Confluent, Inc. (NASDAQ:CFLT) Q2 2023 Earnings Call Transcript

Confluent, Inc. (NASDAQ:CFLT) Q2 2023 Earnings Call Transcript August 2, 2023

Confluent, Inc. misses on earnings expectations. Reported EPS is $-0.41 EPS, expectations were $0.06.

Operator: Hi, everyone. Welcome to the Confluent Q2 2023 Earnings Conference Call. I’m Shane Xie from Investor Relations, and I’m joined by Jay Kreps, Co-Founder and CEO; Steffan Tomlinson, CFO and Rohan Sivaram, our incoming CFO. During today’s call, management will make forward-looking statements regarding our business, operations, financial performance and future prospects. These include statements regarding our financial guidance for the fiscal second quarter of 2023 and fiscal year 2023 and growth in our market opportunity and market share. These forward-looking 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-Q 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 financials 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.

And with that, I’ll hand the call over to Jay.

Jay Kreps: Thanks, Shane. Good afternoon, everyone and welcome to our second quarter earnings call. We delivered a great quarter, for the ninth time in a row we exceeded the high end of all guided metrics. Before going into further detail in the quarter, I’d like to share some organizational news. Steffan Tomlinson will be stepping down from his role as Confluent’s CFO and will be joining Stripe as their CFO. Rohan Sivaram has been named Confluent’s next Chief Financial Officer. Rohan is a seasoned finance and operations leader with nearly two decades of experience at leading companies across financial services, cybersecurity and data infrastructure. Rohan joined Confluent pre-IPO in 2020. He’s been instrumental to the success of our organization across corporate finance, investor relations, treasury and business operations.

Over the last three years, I’ve had the opportunity to work very closely with Rohan and could not be more excited to see him assuming this new role as our CFO. And Steffan, I wanted to take a moment to thank you for everything you’ve done for us. You’ve had an impact on every aspect of Confluent, including growing and scaling our operations, building a world class team and taking us through all nine quarters of earnings as a public company. Thank you and best of luck with your new role.

Steffan Tomlinson: Thank you, Jay. It’s been an amazing experience and career milestone to work with you and the talented team at Confluent. We’ve built a deeply differentiated platform that’s powered our robust growth, which positions the company very well for the future. I couldn’t think of a better leader than Rohan to help guide the company to the next level as Confluent’s new CFO. Rohan is truly an exceptional leader. We’ve known each other for nearly a decade and worked closely at both Confluent and Palo Alto Networks. Congratulations, Rohan, you’ll do great in your new role.

Rohan Sivaram: Thank you, Steffan. Congratulations to you as well. It’s been a pleasure working with you over the years and I’d like to wish you the very best in your next role. We have a world class innovation engine and an amazing team at Confluent. We are a market leader in a $60 billion TAM and we’re just getting started. I very much look forward to driving efficient growth in the years ahead. Now back to you, Jay.

Jay Kreps: Thanks Rohan. Turning now to our Q2 results, total revenue grew 36% to $189 million. Confluent cloud revenue grew 78% to $84 million and non-GAAP operating margin improved 24 points. We have driven more than 30 points of margin improvements in the last 18 months and are well on our way to breakeven in Q4 this year. Achieving this sustained level of high growth despite ongoing market challenges underscores the mission critical nature of data streaming and reinforces our product leadership. In May, we hosted Kafka Summit London 2023. This year more than 1500 members of the community from over 50 countries joined us in person with greater than 2300 tuning in virtually. On our Q1 earnings call, we talked about the opportunity for monetizing Kafka and Confluent Cloud.

This was emphasized at Kafka Summit with the unveiling of Kora, the next generation engine that powers Confluent Cloud. We shared with the audience some of the architectural elements that enable our cloud to drive a 10x advantage in performance while delivering a 60% TCO improvement. Our Kafka business has phenomenal growth ahead of it. Modern data architecture is increasingly centered around streaming and this has driven Kafka to be adopted by hundreds of thousands of organizations, including over 75% of the Fortune 500. This open source user base is growing rapidly and we are still in the early days of monetizing it. The inherent TCO and performance advantages of our cloud offering mean that in addition to the natural growth of this user base, we believe we can dramatically improve the proportion that is monetized as usage shifts to the cloud and can be captured by a managed service.

