CFLT - NASDAQ

Hello, everyone. Welcome to the Confluent Q1 2024 Earnings Conference Call. I'm Shane Xie from Investor Relations, and I'm joined by Jay Kreps, 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 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-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 facility 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 IR website at investors.confluent.io. And finally, once we have concluded our earnings call, we will post the Confluent earnings report to our IR website. The report is a single PDF, which contains our earnings into graphic, 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 the subscription revenue and remains our fastest-growing offering. Non-GAAP operating margin improved 22 percentage points our fourth consecutive quarter of more than 20 points improvement. These results reflect our team's strong execution amid 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, reduced friction and lending new customers. It remains early days but we are in 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 adds 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 the tremendous growth and innovation happening within the data streaming category. Between the 2 events, we had more than 7,000 people joining us in person or registered virtually, spanning start-ups, 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 pricing 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 and 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, who's existing in closed systems that tracked their data inside of walled garden. As the complexity of the analytics world has grown, this has led to a mismatch of data warehouses, data links, AI products and reporting systems. This granted lots of value for technology vendors but created yet another data silo for the end user. However, over the last 5 years, a trend has emerged of standardizing around open data formats and metadata on top of cloud object store. 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 that 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. Kora, 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 incredibly 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 assumption 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 capabilities beyond Kafka and represents significant progress towards building what believe will be the most important data platform in a modern company. Gen AI continues to be top of mind for many companies but most are coming to realize that LLM don't stand alone. RAG or retrieval augmented generation has emerged as the common pattern for Gen AI to extend the powerful LLM models to domain specific data sets in a way that avoids hallucination and allows granular access control. Data streaming platforms play a pivotal in enriching RAG-enabled workloads with contextual and trustworthy data. It enables companies to tap into a continuous stream of real-time data to that power the business and transform it into the right to be used by vector basis for AI applications. Another announcement from Kafka Summit Bangalore that helps make this kind of RAG architecture easier with support for AI models in 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 the digital native segment with companies like OpenAI, Notion and Motive. We're leveraging Gen AI 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 latencies for response times from over a minute down to as slow as 10 milliseconds. With faster, fresher data and more real-time insights available, the customers better equip 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 Gen AI into action. Another great example is GEP Worldwide, a global leader in supply chain and procurement solutions. This $1 billion revenue company provides software consultancy and managed services to some of the world's biggest multinationals. Its software offerings are infused by Gen AI 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 turn 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 and 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 create momentum in multiproduct adoption. These results reflect our team's strong execution on our consumption transformation, and our expanding multiproduct 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 U.S. grew 23% to $127.4 million. Revenue from outside the U.S. 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 are pleased with operating above our long-term target level of 75% for total gross margin even with a continued revenue mix shift 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 negative 1.5%, representing our seventh consecutive quarter of more than 10 points and fourth 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 economy 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 $100,000 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 in the 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 multiproduct 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 multiproduct 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 3 DSP products, which include Connect, Process and Govern are early their S-curve of maturity and adoption than Kafka. But over time, we think the growth potential will be larger than Kafka itself. Second, our opportunity with our DSP products remain in very early days. In Q1 2024, the 3 DSP products accounted for approximately 10% of cloud revenue, but with a substantially faster growth rate than our overall cloud business. We expect 3 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, multiproduct customers have a higher NRR profile. In Q1 2024, customers using 3 or more products in our 100,000-plus customer cohort increased 47% year-over-year. These multiproduct customers had an NRR substantially higher than the company average. This underscores the strong networks of our unified platform, where the success of one product drives additional success in the others. As our data streaming platform matures and multiproduct 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 worst 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 million to $230 million, representing growth of 21% to 22%. subscription revenue to be in the range of $217 million 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's net per diluted share to be in the range $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 breakeven, representing improvement of approximately 7 percentage points. Free cash flow margin to breakeven representing improvement of approximately 16 percentage points and non-GAAP net income per diluted share to be in the range of $0.19 to $0.20. 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 are pleased with our strong and bottom line performance in the first quarter. Our consumption transformation has shown early signs of success. The value proposition of our multiproduct 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 Jay and I will take your questions.

