Elastic N.V. (NYSE:ESTC) Q1 2024 Earnings Call Transcript

Elastic N.V. (NYSE:ESTC) Q1 2024 Earnings Call Transcript August 31, 2023

Elastic N.V. beats earnings expectations. Reported EPS is $0.25, expectations were $0.11.

Operator: Good day and welcome to the Elastic First Quarter Fiscal 2024 Earnings Results Conference Call. [Operator Instructions] Please note, today’s event is being recorded. I would now like to turn the conference over to Janice Oh with Investor Relations. Please go ahead.

Janice Oh: Thank you. Good afternoon, and thank you for joining us on today’s conference call to discuss Elastic’s first quarter fiscal 2024 financial results. On the call we have Ash Kulkarni, Chief Executive Officer; and Janesh Moorjani, Chief Financial Officer and Chief Operating Officer. Following their prepared remarks, we will take questions. Our press release was issued today after the close of market and is posted on our website. Slides, which are supplemental to the call can also be found on the Elastic Investor Relations website at ir.elastic.co. Our discussion will include forward-looking statements, which may include predictions, estimates, our expectations regarding the demand for our products and solutions and our future revenue and other information.

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These forward-looking statements are based on factors currently known to us, speak only as of the date of this call and are subject to risks and uncertainties that could cause actual results to differ materially. We disclaim any obligation to update or revise these forward-looking statements unless required by law. Please refer to the risks and uncertainties included in the press release that we issued earlier today included in the slides posted on the Investor Relations website and those more fully described in our filings with the Securities and Exchange Commission. We will also discuss certain non-GAAP financial measures. The disclosures regarding non-GAAP measures, including reconciliations with the most comparable GAAP measures can be found in the press release and slides.

The webcast replay of this call will be available on our Company website under the Investor Relations link. Our second quarter fiscal 2024 quiet period begins at the close of business on Tuesday, October 17, 2023. On September 5, 2023, we will be participating in the Goldman Sachs Communacopia Technology Conference. With that, I’ll turn it over to Ash.

Ashutosh Kulkarni: Thank you, Janice. And thank you all for joining us today. I’m pleased with how we performed this quarter. We had a strong start to our fiscal year, with our performance, exceeding our stated expectations across both revenue and non-GAAP operating margin. In Q1, revenue grew 17% year-over-year, with Elastic Cloud growing 24% year-over-year. We ended the quarter with more than 1,190 customers with annual contract values over $100,000. As customers continue to adopt Elastic as their data analytics platform of choice for addressing multiple real-time search use cases. And we continue to manage the business with discipline to deliver non-GAAP operating margin of 9.9%. Elastic has always had a singular mission, enabling everyone to find the answers that matter, from all data in real-time at-scale.

The versatility of our platform, the built-in AI capabilities such as the Elasticsearch Relevance Engine or ESRE and our ability to excel at multiple real-time use cases across search, observability, and security on our data analytics platform have all made Elastic a natural choice for our customers as a core element of their IT stack. Our land and expand strategy continues to serve us well and our long-term opportunity remains robust. In Q1, we saw two distinct trends within our business. The first is around generative AI. Generative AI and its intuitive approach to interact with massive amounts of information and generate new content is driving a resurgence of excitement around enterprise search. Businesses are recognizing the opportunity to create new customer and employee experiences and drive efficiencies in various business processes through the use of AI-powered search.

This is opening up new opportunities for Elastic. To build generative AI applications that work within their environment and with their proprietary data, businesses need the ability to provide accurate context in real-time to large language models or LLM. And to do so in a way that doesn’t violate their privacy or security policies. This requires a platform that can allow businesses to use their own or third-party ML models to generate embeddings from their data, irrespective of the type of data. Store these embeddings vector store at very large scale and then efficiently search across these vectors in real-time to enhance LLM responses by providing context using retrieval augmented generation. The platform needs to ensure that this vector retrieval enforces data privacy with document-level permissions and takes context, such as user privileges, personalization, geolocation, and other factors into account.