If that were the extent of Confluent’s opportunity, that would be a very exciting prospect and enough to sustain our growth for many years but Kafka is just the start. In this call, I want to outline the evolution Confluent is driving in the streaming space and how we stand to benefit from it. This evolution is the rise of the data streaming platform. Kafka is the foundational layer in this platform but I outlined today the five key areas of capability that significantly extend the reach and value of streaming infrastructure and that we think are essential elements to the rise of data streaming platforms. The key capabilities of a DSP are the ability to stream, connect, govern, process and share. These capabilities capture the full life cycle of streaming data, how to get it, process it, use it, manage it and share it between systems.

Kafka is the stream of data. It allows companies to produce and consume real time streams of data at any scale with strong guarantees on the delivery of data. It is the foundational hub of data exchange in a modern data architecture and today it comprises the substantial majority of our Confluent cloud revenue. But these other capabilities are not mere add-ons. They are essential components of the emerging platform and represent significant opportunities for monetization for Confluent that are still early in their realization. I’ll walk through each of these capabilities. Discuss the evidence that each is growing into a broadly adopted portion of the DSP and talk about how Confluent is adding these capabilities to Confluent Cloud. Our Kafka business and Confluent Cloud is growing very fast, but even today these non-Kafka components are growing even faster.

Over time, we expect these capabilities to drive the majority of our cloud revenue even as they help to accelerate the use of Kafka as the underlying strength. Let’s start with connectors. Connectors may seem mundane, but they are in fact a key capability. Indeed, many ETL and integration products differentiate in large part on their pool of connectors. They are central to our vision as well. To build a central nervous system for your business you have to be able to connect all of your systems to capture the real time streams of data. Confluent Cloud makes it possible to run any Kafka connector in a cloud native way, making them serverless, elastically scalable and fault tolerant. This has driven the development of over 120 connectors created and owned by Confluent to some of the most common enterprise systems.

However, the ecosystem of connectors is far larger than just these. There are many hundreds of open source connectors to less common systems that are available. We are still early in monetizing this area in Confluent Cloud as fully unlocking it requires ease of use across cloud networking layers and disparate data and SAS systems. We took a major step towards this in Q2 with the release of our custom connectors offering, which allows running any open source connector inside Confluent Cloud, expanding our reach beyond the set of connectors we ship with out-of-the-box. We believe this is still in the early phases of full unlock. On premise in our Confluent platform product Connect has approximately an 80% adoption rate. But we are still in the early days of ramping that level of usage in our fully managed offering Confluent Cloud.

As data streaming use cases grow and real time data flows across internal systems and applications it’s critical that users can discover, monitor and reason about the security and integrity of that data. You need to control who has access to the data to find how that data is allowed to evolve and visualize and monitor where it ultimately goes. Creating a central nervous system for data is only possible if you can stream data safely. What do these governance concerns have to do with streaming, you might ask? Well, it turns out that governance concerns come into play precisely when data moves between systems, when it’s exchanged between teams or is transported between Regents, or as processed from one form to another. In other words, data governance needs arise directly from the primary use of data streaming.

Because Confluent handles this movement and processing, we are uniquely positioned to directly integrate governance of that movement automatically and seamlessly in a way that no other vendor can with a bolt on product. This is the role of stream governance, one of our first moves up the stack and a large product opportunity for Confluent. Stream Governance is our fully managed governance suite that delivers a simple self-service experience for customers to discover, trust and understand how data flows across their business. We have taken a freemium approach to stream governance giving basic functionalities to every customer and more recently, starting to monetize with our Stream Governance Advanced offering. Two thirds of our Confluent Cloud customers are using Stream Governance today and revenue growth from Stream Governance Advanced is the fastest of any product we’ve launched today.

