Elastic Q1 2024 Earnings Call Transcript

Quartr
Provided by Quartr
August 31, 2023

There are 11 speakers on the call.

Operator

The versatility of our platform, the built in AI capabilities such as the Elasticsearch Relevance Engine or Esrei 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 2 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.

Operator

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 LLMs 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 in a 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.

Operator

The platform also needs to be flexible enough to enable hybrid search using a combination of vector, semantic and textual search techniques to ensure the most relevant results possible. Elasticsearch with Esray 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 and ideal choice for these generative AI use cases. In Q1, we saw significant activity around generative AI with a number of customers choosing Esre as their platform for building generative AI applications using our vector search and hybrid search capabilities.

Operator

As an example, a U. S.-based Fortune 100 Global Media and Technology Company, has integrated 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 help desk 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.

Operator

With Elastic's 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's 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. 1 leading telecom equipment company is using their own large language model coupled with Elastic's vector search SRAE capabilities to power their cloud based video search solution, enabling them to better identify bad actors and provide real time security.

Operator

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 SRAE to provide relevance and context based on their private data. Today, we have 100 of paying customers using Esre for vector search and the conversations we are 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.

Operator

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 multiyear 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 strength 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 multiyear deal the Texas A&M University for Elastic Cloud on AWS. The university previously deployed a competitor solution, but moved to Elastic for security and observability.

Operator

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 secure all of their data from a unified platform while optimizing costs and meeting compliance requirements. We also closed a multiyear deal for Elastic Observability with 1

Speaker 1

of the

Operator

largest multinational communications and entertainment companies in the world. They started with a small deployment of Elastic next to a competitor 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 take an AIOps approach to the data they're ingesting into Elastic. This quarter, we also renewed an expanded business with 1 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 multiyear contract for Elastic Cloud on AWS.

Operator

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 mean time 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 powered data analytics platform, are enabling us to compete very well in this environment. Now on to our products. In Q1, we continued our focus on innovation and delivered on several key capabilities to our platform and our solutions.

Operator

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 SRAE 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 are also continuously improving the speed and performance of the Elasticsearch platform. Form.

Operator

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.

Operator

And I'm pleased to highlight that we recently earned top accolades from each of the 3 hyperscalers Microsoft, AWS and Google Cloud. Specifically, we were named the Microsoft Commercial Marketplace Partner of the Year and the AWS US 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 3 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.

Operator

Customers are making significant multiyear 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 on execution. I also want to thank our customers, partners and investors for their continued support and confidence.

Operator

Our conviction in the long term opportunity in front of us remains 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 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.

Speaker 1

Thanks, Ash. We are very pleased with the strong results that we delivered in the Q1, 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 top line 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.

Speaker 1

As Ash mentioned, we saw increased engagement around generative AI use cases in the Q1, 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 commitments that they had previously made.

Speaker 1

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 Q1 was $294,000,000 up 17% year over year on an as reported and constant currency basis. Subscription revenue in the Q1 totaled 2 $70,000,000 up 17% year over year or 16% year over year in constant currency and comprised 92% of total revenue.

Speaker 1

Within subscriptions revenue from Elastic Cloud was $121,000,000 growing 24% year over year on an 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 to month arrangements contributed 15% of total revenue compared to 16% in the prior quarter. Professional services revenue in Q1 was $24,000,000 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.

Speaker 1

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 1190 customers with annual contract values 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 expectation for the quarter and consistent with our prior comments.

Speaker 1

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 see is in running our operational infrastructure.

Speaker 1

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 Q1 was $0.25 Free cash flow on an adjusted basis was $49,000,000 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 $20,000,000 primarily related to timing of cash collections and payments that we had previously expected in the Q2, but occurred during the Q1.

Speaker 1

Looking at the adjusted free cash flow outlook for the Q2, this timing of cash flow shifting from Q2 to Q1 will impact adjusted free cash flow in Q2. Additionally, we anticipate $13,000,000 of one time payments that relate to previously completed acquisitions that will be due in the Q2. 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 $10,000,000 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.

