Confluent, Inc.

Hello, everyone. Welcome to the Confluent Q1 2024 Earnings Conference Call. I'm Shane Zee from Investor Relations, and I'm joined by Jay Kraps, co-founder and CEO, and Rohan Sivaram, CFO. During today's call, management will make forward-looking statements regarding our business, operations, sales strategy, market and product positioning, financial performance, and future prospects. including statements regarding our financial guidance for the fiscal second quarter of 2024 and fiscal year 2024. These forelooking 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 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 data 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 price release and supplemental financials, which can be found on our IO website at investors.confluent.io. And finally, once we have concluded our earnings call, we will post the Confluent earnings report to our IL website. The report is a single PDF which contains our earnings infographic, one-pagers on our technology, our prepared remarks, and slides from today's earnings call. Going forward, we plan on publishing the report at the end of our quarterly earnings call. With that, I'll turn the call over to Jay.

Thanks, Shane. Good afternoon, everyone, and welcome to our first quarter earnings call. I'm happy to report we had a strong start to the year, exceeding the high end of all guided metrics. Total revenue grew 25% to $217 million. Confluent Cloud revenue grew 45% to $107 million, which now accounts for the majority of our subscription revenue and remains our fastest growing offering. Non-gap operating margin improved 22 percentage points, our fourth consecutive quarter of more than 20 points in improvement. These results reflect our team's strong execution amid a still uncertain but stabilizing macro environment. In Q1, we launched our consumption transformation. We oriented our sales compensation for cloud towards incremental consumption and new logo acquisition. We rolled out new systems, metrics, and measures and made pricing adjustments to reduce friction in landing new customers. It remains early days, but we are encouraged by the strong promising signals of our consumption orientation, particularly around new customer acquisition and stabilization of consumption trends. With an increased focus on new logo growth, we added 160 customers to our total customer count, our largest sequential growth since Q1 23. We not only increased the volume of customer additions, but we're better able to target high potential customers, increasing the quality of our customer ads as well. We recently hosted Kafka Summit in London and Bangalore. Kafka Summit Bangalore was the first ever Kafka Summit in APAC. These events are a great illustration of their tremendous growth and innovation happening within the data streaming category. Between the two events, we had more than 7,000 people joining us in person or registered virtually, spanning startups, enterprises, and everything in between, including organizations like Apple, Bloomberg, CERN, ING, Stripe, Uber, and many others. Our relentless pace of product innovation was on full display with 15 major customer-facing features and price and performance optimizations announced across both events, including the general availability of Flink and early availability of a powerful new feature we call TableFlow. TableFlow makes all the data streams that flow through Confluent Cloud available as structured tables in cloud object storage using an open table format called Apache Iceberg. Let me provide a little background on what this means and why it's so powerful. Historically, data in the analytics and data warehousing world has existed in closed systems that trapped their data inside a walled garden. As the complexity of the analytics world has grown, this has led to a mishmash of data warehouses, data lakes, AI products, and reporting systems. This created lots of value for technology vendors, but created yet another data silo for the end user. However, over the last five years, a trend has emerged of standardizing around open data formats and metadata on top of cloud object storage. The rise of cheap cloud object storage like S3 means another path is possible. Instead of fragmenting data across various analytical systems, the tables of data can be shared across systems. Apache Iceberg has arisen as the de facto standard for these open analytic tables on top of cloud object storage. Iceberg is an open source project that has near universal support across the open source systems like Apache Spark and Flink, as well as the data warehousing and data lake house world, including products like AWS Athena, Redshift, Google's BigQuery, and Snowflake. TableFlow is more than just a connector. Already Kafka and Confluent are one of the most common feeds of data into the analytics system. But with TableFlow, we can make that integration far deeper. Quora, our cloud-native Kafka implementation, already heavily relied on cloud object storage for storing the streams of data in Confluent Cloud. TableFlow means that we can open up these same streams directly as iceberg tables with the click of a button. This means data is defined a single time, stored a single time, and no complex mappings or translations are needed. TableFlow is in early access now and taking on its first users. For some vendors, the rise of open data formats like Iceberg is perceived as a threat as it opens up data that was locked in a silo to an ecosystem of processing and analytics layers, letting vendors compete on a level playing field based on cost, performance, and features, rather than any new