The next area of the DSP is Stream Processing. This is an easy one to understand. Data processing is a key component of any major data platform and SQL and other processing layers are a key component of modern databases. Stream Processing extends these processing capabilities to real time data streams. We believe that Apache Flink is emerging as the de facto standard for stream processing. Flink has the most powerful implementation of stream processing of any technology, open source or proprietary, fully realizing streaming as a generalization of batch processing and making it available across a rich ecosystem of programming languages and interfaces. It is widely popular in the open source community and is used by some of the most technically sophisticated companies in the world, including Apple, Capital One, Netflix, Stripe, and Uber.

We’ve discussed the criticality of Stream Processing to our strategy in the past. The easiest way to understand the potential in this area is to understand that for each stream in Confluent Cloud today, there’s likely to be some application code processing or reacting to that stream of data. That application code represents complex software engineering and the opportunity for Flink from the customer’s point of view is to simplify that development effort, from Confluence point of view this allows us to monetize not just the data, but the application itself while helping the customer to realize efficiencies in both the development and operational costs that are possible with the cloud native stream processing layer. We took a major step forward on our Flink strategy this last quarter when we announced the early access program at Kafka Summit, opening up this offering to the first customers who are now actively using the platform.

Early feedback is very encouraging with particular enthusiasm for the direct integration into the other capabilities of Confluent Cloud. For customers, this means their streams of data in Kafka are automatically available for processing in Flink’s SQL and that everything works together with the shared model of governance and security. We’re incredibly excited about this product and look forward to its broad availability later this year. The final capability is about making it easy to share data streams. Sharing within a company has been a mainstay of our platform for some time. However, now we have extended that between companies with a feature we just launched at Kafka Summit, Stream Sharing. This intercompany sharing is a pattern we noticed was gaining startling traction in our customer base in recent years.

Customers in financial services and insurance needed to integrate and provide key financial data streams with a complex set of providers. Customers in travel needed to exchange real time data on flights between airports, airlines, bookings companies and baggage handling companies. Retailers and manufacturers had to ingest real time streams from suppliers to manage an end-to-end view of their inventory or supply chain. Oftentimes these companies would have teams working out complex systems to mediate this sharing, only to realize on further discussion that on both sides the foundational layer that they were opening up was the same. It was Kafka. Stream Sharing allows these companies to enable this inter organizational sharing for any of their existing streams and to do so in a way that enables the same governance and security capabilities that they’d use internally with added capabilities to address the additional concerns of allowing access from external parties.

This means extending our central nervous system vision for something that spans a company to something that spans large portions of the digital economy. By doing this the natural network effect of streaming where streams attract apps which in turn attract more Streams is extended beyond a single company, helping to drive the acquisition of new customers as well as the growth within existing customers. It’s essential to understand that these five capabilities stream, connect, govern, process share, are not only additional things to sell, they are all part of a unified platform and the success of each drives additional success in the others. The connectors make it easier to get data streams into Kafka, which accelerates not just our core Kafka business, but also opens up more data for processing in Flink, adds to the set of streams governed by Stream Governance where they’re shareable by Stream Sharing.

Applications built with Flink drive use of connectors for data acquisition and read and write their inputs from Kafka. Governance and sharing add to the value proposition for each stream added to the DSP. Each of these capabilities strengthens the other four. The full value of this will not be realized overnight. Cloud infrastructure takes time to mature and reach completion. Each of these areas is earlier in the S curve of maturity and adoption than Kafka, but over time, we think these will directly contribute revenue larger than Kafka itself in addition to driving further consumption of Kafka. Most importantly is what these capabilities let our customers do. As these parts come together, they comprise a data platform that is as complete as data warehouses, data lakes or databases have grown to be over the years.

We think this data streaming platform will be of equal size and importance to these other platforms serving as the fundamental nervous system for a modern company. This complete platform resonates with companies of all sizes, industries and geographies serving an endless number of use cases. One segment of our customer base that has been under particular pressure in this macro environment is digital native tech companies who are under increasing pressure to drive new efficiencies. But this is also a high performing segment of our business, a testament to our execution and the TCL advantages of our platform. This includes customers like Instacart, Netflix, Plat and Square. We are seeing particularly strong traction in this segment in India, including customers like Meesho.