Speaker 1

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 2024 to be slightly above the non GAAP operating margin for fiscal 2024. We continue to maintain a strong balance sheet. We ended the Q1 with cash, cash equivalents and marketable securities of $957,000,000 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.

Speaker 1

Additionally, although we are seeing customers ramp their consumption for the new workloads they are consolidating onto Elastic, we believe it is appropriate to pay 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 $4,000,000 at resulting in an increase of $2,000,000 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.

Speaker 1

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 5 basis points at the midpoint at this time. For both fiscal 2024 and fiscal 2025, we expect to grow revenue faster than overall expenses, expanding our non GAAP operating margin each year. With that background for the Q2 of fiscal 2024, we expect total revenue in the range of $303,000,000 to $305,000,000 representing 15% year over year growth at the midpoint or 13% on a constant currency basis.

Speaker 1

We expect non GAAP operating margin for the Q2 of fiscal 2024 in the range of 9.5 percent to 10% and non GAAP earnings per share in the range of 0.25 dollars using between $101,500,000 $102,500,000 diluted weighted average ordinary shares outstanding. For full fiscal 2024, we expect total revenue in the range of $1,242,000,000 to $1,250,000,000 representing 17% year over year growth at the midpoint or 16% on a constant currency basis. We expect non GAAP operating margin for Esrei, using between 102,000,000 and 104,000,000 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.

Speaker 1

And with that, let's go ahead and take questions. Operator?

Speaker 2

Thank you. We will now begin the question and answer And our first question today comes from Pinjalim Bora with JPMorgan. Please go ahead.

Speaker 3

Esray. Hey, guys. This is Noah on for Penjal, and 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 backing up against the competition at this point? And I just had a quick follow-up.

Speaker 3

Thanks.

Operator

Yeah, 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 are seeing in the business is continued consolidation onto our platform.

Operator

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 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 and towards our strength. So The win rate continues to be very strong, and I'm very excited about both these segments for us.

Speaker 3

Thanks. And then just a quick second question, but 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 are you sort of thinking about that as you update the guidance for the rest of the year? Thanks.

Speaker 1

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 top line, across the bottom line.

Speaker 1

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 it's 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.

Speaker 1

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 $4,000,000 on the low end, as you saw, because we no longer likely we no longer see the likelihood that we'll end at that lower end of the range. So that's why we raised the bottom end of the range.

Speaker 1

We're looking forward to Q2 and the rest of the year, and we'll update you again on the next call.

Speaker 2

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

Speaker 4

Yes. Thank you very much for taking the question. Great to hear about the hundreds of customers using the new Esri 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.

Speaker 4

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.

Operator

Thanks for the question, Tyler. I can I'll 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.

Operator

They're storing then 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. And 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 tier, so either the platinum or the enterprise tier.

Operator

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. 1st and foremost, it is beyond exciting, right? So generative AI and the possibility of the kinds of experiences that you're able to deliver to your employees, to your customers, and to do it in such a way that it improves the efficiency of your business processes, reduces your cost. This is absolutely a you know, C level discussion, the kinds of conversations that we've been having, it's exhilarating.

Operator

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 Control over things allows them to make sure that they really get comfortable with the large language models and the generation functionality. Now all of these capabilities are relatively new. So that's where we are.

Operator

As more and more Clothes 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 are 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 years. Janesh, I don't know if you want to add anything in terms of how you're looking at this.

Speaker 1

No. I'll just reiterate the same level of excitement around the that you mentioned. When I hear from customers, our sales people, 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.

Speaker 4

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 comments on kind of the timing of when you saw that? And obviously, you're not calling the bottom, but Just if those have kind of been consistent into August.

Speaker 4

Thank you.

Speaker 1

Yeah, Tyler, as you know, linearity within the quarter can always be affected by the I mean 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 seek some Esray, 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, right, in terms of the customers starting to consume nicely against the contracts that they had previously committed to.

Speaker 1

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

Speaker 5

SRAE.