entrant having to overcome significant data gravity. However, we believe Confluent is uniquely positioned to benefit from this trend as our goal, and indeed our business model, is built around the sharing of data. So the rise of Iceberg creates a very important destination for data that can increase the value of the streams in our platform. This makes TableFlow central to Confluent's vision of opening up and connecting all the data in an organization. We've heard overwhelmingly positive feedback from customers with this announcement and look forward to making this a significant part of our business over time. Last quarter, we discussed the world of stream processing and why our Flink offering is uniquely positioned to win this market. And we've been seeing incredible interesting excitement for our Flink offering. Nearly 600 prospects and customers have tried Flink since its preview. At Kafka Summit London, we announced the general availability of Confluent Cloud for Apache Flink. Early customer feedback has been strong. We see many of these customers starting the ramp towards production applications that will drive significant consumption over time. We announced another exciting Flink development at Kafka Summit Bangalore. We'll be adding Flink to our on-premise software offering, Confluent Platform. This helps our on-premise and hybrid customers adopt Flink for critical workloads running in their data centers. These are very exciting steps for Confluent, and it cements our position as the only complete data streaming platform. TableFlow and Flink are new capabilities beyond Kafka and represent significant progress towards building what we believe will be the most important data platform in a modern company. GenAI continues to be top of mind for many companies, but most are coming to realize that LLMs don't stand alone. RAG, or retrieval augmented generation, has emerged as the common pattern for GenAI to extend the powerful LLM models to domain-specific datasets in a way that avoids hallucination and allows granular access control. Data streaming platforms play a pivotal role in enriching RAG-enabled workloads with contextual and trustworthy data. It enables companies to tap into a continuous stream of real-time data from the systems that power the business and transform it into the right format to be used by vector databases for AI applications. Another announcement from Kafka Summit Bangalore that helps make this kind of RAG architecture easier was support for AI models and remote inference in Flink SQL. This capability is designed to simplify the development and deployment of AI applications by enabling software developers to integrate inference and embedding computation directly into their data processing, making it easier than ever to bring AI to real-time apps. We're seeing particularly strong traction with GenAI in the digital native segment, with companies like OpenAI, Notion, and Motive, who are leveraging GenAI to reimagine customer experiences in nearly every industry. One such customer is an AI-powered customer intelligence platform to manage contact centers and customer engagements. A powerful communications AI is central to its platform and is used for a variety of use cases, including surfacing real-time insights for call center managers and identifying when agents need immediate assistance or intervention in handling problematic situations. Their existing architecture was unable to handle the demands of real-time, with latency sometimes exceeding a minute. This sluggishness was unacceptable for an AI application that requires access to fresh and continuously updated data. So this customer turned to Confluent Cloud for fast and scalable data streaming. By integrating Confluent with other components of its architecture, the customer was able to significantly reduce latency for response times from over a minute down to as low as 10 milliseconds. With faster, fresher data and more real-time insights available, the customer is better equipped to meet the needs of its customers and provide them with valuable tools and analytics for managing their contact centers and customer engagements. But it's not just digital natives who are putting GenAI into action. Another great example is GEP Worldwide, a global leader in supply chain and procurement solutions. This billion-dollar revenue company provides software, consultancy, and managed services to some of the world's biggest multinationals. Its software offerings are infused by GenAI to support chatbots and decision support tools. Previously, the team was an open source Kafka shop, but operating and maintaining open source became too burdensome to maintain, ultimately stifling their ability to iterate and innovate quickly. So they turned to Confluent. With Confluent serving as the central nervous system of its software, the company is able to more quickly connect data across hundreds of applications, including both custom apps and the operational and analytical estates, to provide contextual, relevant, and real-time insight into its AI platform. Confluent continues to innovate across our products and partner ecosystem to make it easier for customers so organizations can quickly scale and build AI-enabled applications using trusted data streams. In closing, I'm incredibly proud of our team. Our rapid pace of innovation is phenomenal, and our field and go-to-market teams are leaning into our consumption transformation with early positive results. I've never been more excited or confident in Confluent's ability to capture the lion's share of the data streaming platform market. With that, I'll turn things over to Rohan.