[Operator Instructions] And today, our first question will come from Sanjit Singh with Morgan Stanley, followed by RBC.

Congrats on a solid start to the year. Jay, I want to go back to the big macro environment in terms of just the pace of new software development projects. I remember last year, that had definitely slowed down quite a bit. What are you seeing now in terms of just new software development initiatives? And maybe you can sort of tie that into some of the sales transformation efforts that you have thrown on new organization?

Yes. I think we've seen overall stabilization. I would say the focus for a lot of our customers over the last year was really heavy focus on cost optimization with some amount of new developments, but really only the most necessary things. I do think that's picked up a little bit. The -- that's probably most pronounced in the digital native segment where they were probably the hardest hit last year. And they probably have the biggest bounce back in terms of focus on AI-related initiatives and other developments. So I would say that's positive. And then on the consumption transformation, I think that's gone really well. I do feel like we've seen -- we had to execute really a large number of changes in a pretty short period of time. And I think we've really significantly derisked the set of changes by rolling out a bunch of system changes. They were well adopted by our field team. They've actually proved themselves out with customers. And I think that's shown up in the higher rate of new customer acquisition. And I think one of the nice things is in addition to just getting more customers, we're actually targeting and getting higher propensity customers. So it's kind of more volume and higher quality book. So yes, we felt like that was overall a really good result.

It's good to hear. I really appreciate the breakout on some of the new product contribution in Q1 2024. In terms of the monetization strategy across the pillars of DSP, could you just sort of just outline that for us? And how does Tableflow potentially get monetized overtime?

Yes. Yes. So each of those represents kind of a distinct monetization opportunity. So the connectors, we charge for each of these connectors. There's a couple of pricing levers but it roughly correlates with how many instances of the connector and the amount of volume of data flowing. For Flink, it's kind of the compute hour is very similar to the models you'd see for other processing services like Snowflake. For Governance, it's an uplift that comes as kind of a flat fee as you move to our advanced governance package as well as something that scales up with your usage of the product. And Tableflow is new. So it's just an early access. Now, we haven't announced any pricing but that will also have monetization opportunities that go along with it.

All right. Thanks, Sanjit. We'll take our next question from Matt Hedberg with RBC followed by Barclays.

Congrats on the results. Really nice to see. Maybe as a follow-up to Sanjit's question. You guys have a lot of company-specific drivers that are certainly seeming to be apparent in your numbers. I'm just sort of curious, could you help us think about how important improving hyperscaler trends and growth rates that we're seeing in that is also relevant to your success? Just trying to get a sense for how much of it is just sort of more of the environment versus complement specific?

Yes. Yes, it's a question. I mean I don't know that the specific performance of other companies directly drives us but there's obviously some amount of correlation in all spend in the cloud. If we were breaking out the different things, I would say the success of our consumption transformation thus far. That's an important factor. I think the kind of DSP components that Rohan outlined are early contributors probably, Connect is the furthest along, followed by Governance and Flink just went GA. So that's just starting to ramp to revenue contribution, it'll contribute more coming into next year.

If I can just follow up, actually as a nice tie. It sounds like, Jay, you mentioned 600 prospects have tried Flink. It's great to hear. I mean we're starting to hear it show up in partner conversations as well. It sounds like a '25 thing. I'm just wondering Rohan, to -- when you think about it in guidance, are you featuring any Flink contribution in the second half of '24?

Matt, thanks for your question. Well, we've said this before, really Flink is a big opportunity for us. And 2024 is all about adoption and 2025 is all monetization. So from an overall what's included guidance, we're basically assuming that the contribution -- the material contribution from Flink will happen in fiscal '25.

All right. Thanks Matt. We'll take our next question from Raimo Lenschow with Barclays, followed by William Blair.