Speaker 6

Thanks for taking the questions. I wanted to ask a question digging into the Elastic Cloud revenue growth here of 24%, Really strong number there. But when looking at the monthly cloud revenue, that grew, looks like about low single digits. And then the net new customer adds the 100 ks ACV, that number was a bit lower than in prior quarters. So just kind of thinking through Elastic Cloud, does that mean that the growth or the strength there is coming from customers below 100 ks or is SRAE?

Speaker 6

That are well above 100 ks that's driving that cloud strength. Maybe it's a combination of both, just looking for some more color here.

Speaker 1

Yes. Koji, there's a couple of elements in there that you talked about in terms of monthly cloud as well as the customer sizes. So let me try and unpack both of those for you. In terms of monthly cloud, the monthly cloud business, as you know, is predominantly our self-service motion and the majority of that is SMB. That continued to be stable compared to the past couple of quarters.

Speaker 1

It was not meaningfully different, so neither better nor worse. And that was as we expected. So we anticipated those results. What you're really seeing in the mix there is that our annual cloud subscription motion has actually performed really well. We talked about the increase in consumption that we started to see from the consolidation of workloads and that's all reflected in the annual cloud revenue.

Speaker 1

And then that then drives the mix of revenue. So our strategy to focus on customers that have the higher propensity for growth is working quite nicely. We are seeing those customers expand. We are seeing them make larger commitments. And I think that's actually been working quite nicely for us.

Speaker 1

And then if I look at the customer metrics for more than 100 ks, Again, when I maybe just step back and look at the overall results for the quarter, the overall numbers were really strong for us in terms of both total revenue as well as cloud growth. But in terms of the customer accounts, we saw, as Ash mentioned earlier that customers are continuing to make strong contractual commitments to Elastic. Although the additions to that pool of greater than 100 ks ACV was a little bit lighter, we did see strong expansion in the larger accounts and that reflects those commitments. So from a dollar perspective, we saw strength there too. And the number of net adds in any quarter, it might move around a little bit, but the underlying drivers continue to remain strong.

Speaker 1

And so that's very consistent with the theme of consolidation that we talked about on the continuing commitments from these customers gives us a lot of confidence in our outlook for Q2 and the rest of the year. So I think we've had good consistent growth in our customer metrics historically and we expect that that trend will continue over time.

Speaker 6

Got it. Thanks so much, Janesh. And just one follow-up here. Looking at net revenue retention of 113%, Is it too early to call a potential bottom or how do we how should we be thinking about visibility into the bottom of net revenue retention going forward?

Speaker 1

Yes, the net expansion rate in the Q1, it moved as we had expected it would. You recall that we had covered this on the prior earnings call as well and where we had said that we would expect it to go down. And I think the decline in the net expansion rate reflects the two themes that we mentioned earlier on commitments and consumption. So for cloud contracts, commitments generally don't count towards the net expansion rate, while consumption does. So the strong commits are not in the number, but the slower consumption is.

Speaker 1

And then over time, as the consumption against the committed contracts ramps, that will naturally help the net expansion rate over time. If I think about that from a different angle, our gross retention rates remain very strong and we didn't see any change versus the by the quarter. So the slower net expansion rate has been from slower expansions. So as I mentioned, as that the consumption against committed contracts ramps that will naturally help the expansion number. And finally, as you know, the net SRAE.

Speaker 1

Expansion rate is a lagging indicator. It's a trailing 12 month measure. So as consumption ramps, it will take some time for that to be fully reflected in the net expansion rate. We'll continue to monitor that as we go. But so far, it's playing out as we had previously predicted.

Speaker 6

Very helpful. Thank you so much for taking the questions.

Speaker 2

Thank you. And our next question today comes from Jake Roberge with William Blair. Please go ahead.

Speaker 7

Hey, thanks for taking my questions and congrats on the great results. Just going back to those hundreds of paying customers using Esri and Vector Search, How would you characterize kind of the profile of those customers? Are you seeing that more from existing customers kind of upgrading platform SKUs and lifting Or is that actually starting to drive some new logo activity to Elastic as well?