Meesho is a high growth Indian e-commerce company who last year was one of the most downloaded shopping apps in the world. It was the fastest shopping app to cross 500 million downloads and regularly sees huge traffic spikes that see over 1,000,000 requests per second. Kafka is used broadly across Meesho’s business including its real time recommendation engine to deliver great user experience for customers and sellers. But manually configuring and tuning open source Kafka wasn’t aligned with their overall push for sustainable solutions and driving business efficiencies. So they migrated to Confluent Cloud. Confluent now processes its shopping transactions and is a key part of the architecture that delivers exceptional experiences for its buyers and sellers.

Policy Genius is an online insurance marketplace that covers more than 30 million customers and their life, disability, home and auto insurance needs. Today’s customers demand real time in all aspects of their life, even when shopping for insurance. By combining modern tech with real agents, Policy Genius delivers quotes from leading insurance companies side by side in minutes and helps customers through the selection and purchasing process. Initially, they relied on the competitors Kafka compatible data streaming technology to stream policy information to their agents, but they found themselves spending too much supporting the platform and were caught off guard by surprise costs. And as they look to expand use cases, they needed a more complete data streaming platform they could grow alongside them.

After two months trialing Confluent as a pay-as-you-go customer, they went all in on Confluent Cloud in Q2. With Confluent Cloud, Policy Genius can save money while helping their customers feel good about finding the right insurance online. Recursion Pharmaceuticals is a leading biotech company that uses advancements in AI and biology to accelerate and industrialize the discovery of new drugs. Traditional drug discovery is often slow and expensive, relying on manual bespoke processes and experiments influenced by human bias. Recursion, on the other hand, runs over 2 million experiments per week to generate a massive biological and chemical data set to train machine learning models that discover new insights beyond what is known in scientific literature.

Confluent is the backbone stream infrastructure for experimental data that feeds their AI models, with more than 23 petabytes of real time biological and chemical data improving the predictions of the models. This approach rapidly accelerates the time it takes to discover and develop drugs, and ultimately as how they improve the lives of patients all around the world. In closing, I’m pleased with our strong second quarter results. Our results show that data streaming has emerged as a mission critical component of the modern data stack and our rapid pace of product innovation puts us in an excellent position to continue capturing more of this $60 billion market opportunity. With that, I’ll turn the call over to Steffan to walk through our financials one last time.

Steffan Tomlinson: Thanks, Jay. We delivered another strong quarter beating our guidance on all metrics. Key highlights for the second quarter include robust top line growth, strong customer expansion and substantial margin improvements. These results underscore our leadership position in a $60 billion data streaming market and our team’s track record of driving durable and efficient growth. Turning now to the results, RPO for the second quarter was $791.4 million, up 34%. Current RPO, estimated to be 65% of RPO, was $514.8 million, up 41%. Our growth rates in RPO, while healthy were impacted by a continuation of lower average deal sizes, a result of customer scrutinizing their budgets in the current environment. Despite the budget scrutiny, we remain encouraged that customers continue to derive value from using Confluent and consume more than their commitments, which is reflected in our revenue but not in our RPO results.

In Q2, we added 140 net new customers, ending the quarter with approximately 4830 customers, up 17%. The growth in our large customer base remained robust, driven by continued expansion of use cases. We added 69 customers with 100K or more in ARR, bringing the total to 1144 customers up 33%. These large customers contributed more than 85% of total revenue in the quarter. We also added 12 customers with $1,000,000 or more in ARR, bringing the total to 147 customers, up 48%. And our $5 million plus cohort continued to grow. Our expansion momentum shows that Confluent is the platform of choice for data streaming from early stage adoption to cross company standardization and ultimately the central nervous system of our customers’ modern tech stack.

For Q2 and NRR was above 130% in GRR was above 90%, NRR for Cloud was above 140%, reflecting the power of the industry’s only cloud native platform made possible with Quora. Turning to the P&L, total revenue grew 36% to $189.3 million. Subscription revenue was very strong and grew 39% to $176.5 million and accounted for 93% of total revenue. Within subscription, Confluent platform grew 16% to $92.9 million, exceeding our expectations and accounted for 49% of total revenue. Q2 marks the second quarter this year in which Confluent Platform overperformed relative to expectations. It was driven by strength in regulated industries such as public sector and financial services. These industries are still in the early stages of moving workloads to the cloud, but have a high demand for on-prem data streaming.