Congrats from me as well. Jay, on the Flink side, now that you have proper early customer conversations, what are you seeing in terms of the adoption curve you seeing there? And you obviously saw -- have seen Kafka before. What's the early customer conversations there? And what does it drive you if you think about the addressable market coming out of that one?

Yes, I would say it's been very positive. There's incredible enthusiasm in our customer base really across the broad set of customers from the kind of digital native to large enterprises. It's early in the adoption for any of these cloud offerings. Nobody wants to build production workloads against the pre-GA product. So this kind of milestone of going GAs really kind of the starting line and then it's really about the build of production workloads. And each workload adds a little bit of continuous revenue production. And as those build up within customers, that's where it starts to contribute meaningfully. And so I would say, overall, both the development of that product, the market reception has gone about as well as we could possibly expect as we kind of initiated the development of the Flink offering. Now it's really on us to go execute it as a business and make customers successful with it, which is obviously a very important next step.

Yes. And then one follow-up, Rohan, where I get a lot of the questions at the moment from the financial committees on RPO, cRPO. Maybe it's worth a reminder why that's kind of -- how that number came together and how that number needs to be seen in the overall context of the results?

Absolutely. Raimo, we've called it out last quarter. When we think about the consumption transformation, one of the important changes that we are driving is making sure we're driving and incentivizing and focusing on consumption and not the commitment from the customer. And what that means is RPO is nothing but the commitment from the customer. And that not a huge focus for us because what drives Confluent Cloud is next unit of consumption. And as result of that, we said that when you think about the forward-looking indicators of our business, consumption revenue and subscription revenue are true indicators of organic growth and that will be probably a more leading indicator than RPO, cRPO.

Thanks, Raimo. We'll take our next question from Jason Ader William Blair, followed by Walls Margo.

Just wanted to ask about Gen AI. You gave some customer examples where folks are using your technology as part of Gen AI projects. Can you talk a little bit more about the timing of actual impact to the revenue? And then what specific products are you selling? Is it just the streaming? Or is it some of the other elements of the DSP?

Yes. Yes. So kind of as we described, I would say that's ramping now, like we're seeing customers that are adopting this. Usually the digital names are a little further ahead in their use cases. This is one of the number of use cases for us. It's not the only thing happening. But it's an important one and I think a strategic one for customers. So yes, I think that as these initiatives hit production, I think we'll see an increasing ramp of contribution from them heading into next year. The -- what their customers are using is really the full platform. Like our role in this is to supply chain of data. So that involves our connectors, involves Kora, our Kafka engine, it'll increasingly involved Flink and the integration into the LLM that we just announced in Kafka Summit Bangalore. And so yes, I think all of that will be driven by these use cases.

And one quick follow-up for Rohan. Rohan, can you talk about hiring right now? You seem to be doing a good job managing expenses but I assume that with things stabilizing, you guys are ramping up some of your hiring, and that's one of the reasons why the op margins are going to be flat this year, which is maybe some thoughts on the hiring.

Yes. I mean, Jason, when we really think about our resource allocation philosophy, it is obviously driving durable and efficient growth. And when I say durable growth, it's essentially extending our runway to growth over a long period of time. And as we think about that, of course, like investment and investment in headcount is a key part of that. So for example, in Q1, we've had one of our strongest hiring quarters for the go-to-market organization, which is great. And so yes, I think we feel pretty good with respect to where we are and how we are thinking about a balanced approach on growth and profitability. On your question on the margins, as you know, over the last, say, 24 odd months, we've improved our efficiency by over 40 percentage points. And heading into this year, we're on track to deliver the 7 percentage point improvement, which is going to get us to breakeven for the full year, and we are on track to get there.

Thanks Jason. We'll take our next question from Michael Turrin with Wells Fargo, followed by Mizuho.

Great. Jay, back to Flink, is there a way to think about the customers you see as best suited to take advantage of the offering. I'm wondering if the addition of platform is important from that perspective. And then any early sense you can provide us around how getting newer products to GA can help as the go-to-market conversations are shifting more towards consumption profile and away from booking?