Operator

Yes. So we are seeing a mix of both, right? So keep in mind that our motion has always been a land and expand motion. New customers come to Elastic, typically onto, Elastic Cloud using the monthly description motion, as they start to use us for new use cases and as they grow, seeing the propensity to grow, we will engage with them and then move them to an annual contract and they sort of continue to expand from there. That motion remains consistent.

Operator

Even in the monthly cloud use cases that we are seeing, we are seeing customers use us for generative AI use cases that I mentioned. The examples that I gave were all customers using us with annual contracts, right, so in my prepared remarks. And keep in mind that when you think about the value that we bring in the area of generative AI, what I'm hearing from customers is that really there are 4 key reasons why we tend to win and why we tend to do very well. First is, we simply have a really, really good vector database implementation. It performs very well.

Operator

It scales incredibly well and that's something that is key to success and so our customers are appreciating it. The second thing is We've invested a lot in making sure that we don't just stop at a vector functionality, a vector implementation, but we have invested in capabilities like reciprocal rank fusion for hybrid search. We've invested in functionality that allows you to incorporate context in all the search functionality needed for retrieval augmented generation using personalization, using geolocation, etcetera, as context. The third big reason is we keep hearing about the fact that The enterprise class capabilities like document level permissions, like built in security that we've implemented is something that is critical for actually putting these use cases into production. And that's an area where many others are It's an afterthought for them or they haven't implemented it.

Operator

And lastly, and this maybe comes back full circle to the point, the question that you had asked, We have a position in the market where most customers, all our customers, obviously, but Also a large number of people outside of our customer base are already using Elasticsearch for some form of search or another. And that just means that there is tremendous familiarity. Their data is already sitting in some Elasticsearch instance. So if you are an Elasticsearch user, it's just a natural thing for you to look to us for this kind of functionality. So that doesn't mean that We aren't getting new logos, like I said, because there's a massive Elasticsearch community out there that might not be paying us today.

Operator

They might be using the free version. But that's really the source of our success. And in some of the conversations that I'm having, a Fortune 100 company, We just recently talked to them and they told us that they evaluated vector capabilities across all the vendors out there did a very detailed evaluation and they were just blown away by what they saw Elastic bringing to the table. So Lots of good traction, lots of good momentum across the broad market. Many of these are existing customers, but also new customers that have had familiarity with Elasticsearch looking to us for this.

Speaker 7

Great. That's very helpful. And then when we think about the numbers, When do you think that those apps will actually go live into production and drive potentially more meaningful consumption of the platform? Do you think that's a Q4 4 story or more of a fiscal 2025 dynamic? And then on the margin side, are there any incremental AI investments that we should be just thinking about when it comes to modeling?

Operator

Yes. So let me maybe touch upon the first question first. In terms of many of these use cases are already in production, right. So the examples that I gave in my prepared remarks, but even beyond that, there are customers who have spoken publicly together with Elastic on behalf of Elastic. Just earlier this week at the Google Next event, Cisco co presented with us and talked about The work that they have done on building an internal search application that goes across over 50 internal applications, They have some wonderful stats of what they were able to do in terms of saving hours for their support engineers and making their job heck of a lot easier and better.

Operator

So there are lots of production use cases already. I think what's important to understand is when does this become a big enough customer group that's in production with data having grown to scale that this shows up as a major tailwind. And I we feel very confident that that's going to happen in the coming quarters years. But discretely, we are not looking at that as a significant impact for fiscal 2024.

Speaker 1

Yes. And just to touch on the investments real quick. I mentioned earlier in the prepared remarks that we are increasing some of our investments in Gen AI, clearly oriented towards marketing and development. And that's all reflected in the operating margin guidance for the full year that I provided. Within that, you'll see that if you look at the total spending that was implied in our model for the full year at the start of this year and you compare that to the total spending implied in the guidance in the current guidance that we are providing, it's about the same in the aggregate.