Confluent Cloud revenue grew 78% to $83.6 million. We guided sequential revenue growth of $7.5 million to $8 million for Q2. The actual sequential increase came in at $9.9 million, exceeding the midpoint of our guidance range by $2.2 million and it was driven primarily by higher than expected consumption from select customers. From a product mix standpoint, cloud revenue accounted for 44% of revenue compared to 34% of revenue a year ago and cloud as a percentage of new ACV, bookings exceeded 50% for the 7th consecutive quarter. Turning to the geographic mix of revenue, revenue from the U.S. grew 30% to $113.9 million, revenue from outside the U.S. grew 45% to $75.4 million. Moving to the rest of the income statement, I’ll be referring to non-GAAP results unless stated otherwise.

Total gross margin was 75%, up 440 basis points and above our FY23 target range of 72% to 73%. Subscription gross margin was 79.1%, up 230 basis points, gross margin outperformance was driven by our strong Confluent platform margin that continued improvement in efficiency, optimization of underlying hardware profile and increase multi tenancy and Quora, our core Kafka engine and Confluent Cloud. Turning to profitability and cash flow, operating margin improved 24 percentage points and negative 9.2%, representing our 4th consecutive quarter of more than 10 points in improvement. Q2 operating margin was driven by subscription revenue outperformance 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 14 percentage points and we’re pleased to achieve $0.00 net income per share in Q2.

We’ve included all related shares, outstanding amounts used to calculate historical and guided net loss or income per share and our earnings presentation on our website. Free cash flow margin improved 8 percentage points to negative 18.6%. We ended the second quarter with $1.85 billion in cash, cash equivalents and marketable securities. Now turning to our outlook, I’d like to provide context on how our approach to guidance continues to evolve in response to what we’re seeing in the business environment. At the beginning of the year, we prudently took into consideration and have been navigating the tough selling environment and the macro related factors of additional budget scrutiny and changes in customer buying behavior, both of which have led to sales cycle elongation.

We’ve learned through the first half of this year that customers are more inclined to sign shorter duration contracts, start with smaller initial deal sizes and are okay consuming more than their committed contracts, which has been reflected in our results. Our point of view is the choppy macro environment we’ve seen will continue throughout the remainder of the year. Even with these macro dynamics at play, our data streaming platform continues to grow at outsized rates. Our subscription revenue growth of 39% in Q2 tells the story. From a product mix standpoint, Confluent platform, which is prevalent and regulated industries has overperformed relative to our expectations. We expect Confluent Platform to continue to perform well in the second-half, trending above the expectations we had at the beginning of the year.

Our cloud business continues to be a bright spot given the high net retention rates, product market fit, strong TCO and ROI it delivers to customers. We expect cloud to continue to grow at a substantially higher rate than the rest of the business in the second-half. We’ll continue to monitor the signals of our business and proactively manage the rate and pace of investments. If the macro sentiment improves, we’d expect to benefit from that, but it’s too soon to call. Moving on to our guidance, I’m pleased to share that we’re raising total revenue, gross margin, operating margin and EPS for both the quarter and the year. For the third quarter of 2023, we expect revenue to be in the range of $193.5 million to $195.5 million, representing growth of 28% to 29%.

Cloud revenue to be approximately $92.2 million, representing growth of 62% and accounting for approximately 47% of total revenue based on the midpoint of our guide. Implied in that is a sequential revenue add of approximately $8.5 million which is above our prior quarter guidance range of $7.5 million to $8 million for Q2 23. Non-GAAP operating margin to be approximately negative 10% and non-GAAP net loss or income per share to be in the range of negative $0.1 to $0.00. For the full year 2023, we expect revenue to be in the range of $767 million to $772 million representing growth of 31% to 32%. Non-GAAP operating margin to be approximately negative 10% and non-GAAPp net loss per share in the range of negative $0.5 to negative $0.2 cents. Additionally, we’re raising our FY23 target range for non-GAAP gross margin to approximately 74% for Q 4 2024 targets we continue to expect to land within the range of 48% to 50% for cloud as percentage of total revenue, but likely at the lower end due to the factors we called out before and the strength in our Confluent platform business impacting product mix shift.