Yes. Yes, I'm happy to do that. So we've certainly seen interest across our customer base. One of the things that we will see is a slightly different dynamic between the Confluent Platform Flink offering and the cloud offering. With the cloud offering, the early versions of the cloud offering tend to be best suited to new use cases, just beginning development, whereas there's more of a lift in shift opportunity on-premise as well as suiting new use cases. Over time, as that cloud offering reaches feature completeness and proofs itself out with customers, there will be more of a shift of existing Flink workloads, that's the behavior we saw with Kafka, where the early adoption was the incremental use case and the lift and shift of kind of large installed bases took more time. So I think we'll see a similar behavior here and that's what we've seen out of customers. Nonetheless, across the full set of customers. There's a ton of eagerness. So people are kind of lining up. Even if there's some feature they're waiting on, they're eagerly awaiting the delivery of that feature. So yes, I think that we'll see growth on both dimensions. In terms of why we added to the software offering Confluent platform, that was by popular demand. Originally, the intention was just to do in cloud. Ultimately we have a set of customers that have pretty extensive on-premise operations, some of them are very big Flink users and they were very eager to have an offering for them as well. And for us, our goal is to serve customers everywhere. And so as soon as we add capacity to kind of take on the development of that, we added plans for that and built it up.

Rohan, if I may, just if you can comment from your perspective on how the go-to-market changes you've made are progressing and how that impacts your confidence around the initial fiscal year guide you framed alongside Q3? It's encouraging to see the numbers moving up but just any additional context is useful.

Absolutely. Well, Jay touched on it. I mean, the early indicators from the consumption transformation have been very positive. And we've gone through made a lot of changes with respect to processes, systems. And some of the early data points, for example, if you look at the ads that we had in Q1, the highest we've had in 5 quarters. Obviously, early but very positive. And then when you look at our Q1 performance in general, we're very pleased with our total revenue performance and particularly our cloud revenue performance and the growth we saw 45% year-over-year. And that momentum has actually continued into the month 1 of the second quarter as well. So when you kind of put this into context, Michael, for the full year, we've increased our full year guidance from 22% to 23%. And what has also happened is we've delivered a strong Q1 with a strong guide for Q2. So that has somehow derisked the second half of the year in a manner, which we're uncandidly very happy about. And more importantly, when you look at the growth rates first half versus second half, that was obviously a point of discussion same time last quarter. Now we're looking at flattish because of the derisk nature of our first half performance. So overall, I would say early indication very positive, feel good about our full year guide and obviously happy about our Q1 performance.

Thanks, Michael. We'll take our next question from Gregg Moskowitz with Mizuho, followed by Needham.

Jay, obviously, there's a lot of buzz in the industry around Apache Iceberg. So once Tableflow becomes GA, what are your expectations on the adoption curve among your installed base? Also, do you think that it will help you land new logos as well?

Yes. Yes, I think it will. We were actually expecting a fair amount of enthusiasm around this. As you said, there's a great deal of buzz around Iceberg. Despite that, I think we were actually surprised by how widespread the interest was. And we felt like, well, in many ways, sometimes the analytics environment is kind of a little bit to the side of the team that we naturally serve. We weren't sure if they would have a direct interest in that. But in fact, it's been a huge drop and topic of discussion in almost every conversation that I've had with the customers. So no, it's on us to deliver a GA product. This is just the first step in that journey. So it would be too early to project the rate of adoption or revenue contribution or whatever, but we feel that, that has a ton of potential as it comes out onto the market. And as I said, it does kind of align with our business in, I think, a really fantastic way. Confluent is very much about opening up data and sharing it across an organization. And this is a fantastic mechanism for us to do that. In many ways, the fragmentation of the analytics market made it hard to deliver data and the volume that we would like across all the different systems there. And this really helps with that. And our ability to integrate that directly into Kora and offer that data in a very natural low friction, low overhead way, I think, is a great competitive differentiation. And I think a huge boon to that area as well where one of the challenges in that environment is always getting access to high-quality, reliable data that's up to date. So yes, I think we're very excited about it. Still early and we have to go finish the delivery of the product and make all the customers' success.