The platform also needs to be flexible enough to enable hybrid search using a combination of vector, symantec, and textual search techniques to ensure the most relevant results possible. Elasticsearch, with ESRE delivers this entire set of capabilities in a single platform. It does so in the same platform that is already being used by tens of thousands of organizations worldwide for real-time search use cases. Our proven scale, performance, and advanced enterprise features like document level permissions, built-in security, and hybrid search with Reciprocal Rank Fusion, makes us a highly differentiated an ideal choice for these generative AI use cases. In Q1, we saw significant activity around generative AI with the number of customers choosing ESRE as their platform for building generative AI applications, using our vector search and hybrid search capabilities.

As an example, a U.S.-based Fortune 100 global media and technology company has integrated as ESRE with their own locally hosted large language model to enable their ticketing system to now deliver contextual answers to questions from their customers. This is projected to enable their team to solve about 50% of their helpdesk tickets through this automation, made possible by the power of generative AI. Another example is a leading file-sharing service that is using Elastic’s hybrid search capabilities to power a new AI-powered universal search tool. The combination of vector search and textual search, enables them to bring a significantly superior search experience to their customers across all subsidiaries and applications. With Elastic generative AI and machine-learning capabilities at its core, its tool learns and evolves alongside its users, continuously improving as they use it.

Another example is the leading AI platform Labelbox that uses Elastic to power one of its most popular tools, Labelbox catalog, enabling teams to accelerate and streamline machine-learning model development through optimized search experiences. With Elastic fast and rich search capabilities, Labelbox customers can undertake unstructured data searches in a fraction of the time compared to its previous search solution, which ultimately helps them to capitalize on the possibilities of AI. Similarly, companies are also using Elastic to enable things like forensic video analysis at scale. One leading telecom equipment company is using their own large language model coupled with Elastic vector search capabilities to power their cloud-based video Search solution, enabling them to better identify bad actors and provide real-time security.

These are just a few of the many examples of customers using us for generative AI today. Elasticsearch is the most popular platform for search and as customers build contextual generative AI applications, they are naturally choosing Elasticsearch and ESRE to provide relevance and context based on their private data. Today, we have hundreds of paying customers using ESRE for vector search. And the conversations we’re having with our customers gives us confidence about our continuing traction in this space. We anticipate that as customers start to put more and more of these use cases into production, generative AI will be a real tailwind for our business. The second distinct trend in our business is the continued push by customers to consolidate onto the Elastic platform for multiple use cases.

In Q1, customers continued to make large multi-year commitments as they sought ways to lower their total spend without sacrificing innovation by bringing more workloads from other incumbent solutions onto Elastic. We continue to leverage our competitive strengths in our core areas of search, log analytics, and security analytics to drive our land and expand strategy. As an example, in Q1, we closed a multi-year deal with Texas A&M University for Elastic Cloud on AWS. The university previously deployed a competitor’s solution, but moved to Elastic for security and observability. The customer chose Elastic for ease-of-use of a single platform without needing multiple licenses. And search results in high speed and relevance for all their data, enabling them to rapidly and effectively solve their business challenges.

They use Elastic to search through analyze and secured all of their data from a unified platform, while optimizing costs and meeting compliance requirements. We also closed a multi-year deal for Elastic observability with one of the largest multinational communications and entertainment companies in the world. They started with a small deployment of Elastic next to a competitor’s solution, but consolidated onto Elastic to become the enterprise standard for its observability platform. This company chose Elastic for its flexibility and scalability across different data types and leverages advanced features such as searchable snapshots and machine-learning to help them taken AIOps approach to the data they’re ingesting into Elastic. This quarter, we also renewed and expanded business with one of the world’s leading Internet domain registrar and web hosting companies.

A long-time Elastic customer, the company previously used a competitor solution, but moved to Elastic and in Q1 signed a multi-year contract for Elastic Cloud on AWS. The company has consolidated multiple tools across logs, metrics, and APM in Elastic observability to effectively monitor thousands of online services for customers, while reducing meantime to resolution and streamlining operational costs as its business continues to scale. As we have discussed previously, our customers routinely tell us that our platform delivers a much higher value than competitive offerings and these advantages along with our innovative AI-power data analytics platform are enabling us to compete very well in this environment. Now, onto our products, in Q1, we continued our focus on innovation and delivered on several key capabilities to our platform and our solutions.

