Elastic N.V. (NYSE:ESTC) Q4 2023 Earnings Call Transcript

Elastic N.V. (NYSE:ESTC) Q4 2023 Earnings Call Transcript June 1, 2023

Elastic N.V. beats earnings expectations. Reported EPS is $0.22, expectations were $0.1.

Operator: Hello, and welcome to the Elastic’s Fourth Quarter Fiscal 2023 Earnings Results Conference Call. All participants will be in a listen-only mode. [Operator Instructions] After today’s presentation, there will be an opportunity to ask questions. [Operator Instructions] Please note this event is being recorded. I would now like to turn the conference over to Nikolay Beliov, VP, Investor Relations. Please go ahead.

Nikolay Beliov: Thank you. Good afternoon, and thank you for joining us on today’s conference call to discuss Elastic’s fourth quarter and fiscal 2023 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 supplement 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.

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 was issued earlier today included in the slides posted on our 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. 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 first quarter fiscal 2024 quiet period begins at the close of business on Monday, July 17, 2023. On June 6, 2023, we will be participating in the Bank of America Global Technology Conference. And on June 7, 2023, we will be participating in the Rosenblatt Technology Summit. With that, I’ll turn it over to Ash.

Ashutosh Kulkarni: Thank you, Nikolay, and thank you all for joining us. I’m pleased with how we performed this quarter, given the global market environment, and I’m pleased with our results for the full fiscal year. We remain completely aligned to the needs of our customers, have prioritized focus areas for our business and continue to be confident about the opportunity ahead of us. Elastic has always had a singular mission, enabling everyone to find the answers that matter from all data in real time at scale. Generative AI and its chat-based intuitive approach to information systems, is opening up new opportunities for businesses to offer better services to their customers, make their processes more efficient and drive new insights from their data.

Elastic has been investing in AI and ML capabilities for years, and we have many existing customers and use cases that demonstrate our successes in this area across search, observability and security. Our newer capabilities, including the Elasticsearch Relevance Engine or ESRE and vector search have enabled us to be a key component of the emerging AI stack to democratize generative AI and enable customers to optimize large language models with their own data in a secure way. We are very excited about the long-term opportunity this represents for Elastic. Now turning to our most recent quarter. In Q4, total revenue grew 19% year-over-year in constant currency with Elastic Cloud growing 30% year-over-year in constant currency and representing 40% of total revenue.

We saw solid customer contractual commitments with customers continuing to consolidate onto our platform. We again managed the business with discipline to deliver a stronger-than-expected non-GAAP operating margin of 8.6%. For the full fiscal year, total revenue grew 24% year-over-year and 28% in constant currency, with Elastic Cloud growing 42% year-over-year and 44% in constant currency. We ended the quarter with more than 1,160 customers with annual contract values over $100,000 and more than 140 customers with annual contract values over $1 million, highlighting once again that our land-and-expand strategy is working. During the quarter, customers remain focused on optimizing their cloud consumption. At the same time, customers continued to make large multi-year commitments as they sought ways to consolidate onto the Elastic platform for more use cases to lower their total spend without sacrificing innovation.

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. This quarter, we renewed a seven-figure multi-year deal with the Fortune 500 financial services and digital payment technology firm that uses Elastic across all three of our solutions for observability, security and search. The company has built an enterprise-wide center of excellence around Elastic Observability to power its customer-facing applications and ensure its payment transaction systems remain healthy in addition to leveraging Elastic for anomaly detection, threat hunting, cyber identity and access management and internal search. Like we have discussed previously, our customers routinely tell us the total cost of ownership of our platform is dramatically lower than competitive offerings, enabling us to compete very well in this environment.

We have also been driving campaigns to motivate customers to displace incumbent tools and consolidate onto our platforms and are seeing success with this approach. In Q4, we signed a deal with a large county in California, where we displaced their existing logging solution, doubled their ingest capacity and still save them close to 40% of what they were spending on their prior vendor. Basically, more than 3x higher total value than the incumbent solution. Our differentiated platform capabilities and our compelling total cost of ownership make our platform incredibly sticky and have allowed us to maintain strong gross retention rate in Q4, similar to prior quarters. Now I’d like to share our progress across our three key focus areas: driving durable growth, widening our competitive moat and fueling profitable growth.

Starting with durable growth. Our durable growth is driven by three pillars. First, the strength and versatility of our search analytics platform that enables us to succeed in multiple markets, including search, observability and security, giving us access to $88 billion total addressable market. Second, our innovation engine with a track record of delivering capabilities like vector search, AIOps, APM and security analytics, innovations that give our customers the confidence that they can trust Elastic now and in the future to continue delivering value. And third, our cloud partnerships. We see strong momentum with our cloud partners and in the hyperscaler marketplaces as customers continue to expand their engagements with us. In Q4, we further strengthened our relationship with AWS through a strategic collaboration agreement that will help accelerate integrated go-to-market activities globally and streamlined migration of on-premise workloads to make the cloud adoption journey easier for customers with Elastic Cloud on AWS.