Very helpful. And then either for you or for Rohan. So we've spoken before about the potential to do a lot more business with SIs going forward. The new accelerate with Confluent program will that or can that be a difference maker in your view? and if so, why?

Rohan, you want to take that?

I'll be happy to. Gregg, I mean we've called it out before as well when we think about the broader partner ecosystem and kind of up leveling a little bit, that's an opportunity, which is in early innings, most of the opportunities ahead of us. So specifically around SI and accelerate program that we called out, absolutely, that's an opportunity for us to drive revenue. But again, it's in early days. So it's not that something you're going to see next quarter or next month. It is an huge opportunity for us and we're working hard to make sure that we're taking advantage of that opportunity. So long story short, I think SIs and in general, GSIs and the partner ecosystem will continue to be a focus for us as we look ahead.

Great. We'll take our next question from Mike Cikos with Needham, followed by TD Cowen.

Jay, Rohan, I wanted to come back to the multiproduct adoption that you guys are citing today. And what I was thinking through, I just wanted to stress test this. Is it fair to think that your shift in this to prioritize consumption over commitments is actually driving faster adoption across Confluent's Platform? Or is it still too early to start seeing this in the numbers? This has been like a slow go but that's something to come as a result of this go-to-market transformation you guys have...

Yes. Yes. It's -- actually, it's a very good observation. So this is a subtle point but previously, the field team really sold commitments, which was just dollars. And so the incentive to drive adoption of these DSP components was much less, right? Of course, the customer adopt Flink, they'll consume more as it comes time for them to renew next year, they might commit to more but that payoff could be a year out. It's somewhat delayed. In a consumption world, of course, consumption ramps higher the immediate compensation arrives, right? And so that payoff is much more immediate. And so the consumption transformation was actually quite important for driving adoption of these additional components around Kafka. In terms of have we seen that effect? Yes, I think we've seen an increased focus from our field team on these components to us. The use cases around that it's not like it just materializes overnight to all in 1 quarter, that will build that getting that model right to be set up for multiproduct delivery, was actually a substantial motivation for us in doing this more quickly because we felt we had actually very good offerings now around Kafka, and we wanted to make sure that we were set up to sell them.

Awesome. And then just a follow-up on the go-to-market, a bit of a 2-parter here. But I guess to start with, Jay, like, it's interesting, one of the things that I think you guys are calling out is attach you're seeing from even higher quality customers despite the fact that you're not pressing on commitments, right? And I would have thought the presumption would be that if you're not pressing on commitments, your might get some lower quality customers. So can you kind of tease that out for folks, I think that would be beneficial? And then I guess, the second piece for Rohan, if you could just articulate like I know there was a lot of angst into the first half of this year, given the go-to-market change but like what more is there to do on your front now that you guys are kind of clicking along here with, call it, 4 months and change behind you?

Yes. Yes, it's a great question. I start with the bid on customers. Yes, so the change we made on the field side was to directly incentivize the land as part of the comp plan. But not only that to actually target a set of high potential customers that we felt were particularly important to land and compensate even more highly for those because those will be worth a lot more to Confluent as they ramp to large consumption. And so what was exciting to us was not only the volume of customers go up but then as you said, yes, those were actually better targeted into that set of high propensity spenders than they had been previously. And that -- I think that's just the direct result of the incentives. And we had that differentiation because as I said, we want to make sure these are high-quality customer additions that we're picking up. And I'll let you take the second half, Rohan.

Yes. On -- Mike, on the second half, we're obviously, -- we saw this was the first quarter of the transformation and Jay called out earlier, the early indications have been very positive, which showed up in our cloud performance for the quarter. And more importantly, when we look at our month 1 and how we are entering Q2, we feel good that some of the momentum has actually carried on to Q2. So that's good. But in general, like we still have a couple of quarters of execution that we need to focus on. But if you ask me how am I feeling? Obviously, what's evident in our Q1 performance and our Q2 guide, which are strong and which we feel are ahead of our expectations. And what that does is the strength in the first half is also derisking our second half from an overall guidance perspective. So overall, where we are, we feel really good with the transformation but at the same time, we still need to execute a couple of more quarters.