One of the most significant announcements in Q1 was the release of the Elastic AI-Assistant powered by ESRE. This AI-Assistant, which helps guide analyst investigations and remediation is in beta for security and in technical preview for observability. We continue to enhance capabilities in ESRE and delivered new hybrid search capabilities with the industry-leading implementation of Reciprocal Rank Fusion or RRF to combine vector, keyword, and semantic techniques for better results. We’re also continuously improving the speed and performance of the Elasticsearch platform. And we did work in Q1 in this area, that resulted in faster and more relevant outcomes for search aggregations for cross-cluster search and for dense vector search. This included support for native implementations of vector search using hardware-accelerated SIMD instruction sets, which yields even faster queries and 30% greater indexing throughput.

In the area of Elastic observability, we integrated our Time Series Data Streams or TSDS capability with popular Elastic observability integrations, such as Kubernetes, Nginx, AWS Kinesis, and Lambda, enabling the potential to reduce storage needed for metrics data by up to 70%. In the area of Elastic Security, we extended support for advanced entity analytics with the general availability of lateral movement detection. On the go-to-market front, we continue to focus on our partnerships with the major cloud hyperscalers, and I’m pleased to highlight that we recently earned top accolades from each of the three hyperscalers Microsoft, AWS, and Google Cloud. Specifically, we were named the Microsoft Commercial Marketplace Partner of the Year and the AWS U.S. ISV Rising Star Partner of the year.

And just this week, we were honored to receive the Google Cloud, Global Technology Partner of the Year award. These awards from all the three cloud hyperscalers are a reflection of the strength of our relationships with these cloud partners. The deep product integrations, we have built with them and the success we are achieving together in driving growth for our businesses in the market. Customers are making significant multi-year commitments to our platform through these cloud marketplaces as they leverage Elastic, as an AI-powered data analytics platform for multiple real-time use cases across search, observability, and security. Finally, I would like to again highlight that Q1 was a continued demonstration of our commitment to managing the business with discipline.

We delivered a non-GAAP operating margin of 9.9% for the quarter, which was significantly better than our expectations and we remain on-track to deliver on our non-GAAP operating margin target for the full fiscal year. In closing, I want to thank our team for their dedication and continued focus in execution. I also want to thank our customers, partners, and investors for their continued support and confidence. Our conviction in the long-term opportunity in front of us remain strong. It is based on the strength of our relentless innovation and continued customer confidence in Elastic. Generative AI is opening up new opportunities for us that we expect to capitalize on in the coming quarters and years. And as cloud optimization is stabilizing, we expect to continue making progress on our stated goal of driving growth with profitability.

With that, I’ll turn it over to Janesh to go through our financial results in more detail.

Janesh Moorjani: Thanks, Ash. We are very pleased with the strong results that we delivered in the first quarter, marking an excellent start to the new fiscal year. We once again came in above the high end of our guidance for the quarter for both our topline and our bottom line. In Q1, we delivered 17% year-over-year growth in total revenue with Elastic Cloud yet again driving our results with 24% year-over-year growth. Importantly, we delivered non-GAAP operating margin of 9.9%, demonstrating both our strong investment discipline and the operating leverage inherent in our business model. As Ash mentioned, we saw increased engagement around generative AI use cases in the first quarter, which led to customer dialogue at the highest levels with the C-suite being deeply engaged on the topic.

Our advanced capabilities enable customers to build generative AI solutions, leveraging the benefits of our data analytics platform including its native vector database capabilities as they address multiple real-time search use cases. And this positions us exceptionally well to be a leader in generative AI long-term, which we believe will ultimately drive meaningful revenue for us in the coming years. We also saw continued strong contractual commitments during the quarter, particularly among our larger customers as they consolidated use cases on Elastic and benefited from the value of our platform. In addition, we began to see signs of improvement in consumption patterns as customers increase their consumption against the commitments that they had previously made.