Speaker 1

So what we're really doing is being efficient and saving in some parts of the business to create room to invest in growth areas like Gen AI and that's what you see reflected in the guide.

Speaker 2

SRAE. And our next question today comes from Matt Hedberg with RBC Capital Markets.

Speaker 5

Yes. Thank you. This is Matt Swanson for Matt Hedberg, and I'll echo my congratulations as well. Ash, we kind of focused On two things during the prepared remarks, it was the Gen AI and then the consolidation. And I was wondering if you could just talk to maybe how interrelated These two things are now or maybe in the future.

Speaker 5

Basically, when you're having those C level conversations, how much does Gen AI and things like vector search come up in terms of who they want to consolidate to when they're trying to kind of future proof these decisions?

Operator

That's a great question. And the way I look at it is effectively, Gen AI and the very differentiated capabilities we are able to provide is really helping us in a significant way, which is brand recognition with a C level audience that Generally, in the past, we've not had too many conversations with. And that is a wonderful thing, because that then allows us to continue that discussion of the platform story and how there are so many things that when it comes to real time search use cases, whether it be for observability or security as well, we can add tremendous value to their organization by becoming a key element of their IT infrastructure. And that's really something why I believe that The Gen AI tailwind as this builds up in the coming quarters years is going to be very meaningful for us because it will affect everything that we are able to do with the platform, including the work that we do in observability and security.

Speaker 5

That's helpful. One other thing we talked about was the time to value being kind of a Core value proposition. And when thinking about new products or advancements like the time series data streams and the cost savings for storage, Could you just talk about in this macro how important ROI is in customer conversations and maybe if that's Influencing either product development or the broader go to market?

Operator

Yes, absolutely is incredibly important. So we have seen, as Janesh mentioned, stabilization in sort of the consumption optimizations that we had seen in prior quarters. But the reality is that customers even today care about making sure that they are spending wisely. They are being thoughtful about how they spend, but they want to do it without sacrificing innovation. And that's really the place that we are leaning in with.

Operator

Our the value that we offer for our price tends to be incredibly strong. We heard that over and over again. We offer tremendously differentiated capabilities. We allow you to bring in all of your different data types, analyze it in real time at scale. The performance is fantastic.

Operator

And the more we do to help you optimize your costs with things like time series data streams with things like searchable snapshots. Even the improvements that we keep making in the platform itself that allows you to reduce your overall costs, whether it be for vector search or something else, All of these things matter because that helps them reduce their infrastructure spend on hardware or what they're leasing from cloud providers, and that is incredibly important to them. And to be able to do that with a single platform is just a great value proposition. I've talked about this now for a couple of quarters that we've been leaning into this both from the product side and the go to market side because we see this as an opportunity to take share in the market in this time, and we are absolutely doing that. That's what's really driving a lot of the large commitments that we are seeing because we are able to get a customer to see how they can do more with Elastic and that results in a displacement of some incumbent And over time, that just increases our share.

Speaker 5

Thank you.

Speaker 2

Thank you. And our next question today comes from Raimo Lenschow with Barclays. Please go ahead.

Speaker 8

Hey, thank you. And I might have missed it earlier, but like can you speak to if I think about vector search and semantic Obviously, with vector search, there's a lot more compute involved than before. Like what do you guys seeing in terms of consumption trends and as customers Working with this. And what does it mean for you guys in terms of the momentum there because clearly customer signs one contract and the Customer is using them resources, but this seems to be like a bigger resource consumption that you get from these newer Technologies. So could you speak to that, please?

Speaker 8

And I have one follow-up for you, Janesh.

Operator

Yes, sure, Raimo. This is Ash here. I can touch upon that first one. So you're exactly right that when you're dealing with vector search or even semantic search, like really semantic search is all about doing search based on the meaning as opposed to just text. And what that requires you to do is to take the data that you have and run it through an ML model.

