customers' time to value. And we are still early in leveraging our partner ecosystem and bringing to bear a solution and industry focus. As an eight-year-old company, we believe our go-to-market model will drive differentiation and separation from our competitors, which will generate greater leverage and efficiency in our model over time. Looking forward, we remain confident in our ability to achieve positive non-gap operating margin when we exit Q4 2024, Confluent's 10-year mark as a company, a profitability timeline comparable to many of our successful high-growth peers. And finally, we're pleased to announce that Ray Perez has joined Confluent as our Chief Customer Officer. Ray joins us from New Relic, where he most recently held the role of CCO, leading the Solutions Engineering, Solutions Architecture, Enablement, and Expert Services teams. We'd also like to thank Roger Scott for his leadership and impact while at Confluent and wish him the best in his next chapter. To summarize, we have entered the data streaming era. Kafka is at the center of this movement, but represents just the foundation of the emerging platform. Our recent releases of Stream Designer and Stream Governance are great examples of this and show how Confluent is moving up the stack to help our customers connect, process, store, govern, and share data from across their businesses. We believe this model will be the basis to drive continued durable and efficient growth for our business and allow us to capture the lion's share of our large market opportunity ahead. With that, I'll turn the call over to Stefan to walk through the financials.

Thanks, Jay. In Q3, we beat our revenue and bottom line guidance as we've done in each quarter since going public. Key highlights include strong top-line growth, including the largest increase in sequential revenue add for Confluent Cloud, robust expansion of large customer cohorts, which translated to another quarter of greater than 130% net retention rate, and a 14-point year-over-year improvement in non-gap operating margin. These strong results reflect that our market-leading data streaming platform continues to resonate with customers despite a cost-conscious environment. and we continue to demonstrate our ability to drive durable growth and improve efficiency and profitability. Turning to the detailed results, I like to note all comparisons are on a year-over-year basis unless otherwise noted. RPO in the third quarter grew 72% to $663.5 million. Current RPO, estimated to be 62% of RPO, was approximately $408.2 million, up 59%. Total revenue grew 48% to $151.7 million. Subscription revenue grew 50% to $138.7 million and accounted for 91% of total revenue. Within subscription, Confluent platform revenue was $81.8 million, up 25%, and accounted for 54% of total revenue. Confluent Platform remains an important component of building a central nervous system for our customers and continues to drive upsell and cross-sell opportunities for Confluent Cloud. And we saw another record quarter of sequential revenue add for Confluent Cloud, up $9.9 million sequentially and up 112% to $56.9 million, representing 38% of total revenue compared to 26% of revenue a year ago. Cloud accounted for more than 60% of new ACV bookings, and Q3 marks the fourth consecutive quarter where Cloud accounted for greater than 50% of new ACV bookings. As cloud accounts for a larger share of new ACV bookings, Confluent platform will have lower ACV and less upfront revenue. Confluent cloud momentum was driven by our strong product advantage, our continued focus on decreasing time to value, and use case expansion, leading to robust consumption across a broad spectrum of verticals. Additionally, customers run their operational workloads on Confluent, and these workloads are directly responsible for driving the core operations of our customer's business, which reflects the mission criticality and resiliency of our data streaming platform. Turning to the geographic mix of revenue, Revenue from the US grew 44% to $95.1 million. Revenue from outside the US grew 56% to $56.6 million. On our last earnings call, we called out some deals that were taking longer to close in Q2 due to additional scrutiny in pockets across geographies. While this dynamic has continued, I'm pleased to report that the vast majority of those deals were closed as expected in Q3. Turning to customers, we added 120 net new customers, ending the quarter with approximately 4,240 total customers, up 40%. We're pleased with the improved sequential growth despite the continued impact of paywall removal. This strategic move removed the payment friction for developers to test drive Confluent, and it continues to have a positive effect for new signups. As a reminder, we expect the impact of total customer count will take a few quarters to work through, and new pay-as-you-go customers do not have a material