Thanks, Mike. We'll take our next question from Derrick Wood with TD Cowen, followed by Bernstein.

Jay, you mentioned having gone through some pricing changes recently. Can you remind us what changes you made and what kind of dividends you're expecting to see as this gets absorbed in the market?

Yes. Yes. There's a set of changes. Some of these that are actually product offerings, which effectively allow better TCO and incentivize the use of our multi-tenant offerings, which are more efficient for us. So we announced freight clusters in Kafka Summit Bangalore. We announced enterprise cluster type, which is a high-performing multi-tenants offering with private networking. We made adjustments to some of the throughput-oriented pricing. So there was a number of changes that came out. All of these were meant to reduce friction in the land and expand process. We've thought about those consumption transformation. A big part of it was changes on the field team, changes in our systems, changes in compensation. But I think going along with that, we felt it was very important that there will not be a ton of product or pricing friction in that land process, right? So if we're trying to tell the team to go sell in a way that gets customers up and going, it can't be the case to get to a reasonable price. There's a 6-month negotiation at the very front door of the process. And so those changes have lined up with that. Why do that? It's ultimately because there's a ton of Open Source Kafka and we want to go soak that up with our cloud offering. We feel that's a very important. So kind of growing the breadth of that customer base that sets us up for all the growth on those customers over time. And we do feel like these kind of changes and new offerings unlock workloads that would have been harder to access, and that comes out of the TCO of the offering, right? We've talked in the past about how Kora is able to really offer a better TCO for customers. And it's important that we make sure we have offerings that cut across all the different workloads they have, so that it's a bit of a no-brainer across everything they do, not just a certain workload type or a certain use case. So that was our goal.

Yes, that's very helpful color. And I don't know, for Jay or Rohan, you guys talked about rebound and digital native consumption trends, wanted to ask about financial services vertical, which is obviously important for you. Just curious what you're seeing there around demand conditions and deal sizes and whether you're seeing much composition change in Platform versus Cloud?

Yes. That's continued to be a strong segment for us. And over the last few years, we have seen a pretty significant ramp-up in Confluent Cloud adoption. And I would say that, that happened first in the smaller banks. And then over time, that spread to some of the largest financial institutions. And they tend to be a little bit slower to start with the new cloud offering. There's actually very substantial security, reliability, scrutiny that goes into the adoption of any part of their stack but increasingly, we're really a great fit for their use cases and it actually allow them to meet the requirements that they have faster if they are trying to build this out themselves. And so we've started to see great adoption of cloud and financial services. I think that's a very promising thing as these very large institutions open up something that has very low friction to consume across their very broad set of use cases. So we're really excited about kind of getting in the front door in a lot of these very large banks.

Thank you. Our next question will come from Peter Weed with Bernstein, followed by Guggenheim.

Obviously, great to see the continued momentum on the Cloud side and the transition to consumption working out kind of as you planned. But I may have missed it, but I feel like we haven't talked very much more on the Platform side, where I think we saw a sequential step down in revenue and I wonder how we should think about some of that a little bit more weakness there and whether or not some of that's cannibalization of people moving to cloud. And so it's just some underlying share shifting or whether or not we should think about like slower growth going forward on that side of the business given that it's an important part of the revenue stream.

Yes, do you want to speak to that, Rohan?