Operator

And that ML model, doing that work, is effectively significantly higher in terms of compute then just storing that data. But effectively, you have to take all your data, run it through an ML model, create vector embeddings and then use everything that you've built to then search against whatever that Information might be that you're searching for using that semantic information as opposed to just the textual information. And that tends to be much more compute intensive than traditional textual search. And as you know, for us, it's not just about consumption, but it's also the fact that ML is in a higher paid tier. So you either need platinum or enterprise.

Operator

And that is the second way in which we monetize. So both of those come into the picture for us for either vector search or semantic search, and that's really where we are seeing the progress. So like I mentioned, We have hundreds of customers now that are using us for our vector search capabilities, and that's really very exciting for us.

Speaker 8

Okay, perfect. Yes, that sounds very exciting. Thank you. And then Janesh, if I think about the evolution on the profitability side, like How do you think about investments as we think about going kind of maybe you talked about stabilization on the macro side a little bit. How do you think about like investments into sales and marketing, etcetera, Because a lot of these need to be much earlier than kind of the real revenue coming through because people need sales guys for example need to go live etcetera.

Speaker 8

Like how should we think about the Progression of investments as we go through this year. Thank you and congrats from me as well.

Speaker 1

Yes. Thanks, Raimo. So look, as I look Back at Q1, we are very pleased with the operating margin result in the quarter. I think that just reflects the hard work and focus of all of our employees to ensure that we manage the business with discipline. And as we've shared before, we have natural operating leverage that's inherent in the model and that was visible here in the Q1 results.

Speaker 1

We will continue to grow expenses slower than revenue on a full year basis as we invest in the business. And that will be sufficient to then help us achieve our near goal for fiscal 2024. But in terms of investments in the business, we entered this year with the right amount of selling capacity for this fiscal year and that was a focus area for us a couple of quarters ago, as you'll recall. And we continue to selectively invest in enterprise and commercial selling capacity. We are also investing appropriately here against the Gen AI opportunity, as I mentioned.

Speaker 1

So we are continuing to make investments throughout the business in areas that we feel are appropriate and that are best positioned to drive growth the rest of this year and into fiscal 2025. We obviously don't want to compromise on top line growth, but it is about ensuring balanced growth and profitability, and that's what we are committed to doing.

Speaker 8

Okay, perfect. Makes it very clear. Thank you.

Speaker 1

Thank you.

Speaker 2

Thank you. And our next question comes from Andrew Nowinski with Wells Fargo. Please go ahead.

Speaker 3

This is Stefan Schwartz on for Andy. Thanks for taking my question. Wanted to ask In terms of the vendor consolidation that you've talked about, Singh, is there any commonality among the customers Who tend to consolidate with you either in terms of size or vertical or geo?

Operator

There is no specific trend in any geo. I mean, we've seen that trend playing across multiple kinds of verticals across multiple geos. What tends to be the typical driver is When these customers are paying extremely high rates for incumbent solutions, And then they see what Elastic is able to do, which is not only much more differentiated, much more capable in terms of the performance, the kinds of data we can handle, the kinds of analytics that we can do, the machine learning functionality that we've built in, now with the generative AI capabilities, like it just becomes a no brainer. And usually what is needed is that inflection point where they see that the value they would get and the price that they would get it is meaningful enough that it justifies the effort to do the conversion of the move from their incumbent vendor to us. And that's really the inflection point.

Operator

And in the current environment where Customers are continuing to be thoughtful and mindful of their spend areas, and they want to make sure that they are driving innovation, but also with cost controls and constraints, it's a perfect setup for us.

Speaker 3

Got it. Thank you very much and congrats.

Operator

Thank you.

Speaker 2

Thank you. And our next question today comes from Brent Thill with Jefferies. Please go ahead.

Speaker 3

Hey, guys. This is Bo Yin on for Brent. Thanks for taking the question. So I wanted to ask about optimizations and customer behavior. Can you talk about the dynamic between customers focusing on optimizing their near term consumption, but Also bring on more workloads to Elastic to drive TCO savings.