contribution to our revenue in any given quarter. The growth in our large customer base continue to be robust. Customers with $100K or more in ARR grew 39% to 921, representing 22% of our total customer count, and these customers contributed more than 85% of total revenue in the quarter. customers with 1 million or more in ARR grew 53% to 113. As discussed at current, we have a growing number of customers with 5 million plus and 10 million plus in ARR, and we see strong expansion opportunities across our customer base, including these two largest customer cohorts. Dollar-based net retention rate in the quarter remained above 130% for the sixth consecutive quarter, driven by 90%-plus gross retention and strong expansion across platform and cloud. Importantly, NRR for cloud continue to be higher than the company average and NRR for hybrid customers remain the highest. A period of tough economic times is when the real durability of demand for our product is tested. And we think our consistent and strong NRR is a testament to our TCO advantage and the mission criticality of our use cases. Moving on to gross margins, I like to note that I'll be referring to non-GAAP results unless stated otherwise. Total gross margin was 71% and subscription gross margin was 76.9%. Our focus on improving the unit economics of our cloud offering continued to pay off, driving another quarter of healthy gross margins despite a continued revenue mix shift to Confluent Cloud. In the near term, we anticipate total gross margin to fluctuate near our mid-term target of approximately 70%. Turning to profitability and cash flow, operating margin improved 14 percentage points to negative 28%. The improvement was primarily driven by improved sales and marketing efficiency and our balanced approach of investing in the highest ROI projects while continuing to proactively manage spend across the organization. Net loss per share was negative 13 cents using 282.3 million basic and diluted weighted average shares outstanding. Free cash flow margin was negative 30% in line with our expectations. As discussed last quarter, we changed our annual bonus structure by moving 13 and a half million payout into Q3 22 from Q1 23. The bonus payment had a negative impact of approximately 9 percentage points on free cash flow margin in the quarter. And we ended the third quarter with $1.94 billion in cash, cash equivalents, and marketable securities. Now I'll turn to our outlook. We are raising our revenue and bottom line guidance for Q4 in FY22. The magnitude of the raise incorporates what we've experienced since June, where deal cycles are elongated due to the additional scrutiny on budget approvals. Our forecast assumes that this macro dynamic persists in Q4. For the fourth quarter of 2022, we expect revenue to be in the range of 161 to 163 million, representing growth of 34 to 36%. Confluent Cloud sequential revenue add to be in the range of 9.8 to 10 million. non-GAAP operating margin to be approximately negative 28%, and non-GAAP net loss per share to be in the range of negative 16 to negative 14 cents, using approximately 286 million weighted average shares outstanding. For the full year 2022, we expect revenue to be in the range of 578 to 580 million, representing growth of 49 to 50%. non-GAAP operating margin to be approximately negative 32%, and non-GAAP net loss per share in the range of negative 65 to negative 63 cents, using approximately 280 million weighted average shares outstanding. Looking ahead, while we're still in the midst of annual planning, I'd like to provide a preliminary outlook for next year. For the full year of 2023, we expect revenue to be in the range of 760 to 770 million, Incorporated in the preliminary revenue outlook is a negative impact of 12 to 17 million, stemming from the increased scrutiny on deal approvals, and we're assuming that the overall macro dynamic that we see today will continue to persist throughout next year. And we expect non-GAAP operating margin for the full year 2023 will be approximately negative 21%. We will continue to invest with discipline, focusing on the highest ROI segments of our business to drive efficient and high growth. We'll monitor and course correct if the macro conditions change materially, and action is warranted to ensure we meet our margin targets. In closing, our strong Q3 results are another proof point of our ability to drive high growth with increased efficiencies. The demand environment for data streaming remains strong despite the macro dynamics around deal approvals. Our Confluent Cloud momentum reflects our TCO value proposition, the differentiation of our use case driven consumption model, and the mission critical nature of our cloud native platform. Looking forward, we're well positioned to drive efficient digital transformation with high ROI for our customers. Now, Jay and I will take your questions.