And we continue to expect to achieve break even for non-GAAP operating margin. The timing of free cash flow margin break even will roughly mirror that of our operating margin. In closing, I’m pleased with the continued momentum we see across Confluent Platform and Confluent Cloud. Our market leading data streaming platform is winning and we’re continuing to execute well in a choppy macro environment. Looking forward, we’re well positioned to drive durable and efficient growth. Now Jay, Rohan and I will take your questions.

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Q&A Session

Operator: Thanks, Steffan. To join the Q&A, please raise your hand. And today, our first question will come from Jason Ader with William Blair, followed by Wells Fargo. Jason, please go ahead.

Jason Ader: Yes. Thanks Shane and good luck to you Steffan. You really do have the Midas touch, with your job choices, but my question is on the consumption side. Confluent Cloud has been out for a few years now. Are you seeing a trend where customers are over consuming more than they previously had and you talked about kind of the annual commitments that they’re making, are they tending to make lower annual commitments because of the economy and therefore overconsume more and then how does that manifest in the numbers?

Steffan Tomlinson: Yes that’s a great question and that dynamic is present. I would attribute it to two facts, internally we have been really shifting our go-to market to emphasize driving consumption, more use cases coming on to the platform as quickly as possible even outside of the term of new commitments. And then externally, yes, there’s real market pressure and so companies are being very thoughtful about how, what they commit to up front, how much they pay ahead et cetera, and so, both those dynamics are present and that is reflected in a really strong consumption results. I think it’s ultimately healthy. This is kind of the intention of these consumption models that’s certainly how we treat consumption vendors internally. But it does show up you know when you look at the kind of RPO, CRPO split and RPO versus kind of revenue performance for Confluent Cloud.

Jason Ader: All right and one quick follow up just on Fed ramp, when are you guys expecting to get Fed ramp authorized for Confluent Cloud?

Steffan Tomlinson: Yeah, we haven’t given any you know public timeline for that. It’s obviously a big focus for us and we’ve seen really strong results in the public sector even though we’re effectively kind of fighting with one hand tied behind our back. So we’re very excited about that coming online.

Jason Ader: Thanks very much and Congrats to you, Rohan.

Rohan Sivaram: Alright, thanks Jason. We’ll take our next question from Michael Turrin with Wells Fargo followed by Goldman. Michael, please go ahead.

Michael Turrin: Hi, thanks. Appreciate you taking the question. I apologize the video operator seems to be not too kind on my side, but quick question just on Cloud, obviously a big point of focus came in strong in Q2, just wondering if you can add commentary on the progression you saw during the quarter, visibility you have into rest of the year as a result and then it looked like 3Q guidance is now sequentially down a touch as of starting point versus where Q2 came in. Was there anything unexpected that came through in Q2 or maybe just help us think through the progression of what you’re expecting to see on Cloud from here? Thanks.

Jay Kreps: Yes, we saw really great results on consumption. I would say particularly set a larger customers drove kind of over performance there. We didn’t think that that indicated necessarily equal over performance on each subsequent quarter. But overall the trajectory for Cloud consumption is very strong and we feel really good about it. So I don’t know if you want to add anything to that Steffan?

Steffan Tomlinson: Yes. The only other thing I’d add is at the beginning of the year we had called for sequential increases in Cloud revenue and we’ve been delivering that in Q1 and Q2. We had guided $7.5 million to $8 million for Q2 and we came in $2.2 million above the midpoint of the range and so when you when you take out a little bit of that over performance and you look at our guide for Q3 that will, that is a sequential increase relative to our original guide in Q2. So the underlying strength and drivers of the cloud business very strong and we are seeing adoption across cohorts and we’re seeing very good adoption in the marketplace.