Speaker 3

Is that increase in workloads being offset by optimization on those workloads? Or how should we be thinking about those dynamics?

Operator

Esrei? This is Ashish. So it's really difficult to sort of tease apart the exact dynamics in any one on how these things are moving. But in the aggregate, what I'll say is what we are seeing is that the majority of customers are Generally, when it comes to the consumption optimization that people were doing, they're generally where they want to be at this point. It started a few quarters ago, as you know, we talked about it, and it's gotten to a point where customers have done all the things that they generally believe that they need to do.

Operator

Data continues to grow. The kinds of use cases that we play in tend to be incredibly important. So it's not like they can just walk away from them. And so you see that kind of stabilization in the consumption optimization that people have been doing. At the same time, As we've talked about with you in the last several quarters, we've been leaning in, in this current environment to really drive consolidation onto our platform really showcase all the things that customers can do on our platform, and that's reflecting that's resulting in customers bringing newer workloads, consolidating multiple things.

Operator

And those new workloads are also now starting to ramp up. So Both those factors are playing in, and that sets us up quite nicely as we look ahead.

Speaker 8

Thank you.

Speaker 2

Thank you. And our next question today comes from Rob Owens with Piper Sandler. Please go ahead.

Speaker 3

Hey, thanks for taking my question. This is Ethan on for Rob. I just wanted to ask around how important the channel is when it comes to selling these Selling Esre and Gen AI functionality, especially as we think about you selling into these really large organizations and when the C suite gets involved? Thank you.

Operator

Yes. So the channel tends to be important, but keep in mind that for newer areas like this, The reality is that these are areas where we tend to have direct conversations with these customers, And the channel can often help us broker some of those conversations, but it's we tend to be the experts, so We tend to have a lot of these conversations where the relationships, the partner relationships really become wonderfully important and are helping us is the relationships we have with the cloud hyperscalers. As you saw from some of the accolades we won, that we talked about in this earnings call, we have our relationship with Google, with Microsoft, with AWS, They are strong and they're continuing to grow stronger. And that just means that when customers are talking to them, It allows us to go in jointly with these partners and have these kinds of conversations where customers are looking to do things that are on the leading edge. And those are the relationships that we believe are really critical at this phase, and that's where we have a lot of strength.

Operator

So I'm excited about that. Thank you.

Speaker 2

Thank you. And our next question comes from Kinsley Crane at Canaccord. Please go ahead.

Speaker 9

Hi, thanks for taking my question. I want to talk through consolidation wins. Are these picking up for you? And then how often is it the case that logging is leading Consolidation motion and then how often would you see a customer essentially adopt APM during this process?

Operator

The consolidation trend has definitely been strong in the last couple of quarters like we've talked about. And a lot of it, in my opinion, has to do with the fact that as people have as CIOs and companies have become more thoughtful about their spend envelopes, They're looking to see where they can save, and we have a value proposition that allows them to do that, while at the same time doing even more and getting the kinds of innovative technology that we've been bringing out in market. So It's working very nicely in our favor. Now what we typically tend to lead with, like we've talked about in the past, tends to be log analytics, tends to be security analytics and tends to be search. And then we progress from there, right.

Operator

So we have lots and lots of customers now that are using us thousands of customers that are using us for APM. And that's all many of those customers started with us with logs to begin with. And then they moved from logs and realized that they could get a much better picture of their overall observability landscape by not just bringing logs into Elastic, but also bringing APM traces. And then they eventually will bring on metrics and other things, real user metrics and so on. And that's the pattern that we see over and over again.

Operator

So the consolidation pattern tends to be one where we might start with log analytics and security analytics and search, but then we'll invariably go on to other elements of observability and other elements of security and so on.

Speaker 9

Great. Thank you, Ash. And then one brief follow-up for Janesh, if I may. Esray. Makes sense to be prudent on the guide, but could you walk us through how consumptions trended month by month in Q1?

Speaker 9

And then how did that fare so far in August?