Thanks, Jay. Good afternoon, everyone. We delivered solid first quarter results, beating all our guided metrics in a still uncertain macro environment. Key highlights include robust top line growth and bottom line improvements, the largest sequential customer growth since Q1 2023, and great momentum in multi-product adoption. These results reflect our team's strong execution on our consumption transformation and our expanding multi-product platform leadership in data streaming. Turning to the Q1 results, total revenue grew 25% to 217.2 million. Subscription revenue grew 29% to 206.9 million. Within subscription, Confluent platform revenue grew 15% to 100.1 million, representing 46% of total revenue. Customers rely on Confluent Platform to harness data streaming on-prem, on the edge, and bridge to the cloud. We continue to see healthy demand for Confluent Platform as most organizations are still early in their move to the cloud. Confluent Cloud revenue grew 45% to $106.8 million, exceeding our guidance of $105 million, and ended the quarter at 49% of total revenue, compared to 42% a year ago. Our cloud performance was driven by the ramp in consumption from select customers added in recent quarters. And we started seeing stabilization of new use case expansion in our existing customer base, including our digital native segment. Turning to the geographical mix of revenue, revenue from the US grew 23% to 127.4 million. Revenue from outside the US grew 28% to 89.8 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 76.9%, up 470 basis points. Subscription gross margin was 80.7%, up 320 basis points. We're pleased with operating above our long-term target level of 75% for total gross margin, even with a continued revenue makeshift to cloud. Our cloud offering has significant architectural advantages in multi-tenancy, elasticity, data balancing, networking, and data replication. Combined with continual optimizations at every layer of the stack, we have driven a significant cost advantage in operations while delivering industry-leading innovations to our customers at a lower TCO. Turning to profitability and cash flow, operating margin improved 22 percentage points to negative 1.5%, representing our seventh consecutive quarter of more than 10 points and fourth consecutive quarter of more than 20 points in margin improvement. Operating margin performance was driven by our gross margin performance and our continued focus on driving efficient growth across the company with the most pronounced progress made in sales and marketing. The improvements in sales and marketing demonstrates focused efforts in driving operating leverage and improving unit economics. Net income per share was $0.05 for Q1, using 350.2 million diluted weighted average shares outstanding. Fully diluted share count under the Treasury stock method was approximately 362.4 million. Free cash flow margin improved 33 percentage points to negative 14.6%. And we ended the first quarter with $1.91 billion in cash, cash equivalents, and marketable securities. Turning now to other business metrics. Total customer count was approximately 5,120, representing an increase of 160 customers sequentially. This is our largest sequential growth in total customers since Q1 2023, reflecting the early signs of success from our consumption transformation. Customers with 100k plus in ARR grew 17% to 1,260 and continue to account for greater than 85% of our revenue. Customers with 1 million plus in ARR grew 24% to 168, reflecting the power of our network effect and customers' continued standardization on our data streaming platform. NRR was healthy and in line with our target range of 120% to 125% for this year. Gross retention rate remained strong and was above 90%. As discussed last quarter, we expect NRR to exceed our midterm target threshold of 125% starting fiscal year 25 as we exit the consumption transformation. RPO was 840.2 million, up 13%. Current RPO was estimated to be 570.6 million, up 20%. As discussed in prior quarters, RPO-related metrics are now less relevant given our greater focus on driving consumption for our cloud business. Starting this quarter, investors can access our RPO metrics in our Supplemental Financials document on our IR website. Now, I would like to discuss our long-term opportunity with our data streaming platform, or DSP. We have driven success with our cloud-native streaming product, with Kafka accounting for the substantial majority of our cloud revenue. Over the last few years, we have added Connect, Process, and Govern to complete our multi-product