Yes, I'll be happy to take it. Thanks for your question, Peter. Well, when we look at our Confluent Platform performance, we're very pleased actually. We grew 15% year-over-year. And when you generally think about the Platform business, more of as a reminder, what happens is about 20% of total contract value is recognized as license revenue upfront. So what that can do, that can add a little bit of lumpiness in the revenue. Clearly, based on the timing of large deals or the timing of renewals for large deals, those have an impact. But when I take a step back and I look at, say, in the last 12 months for this business, we've been very pleased with the overall momentum. And Jay also called out with respect to product innovation, we launched a Flink on-prem, which is obviously going to help this part of the business as well. So yes, I mean, listen, we've said that Confluent needs to be wherever our data and applications are side. If it's on-prem, we need to be on-prem, if it's in the cloud, we need to be cloud. Just keeping that in mind, we do feel that this is going to be an important part of the business as we look ahead.

All right. We'll take our next question from Howard Ma with Guggenheim, followed by JPMorgan.

Jay, can you talk about some of the alternative options that you're aware of for the transport layer in RAG architectures? I don't believe there's a standard yet. And do you have -- on that point, do you have plans to establish a more formalize reference architecture program for RAG implementations and perhaps broader inference use cases too. And it's really aimed at making Confluent the standard for transport and transformation as well.

Yes, yes. It has been a focus for us kind of evangelizing this architecture because, as you say, it is something that's just coming in kind of formation now. The reality is I don't think that there are great alternatives for real-time data movement, right, outside of Confluent. I would say we have a kind of strong status as a de facto for real-time movement across the enterprise. There is opportunities for customers to just try and build it and batch. There's plenty of batch GTL products. The reality is though for a lot of these use cases, there are interesting questions about the business, and that's really just not good enough. For a lot of these use case, it's something that's customer support related or in other words, driving some aspects of the business where kind of answering without of data information is very likely to wrong relative to what the customer was just viewing. And so we are seeing a real push towards real time. And yes, it's on us to make sure that, that -- as that stack solidifies, we have a permanent position in that.

That's great. And maybe I could slip in one more. Just on the topic of Open Source Kafka conversions. Can you talk about any progress that you're seeing with the Confluent migration accelerator tool, I believe it's called. And it is increasing your wallet share among Fortune 500 and to what extent our partners using that tool?

Yes. We're just ramping that up. So somewhat surprisingly, we haven't had really a focused effort on these migrations. It's been somewhat more one-off customer by customer. And so both in terms of tooling and with our partners, creating a focused effort to move customers over. As you can imagine, in any of these situations where there's kind of a better TCO alternative but some effort that's required to make the switch, you want to reduce as much as possible that effort and make it really easy for customers to get from point A to point B. So I think it's just coming into being down, we believe that will contribute over the next few years.

Thank you. We'll take our next question from Pinjalim Bora with JPMorgan.

Congrats everyone for the quarter. One clarification, help me understand how broad-based was the cloud consumption ramp? I heard it was driven by a select set of customer? So wanted to clarify. And in a way to understand if some of the new AI vendors that you recently added materially contributed in the quarter?

Yes, you want to take it Rohan?

Yes, happy to. Pinjalim, thanks for your question. So when you look at the Cloud performance, I'd put it in maybe two categories, the performance, if I had to call out for Q1. The first one is when you look at our broad base of customers, we did see stabilization in consumption and the net new use cases. And the digital need of segment is inclusive in there. So that's good, that's a broad base of our customer. And the second call out was newer customers. We've seen the ramp-up of these newer customers, I'd say, something that we are very pleased on. And the Gen AI customer that you spoke about is probably in that [ port ] of customers. It's a few of them who've kind of we've run and where the ramp schedule looks in line and we're pretty happy with that. And that's for Q1. And as we enter Q2, most of these trends have continued into month 1 of Q2, which has informed our guidance for Q2 as well. So that's the overall context around the consumption patterns.

One question for you, Jay. We have been picking up on this notion that Flink SQL being SQL, which is most understood by almost every developer, kind of opens up the aperture versus a skilled set of Java developer or something else and bringing in more developers to do more Flink and then Flink additionally drives more Kafka, that kind of creates a little bit of a flywheel. Are you starting to see some of...

I like this question. I mean this question sounds like my answer already. Go ahead. Go ahead.

No, no, no. Please answer.