Speaker 1

Kingsley, as I've mentioned a little bit earlier, I think it can vary from month to month. There's always going to be a little bit of noise in the monthly data. And so what we generally saw was consistency through the course of the quarter. And overall, I think the themes just played out as we described over the course of Q1. And then specifically for August, as I mentioned, we aren't done with August yet.

Speaker 1

So, hard for me to talk about that, but I will share that the general tone of customer conversations was similar to where it was in Q1.

Operator

Okay. Thank you.

Speaker 2

Thank you. And today's last question comes from Srinik Kothari with Baird. Please go ahead.

Speaker 10

Hey, thanks for taking my question. Great quarter. Congrats. So since you touched upon the annual cloud SRAE. Subscription motion performing quite well, Ash and highlighted some of the prominent organizations of the Fortune 100 and the leading 5 share service leveraging our capabilities.

Speaker 10

So it appears that your CE level engagement strategy and to your earlier point on hyperscaler partnerships Working quite well. But then I think Janesh also mentioned that the net adds to the 100 ks ACU was a bit lighter. So just if you guys can help reconcile and help perhaps unpack like how much of the business is currently being driven by this top John, or enterprise focused motion that you guys are strategically kind of moving towards that you highlighted few quarters back? And then I have a quick follow-up.

Speaker 1

Yes, I'll just touch on that real quick in the interest of time. We've continued to see strong contractual commitments to Elastic and we saw that here in Q1. It continued a trend we've seen for a few quarters now. So overall, I'd say our investments in the price selling motion and everything we bring to that, including the partnerships and so forth that you touched on, I think that's actually working quite nicely. Keep in mind that in our land and expand motion, the initial lands tend to be very small and then we tend to expand with customers over time.

Speaker 1

And so within that pool of over 100 ks customers that you mentioned, although the number of additions was a bit lower, we did see very strong expansion in the larger accounts and it flex those commitments. So we felt very good about how this all played out. And I do expect that we will have consistent growth in our customer metrics over time. It's been a good driver for us in the past, and I do that trend will continue over time.

Speaker 10

Got it. Thanks a lot, Janesh. And just very quickly, I mean, I know there was earlier question around Consolidation correlation with multiple use cases including GenAI. I was just wondering like are you also seeing kind of direct correlation with this kind of enterprise focused top down motion and consolidation as well. And are you guys kind of going about in a strategical fashion, not Like as I said, targeting industries or verticals, but just kind of in terms of kind of larger commitments and trying to target accordingly?

Operator

Yeah. I mean, so like we've talked about, right, in prior calls as well, our focus on enterprise selling has been strong. And we've talked about the fact that we've been very strategically focusing on customers that have greater propensity to grow with us. And that includes customers in the enterprise segment, that includes customers in the commercial segment. And one of the levers that we have been really focused on is our ability to deliver highly differentiated value at a incredible price for our customers because of the strength of our platform and its ability to deliver on multiple real time search use cases, whether it be for search, observability or security incredibly well.

Operator

And so we've been leaning into that as a motion irrespective of vertical and geography. So we've been driving that motion with our sales organization, and it's paying off. It's paying off in larger commitments. It's paying off in more workloads coming onto our platform and us taking share. And it's reflecting now in some of the and us taking share.

Operator

And it's reflecting now in some of the benefits that we're seeing in revenue.

Speaker 2

Thank you. And ladies and gentlemen, this concludes our question and answer session. I'd like to turn the conference back over to Ash Kulkarni for any closing remarks.

Operator

All right. Thank you all very much for joining our call today. We had a strong start to our fiscal year, and I'm really excited about the opportunity and our position in the market as a leading AI powered data analytics platform for multiple real time search use cases. We will be hosting our ElasticON AI Conference in San Francisco in a few weeks, and I am looking forward to seeing our customers there as we talk about all the exciting things we are doing in this space. Have a great rest of the evening.

Operator

Thank you.

Speaker 2

Thank you. This concludes today's conference call. We thank you all for attending today's presentation. You may now disconnect your lines and have a wonderful

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Elastic Q1 2024
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