platform. As Jay mentioned, early customer reception of our stream processing product, Flink, has been strong. As our customers start building and ramping their streaming applications, we expect Flink will contribute to revenue meaningfully in 2025. But Confluent isn't just about streaming and stream processing. Our growth potential with Connect and Govern is often underestimated. Legacy integration companies have a massive installed base around connectors, and this is a significant opportunity for our Connect portfolio. Connect is our first and largest DSP product after streaming, and its revenue growth trajectory has been robust. For Govern, the increasing complexity around data, security, regulation, coupled with the rise of gen AI are driving the demand for our governance products. In fact, revenue growth for stream governance has been the fastest of any products we have launched to date. The multi-product aspect of our unified platform adds to our growth vectors and extends our runway to drive durable and efficient growth. Let me put it into more context. First, each pillar of our platform has the potential to become a large, independent business on its own. The three DSP products, which include Connect, Process, and Govern, are earlier in their S-curve of maturity and adoption than Kafka. But over time, we think their growth potential will be larger than Kafka itself. Second, our opportunity with our DSP products remain in very early days. In Q1 2024, the three DSP products accounted for approximately 10% of cloud revenue, but with a substantially faster growth rate than our overall cloud business. We expect the three DSP products to remain the fastest growing part of our business and account for a much larger portion of our cloud revenue over time. And third, multi-product customers have a higher NRR profile. In Q1 2024, customers using three or more products in our 100K plus customer cohort increased 47% year over year. These multi-product customers had an NRR substantially higher than the company average. This underscores the strong network effects of our unified platform where the success of one product drives additional success in the others. As our data streaming platform matures and multi-product adoption continues to increase, we believe we will be in a stronger position to address our 60 billion market opportunity ahead. Before turning to our financial outlook, I'd like to note that our guidance philosophy is consistent with prior quarters with the overall objective of setting prudent and achievable targets. We don't forecast a better or worse macro environment in our guidance. And as a reminder, beginning with the third quarter of 2024, we will fully transition to providing total subscription revenue guidance only. Now let's turn to guidance. For the second quarter of 2024, we expect total revenue to be in the range of 229 to 230 million, representing growth of 21% to 22%. Subscription revenue to be in the range of 217 to 218 million, representing growth of 23% to 24%. Cloud revenue to be approximately 116 million, representing growth of approximately 39%. Non-GAAP operating margin at approximately negative 1%, representing improvement of approximately 8 percentage points. And non-GAAP net income per diluted share to be in the range of $0.04 to $0.05. For the full year 2024, we now expect total revenue to be approximately 957 million, representing growth of approximately 23%. Subscription revenue to be approximately 910 million, representing growth of approximately 25%. Non-GAAP operating margin to break even, representing improvement of approximately seven percentage points. Free cash flow margin to break even, representing improvement of approximately 16 percentage points. and non-GAAP net income per diluted share to be in the range of 19 cents to 20 cents. Finally, we expect net dilution for fiscal year 24 will be approximately 3% in line with our midterm target. Our long-term target is to bring net dilution down to under 2%, which we expect will drive SBC as a percentage of total revenue down to the mid teens over time. In closing, we're pleased with our strong top line and bottom line performance in the first quarter. Our consumption transformation has shown early signs of success. The value proposition of our multi-product platform is resonating with customers. We will stay focused on delivering innovation and value to our customers while continuing to fine-tune our go-to-market effort, which we believe will put us in a stronger position to capture our market opportunity ahead. Now, G and I will take your questions.