Are we starting to see that? Yes, we are. Yes, I mean our goal is to open up the full set of APIs. So the first thing we launched was SQL. Our intention is to bring out Java and Python APIs as well. We think they serve differences. There's a set of kind of core applications that will probably always be in these more application-oriented programming languages like Java. There's a set of more dynamic use cases and transformations, which are well suited to SQL. One of the powerful things about Flink is kind of opening up that broad set of tools, all on top of a core engine, I think that's one of the things that's made it the leader in stream processing. And as we do that, yes, our goal is very much to make this easier and easier to use. The -- for a long time, I think it's been the case that customers would prefer real-time data. They would rather work with apps that updated in real time, they reacted in real time, they would rather to connect things in real time. Nobody wants the data to be slow. It's actually just been difficult to do that. So making this really easy is kind of a core way of enabling this. Like there's an obvious benefit if you can make it not more costly and not more complicated for our customers. So when you see us kind of focusing on both this ease of development and TCO orientated things, that really is the kind of core thing that drives this, and as we do we think there's a huge opportunity for this whole set of batch data movement, batch processing that really needs to move and will move as the alternative becomes appealing because of that ease of use in TCO.

As a reminder, the Confluent earnings report is now on our IR website. The report contains our earnings infographic, a 1-pagers on our technology, the prepared remarks and earnings slides from today's call. We encourage you to go and take a look. And today, our final question will come from Miller Jump with Truist Securities.

Right. Great. I'll echo congrats on the strong start. So just -- you talked about the strength in governance and I'm just curious, like is the need to get your data estate ready for AI driving more conversations there? And then maybe if you could just remind us what that opportunity looks like maybe on a unit economics level, if you're spending in dollar on streaming? What does that look like for Governance?

Yes. Yes, it's a great question. So yes, AI is definitely one of the drivers. I would say that there's a whole set of forces that have driven interest in data governance. One of those is just the kind of rising compliance regime around data. GDPR is to start but there's a long list of things that organizations have to do. The second is around just the safety of data. The third is actually around opening it up. Those first two are maybe things you have to do. But in order to really take advantage of data, it has to be the case that the right team can find the right data set, what it means at the right time, that kind of discovery process, documentation is actually really critical to the integrity of data as something that customers can build around and against. And then as you said, all of that, I think, has been supercharged by AI, where you have a set of applications that are much more data rich to draw on many more data sources across an organization than a traditional enterprise app might. But in order for that to work well, you have to know what's going work. And is it up to date? Is it getting there in the right way? Is it supposed to be there at all? And managing all of that has just gotten harder and harder, and managing it on top of some trusty set of old bespoke pipelines is trending towards impossible, and I think that's one of the things that's driven the rise of data streaming. And the nice thing for us is the ability to bring these governance capabilities kind of right there with the Platform. So there's no extra effort to go and adopt this use case by use case. The data is naturally tracked as it flows, you have the lineage of what goes where, you've kind of strong schemas that allow the creation of these data products that are shared across organization. And this is a really powerful thing for customers as they think about how they use this technology in the large and how they really take advantage of the day that they have to better serve customers and be more efficient. And on the unit economics, yes, this will change over time as that product line develops. Right now, it is kind of a step up with some additional usage as you use it more broadly. I think we're adding more and more functionality around the encryption of fields of data around other aspects of how you use and analyze data, and I think that will increase the monetization over time. I think it's too early to call the kind of final pending state ratio probably for any of these offerings but we do think that, that will be a sizable business for us.

That is helpful. And if I could squeeze in one quick one for Rohan. Any gross margin changes to consider as these uses outside of streaming start to scale?

Yes. From a gross margin perspective, what we've said, Miller, is we are essentially long term target at 75-plus percent gross margin. We are operating well above that and it's been consistently above that. So as we look ahead for rest of the year, we expect to be in the zip code of gross margins. So not a whole lot to call out there with respect to any impact one way or the other on gross margins.

All right. Thank for all the questions. This concludes our earnings call today. Thanks again for joining us. Bye, everyone.

Thanks, everyone.