We will monitor this ramp against the backdrop of broader consumption optimization trends, which still might take a couple of quarters to play out, but we are pleased with the early signs we saw during the quarter. As we look out over the rest of the year, we continue to expect that the compelling value proposition for customers of our platform, combined with the strong engagement we’ve seen for generative AI will drive our overall business momentum. Let’s get deeper into the results for Q1 and our outlook. Total revenue in the first quarter was $294 million, up 17% year-over-year on an as reported and constant currency basis. Subscription revenue in the first quarter totaled $270 million, up 17% year-over-year, or 16% year-over-year in constant currency, and comprised 92% of total revenue.

Within subscriptions, revenue from Elastic Cloud was $121 million, growing 24% year-over-year on as reported and constant currency basis. Elastic cloud represented 41% of total revenue in the quarter, up from 39% a year ago. Elastic Cloud revenue based on month-to-month arrangements contributed 15% of total revenue compared to 16% in the prior quarter. Professional services revenue in the first quarter was $24 million, growing 29% year-over-year on an as reported and constant currency basis. Although professional services may fluctuate across quarters based on the timing of services delivery, we do not expect it to vary significantly in mix over time. To add more context around overall deal flow. EMEA grew fastest during the quarter, followed by the Americas, and APJ.

We continue to see a healthy balance across the business based on geography, solutions, and verticals and this diversification reflects the breadth and popularity of our platform. Moving on to customer metrics. We ended the quarter with over 1,190 customers with annual contract value is more than $100,000. Looking at customer additions more broadly, we ended the quarter with over 4,170 customers above $10,000 in ACV and approximately 20,500 total subscription customers. Our net expansion rate, which as you know is a lagging indicator was approximately 113% in-line with our expectations for the quarter and consistent with our prior comments. Overall, customers continue to adopt Elastic as their AI-powered data analytics platform of choice for addressing multiple real-time search use cases.

Customers across industries and across the globe are adopting and growing on Elastic, particularly Elastic Cloud and we remain excited about the opportunity ahead of us. Now turning to profitability for which I’ll discuss non-GAAP measures. Gross margin in the quarter was 76.5% versus 76.3% in the prior quarter. I’m very pleased with how the team managed discounting in the field during the quarter and also drove efficiencies in running our operational infrastructure. Our operating margin in the quarter was 9.9%, which was better than expected. The strong operating margin performance was driven by our revenue outperformance and our continued focus on managing our expenses. Diluted earnings per share in the first quarter was $0.25. Free cash flow on an adjusted basis was $49 million in the quarter or 17% adjusted free cash flow margin.

This represents our highest adjusted free cash flow margin to date, as we continue to drive operational focus in the business. The strength in adjusted free cash flow was partly due to timing benefits of approximately $20 million, primarily related to the timing of cash collections and payments that we had previously expected in the second quarter, but occurred during the first quarter. Looking at the adjusted free cash flow outlook for the second quarter, this timing of cash flow, shifting from Q2 to Q1 will impact adjusted free cash flow in Q2. Additionally, we anticipate $13 million of one-time payments that relate to previously completed acquisitions that will be due in the second quarter. Although we don’t usually provide a specific quarterly outlook on cash flow, given some of the puts and takes in Q2, I’ll share that we expect adjusted free cash flow in the current quarter to be in the range of approximately negative $10 million to breakeven, reflecting these two items.

As we’ve said before, cash flow on a quarterly basis will fluctuate given timing issues around inflows and outflows, as well as seasonality impacts. So we continue to look at cash flow primarily on a full-year basis. For the full fiscal year, there is no change in our prior outlook and we continue to expect free cash flow margin on an adjusted basis for fiscal ’24 to be slightly above the non-GAAP operating margin for fiscal ’24. We continue to maintain a strong balance sheet. We ended the first quarter with cash, cash equivalents, and marketable securities of $957 million. Turning to guidance, while we were very pleased with our outperformance in Q1, we continue to be prudent as we plan for the rest of the year. The macroeconomic climate has been stable, so we continue to assume that macroeconomic conditions will remain unchanged.

Additionally, although we are seeing customers ramp their consumption for the new workloads we’re consolidating onto Elastic, we believe it is appropriate to anticipate that consumption patterns may continue to fluctuate in the near term. Accordingly, we are raising the low end of our total revenue guidance for the full fiscal year by $4 million at this time, resulting in an increase of $2 million at the midpoint. Since it is still early for us in the fiscal year, we are going to monitor these trends for another quarter before further evolving our outlook. In terms of operating expenses, we continue to invest with discipline in the business. Over the past several quarters, we’ve continued to drive efficiency in the business and that focus will not change.

At the same time, we see an opportunity to invest in development and marketing around generative AI as we solidify our leadership in this space. We continue to balance investing for growth against profitability and we’ll carefully monitor our progress each quarter. We are raising our non-GAAP operating margin guidance by 25 basis points at the mid-point at this time. For both fiscal ’24 and fiscal ’25, we expect to grow revenue faster than overall expenses, expanding our non-GAAP operating margin each year. With that background, for the second quarter of fiscal ’24, we expect total revenue in the range of $303 million to $305 million, representing 15% year-over-year growth at the midpoint or 13% on a constant currency basis. We expect non-GAAP operating margin for the second quarter of fiscal ’24 in the range of 9.5% to 10% and non-GAAP earnings per share in the range of $0.23 to $0.25 using between 101.5 million and 102.5 million diluted weighted average ordinary shares outstanding.

For full fiscal ’24, we expect total revenue in the range of $1.242 billion to $1.25 billion, representing 17% year-over-year growth at the midpoint or 16% on a constant currency basis. We expect non-GAAP operating margin for full fiscal ’24 in the range of 10% to 10.5%, and non-GAAP earnings per share in the range of $1.01 to $1.11, using between $102 million and $104 million diluted weighted average ordinary shares outstanding. In summary, we had a strong start to the year, we are executing well and we are excited about the rest of this fiscal year and beyond. And with that, let’s go ahead and take questions. Operator?

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Q&A Session

Operator: [Operator Instructions] And our first question today comes from Pinjalim Bora with JPMorgan. Please go ahead.

Unidentified Analyst: Hi guys, this is [Noah] on for Pinjalim. Thanks for taking our questions. Just curious if you could maybe expand on the performance of both the observability and security practices and how that’s stacking up against the competition at this point and I just had a quick follow-up. Thanks.?

Ashutosh Kulkarni: Yes, this is Ash here, I can take that. Thanks for that question. So in terms of our ability to compete and differentiate in the market on both observability and security that continues to stay very strong. Just – even in this quarter like I talked about, one of the trends that we’re seeing in the business is continued consolidation onto our platform, a lot of those consolidations tend to be around observability and security. The examples that I gave in my prepared remarks were around that. The capabilities that we’ve been delivering in this area, especially the – some of the newer AI-Assistant functionality for security, what’s in beta now and it’s an early preview for observability, those are driving a lot of excitement in our customers as they see not just the functionality that we’ve built, but the way we can help them take advantage of generative AI and do things in a very differentiated manner, really analyze all their data and get insights that other platforms aren’t able to give them like that’s continuing to play well towards our strengths.

So the win rate continues to be very strong and I’m very excited about both these segments for us.

Unidentified Analyst: Thanks. And then just a quick second question, it sounded a little bit more incrementally positive around the consumption trends you’re seeing so far and totally understand – the understanding that there could be still some fluctuation for the remainder of the year, but how are you sort of thinking about that as you update the guidance for the rest of the year? Thanks.

Janesh Moorjani: Yes, I can take that. So, look, the way we think about the guidance for the year, as I mentioned, it’s relatively early for us. We are very happy with the momentum that we saw in Q1. The quarter played out nicely for us across the topline, across the bottom line. But as I said earlier, because it’s still a little bit early in the year, we think the best thing to do at this stage is just to continue to be prudent. We continue to guide based on what we know and we also continue to build in some protection for the things that we don’t know. And although we saw some positive signs of customers ramping here in Q1, it’s conceivable that consumption may fluctuate in the near term. So we just think it’s best to consider that possibility in our guidance.

And that’s what we’ve done here for Q2 and for the full year. And beyond Q2, as I look out to the back half of the year, we don’t anticipate any worsening in the second half. We simply want to be measured in our approach to the full year outlook, since it’s early in the year. So given the results that we had here in Q1, which were quite strong, we raised the guidance by $4 million on the low end as you saw, because we no longer likely – we no longer see the likelihood that will end at that lower-end of the range. So that’s why we raised the bottom end of the range. We’re looking forward to Q2 and the rest of the year and we’ll update you again on the next call.

Operator: Thank you. And our next question today comes from Tyler Radke at Citi. Please go ahead.

Tyler Radke: Yes, thank you very much for taking the question. Great to hear about the hundreds of customers using the new ESRE product. Could you just talk about the monetization of that? I know there’s kind of several ways you can monetize in terms of being on the enterprise and having to turn on some of the ingestion capabilities. But how significant could that be in terms of driving revenue? Would you expect to kind of see the impacts this year or is this more of a next year event? Thank you.

Ashutosh Kulkarni: Thanks for the question, Tyler. I can – I’ll all address that. So, this is Ash here. So, as you think about our consumption model, the way you should think about it is, as customers use the ESRE functionality, they’re doing multiple machine-learning tasks in there. They’re effectively taking their data and then turning them into Vector Embeddings, they’re storing that data and then using our vector search functionality. They’re using things like Reciprocal Rank Fusion for hybrid search, combining that vector search with semantic search and textual search So all of this tends to be – especially the machine-learning stuff tends to be quite compute-intensive. So that is one aspect. The second aspect is for machine learning, you have to be on one of our premium tiers, so either the Platinum or the Enterprise tier.

So both of those tend to be ways in which the consumption grows. The second is what I’d say is, as you think about where customers are in this journey, first and foremost, it is beyond exciting, right? So generative AI and the possibility of the kinds of experiences that you are able to deliver to your employees to your customers and to do it in such a way that improves the efficiency of business processes, reduces your cost, this is absolutely a C-Level discussion, the kinds of conversations that we’ve been having, it’s accelerating. It’s really driving a resurgence for search in so many different ways and just in the conversations that I’m having with customers, it’s becoming very clear that everybody is looking for ways to do this in different domains across their company.

Now where they are starting in most cases is with internal facing applications, applications that their employees might be accessing, which gives them a little bit of control over things, allows them to make sure that they really get comfortable with the large language models in the generation functionality, all of these capabilities are relatively new. So that’s where we are. As more and more workloads go into production, as the volumes of data in these systems, grows all of that is also going to drive the consumption and the revenue that comes from it. So in terms of the way we are looking at it, the way I look at it, we are very early in the journey. The hundreds of customers that we have today just gives me tremendous confidence and the traction that we’re seeing, gives me tremendous confidence in our ability to continue to be a strong leader and to see this become a real tailwind for us in the coming quarters and years.

Janesh, I don’t know if you want to add anything in terms of how you’re looking at this?

Janesh Moorjani: No, I’ll just reiterate the same level of excitement around the opportunity that you mentioned. When – I hear from customers, our salespeople, folks out there, the level of excitement around gen AI is just tremendous. So I think it’s a great long-term potential revenue opportunity for us.

Tyler Radke: Great. And Janesh, just on the macro environment, it sounded like you saw some encouraging signs of stabilization and improvement. Could you just give us a sense on how the linearity of the quarter played out and have those stabilizing or improving trends continued in August? Just any comment on kind of the timing of when you saw that and obviously, we’re not calling the bottom, but just if there a kind of been consistent in August? Thank you.

Janesh Moorjani: Yes. Tyler as you know, linearity within the quarter can always be affected by the timing of specific deals and this time was no different. I think we did really well to close the business that was on the table before the end of the quarter. With respect to the consumption patterns that we saw, again, we saw consistency during the quarter. In any given month, we did see some customers go up and down, but looking at consumption trends on a monthly basis, it can be a little bit noisy. But overall, the themes played out as we described in terms of the customers starting to consume nicely against the contracts that they had previously committed to. And in terms of August. I think it’s just too early to tell, we haven’t even closed August yet, but I will share that the general tone of customer conversations that we’ve seen has stayed similar to Q1 with a lot of interest in gen AI.

Tyler Radke: Great. Thank you.

Operator: Thank you. And our next question today comes from Koji Ikeda with Bank of America. Please go ahead.