Our work with our hyperscaler partners is continuing to help us close large deals through their marketplaces. In Q4, we renewed and expanded a three-year deal with CoreLogic, a leading global property information, analytics and data-enabled solutions provider, which began its absorbability migration journey with us two years ago, moving to Elastic Cloud via the Google Cloud Marketplace. As an Elastic Observability customer, CoreLogic leverages capabilities such as uptime and APM to monitor business-critical applications. CoreLogic also heavily relies on Elastic Enterprise Search for its data indexing and retrieval capabilities. We also expanded and renewed a seven-figure deal this quarter with a leading buy now pay later provider. The company uses Elastic Observability for log monitoring as well as Elastic Security for SIEM.

We signed a multi-year contract in Q4 for Elastic Cloud via the AWS marketplace, enabling them to optimize costs and accurately scale their environments as their data usage continues to grow, especially during peak shopping seasons such as Black Friday and Cyber Monday. Now on to our widening competitive mode. Our solutions continue to be bolstered by innovation on the Elasticsearch platform, driven in part by our AI and machine learning capabilities. ML continues to be a major driver for customers adopting our higher subscription tiers. We already have over 20% of our annual cloud subscriptions using our ML functionality for search, observability or security. For example, in Enterprise Search, we expanded a three-year deal with one of the largest home improvement retailers in the United States for Elastic on Google Cloud.

A longtime customer, the company uses Elastic to power its online retail business, enabling customers to search, browse and discover products at scale efficiently. They use Elastic for multiple use cases and are leveraging our machine learning capabilities in observability as well as testing capabilities like vector search to enhance search experiences for their customers using a single cost-efficient platform compared to legacy solutions. The increased focus on AI and in particular, large language models is shaping customer perspectives and business expectations. Our goal is to democratize generative AI and make it possible for everyone to build generative AI applications and domain-specific copilots that are relevant to their businesses and optimized with their proprietary data.

Our recently announced Elasticsearch Relevance Engine or ESRE, it’s powered by built-in vector search and transformer models that have been designed specifically to bring the power of AI innovation to proprietary and enterprise data. A key part of our approach to machine learning is allowing our customers to integrate their own models in addition to leveraging the models that we offer by natively integrating machine learning into the core of Elasticsearch. We have enabled our customers to adopt new ML-based features across each of our solution areas. This means that thousands of companies that have invested in Elastic solutions can advance AI initiatives to date without a lot of additional resources. This is a big competitive strength for Elastic.

Our announcement of ESRE last week at the Microsoft Build Conference has been very well received by our customers and partners alike. Now I will share some details about additional innovations in security and observability solutions. This past quarter, we expanded capabilities for Elastic Security, including Cloud Security Posture Management for AWS, container workload security and cloud vulnerability management. Elastic now delivers a comprehensive security analytics solution that includes complete Cloud Native Application Protection or CNAP for AWS, providing organizations with the power they need to modernize their cloud security operations, improve attack surface visibility, reduce vendor complexity and accelerate remediation. We also announced that we are contributing Elastic Common Schema, or ECS, to OpenTelemetry and committing to joint development of a common schema for observability and security logs.

OpenTelemetry, or OTel, is the second highest velocity project in the Cloud Native Computing Foundation also known as CNCF and is the emerging industry standard for telemetry data, encompassing metrics, logs and traces. CNCF choosing the Elastic Common Schema as the basis for their OTel schema for logs reflects the incredibly broad adoption of Elastic for log analytics and security analytics and our continued leadership in this area. The merging of ECS and OTel will help advance OTel’s adoption and help our customers get increasing value from their investments in our platform. In addition, we launched the beta of a new Service Level Objective or SLO monitoring capabilities in Elastic Observability, which let customers measure and monitor service quality such as latency, availability or other custom-defined key performance metrics.

These new capabilities help customers define SLOs, monitor and track performance against these SLOs and alert on SLO violations to deliver on service levels. Now moving on to my last key point, profitable growth. As we’ve demonstrated this quarter, we are committed to managing the business with discipline. We delivered a non-GAAP operating margin of 8.6% in Q4 and are on track to deliver on our 10% target for FY2024. We continue to expect further margin expansion in fiscal 2025. Our fundamentals remain strong. We remain committed to continuing our growth strategy while delivering increasing profitability. In closing, I want to thank our employees for their dedication and contribution to our performance. 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, especially in Elastic Cloud remains unabated. It is based on the strength of our many exciting product innovations and continued customer confidence in Elastic. We are focused on execution. As the amount of data being generated and used increases and the need for finding answers that matter from all that data becomes more critical, Elastic is well positioned to take advantage of this generational opportunity. With that, I’ll turn it over to Janesh to go through our financial results in more detail.

Janesh Moorjani: Thanks, Ash. We delivered solid results in the fourth quarter, finishing a good year for Elastic despite the current economic environment. We are pleased that we once again came in above the high-end of both our topline and bottom line guidance for the quarter. In Q4, we delivered 19% year-over-year constant currency growth in total revenue and Elastic Cloud grew 30% year-over-year in constant currency. Importantly, we delivered non-GAAP operating margin of 8.6% and are on track to achieve our goal of 10% for fiscal 2024. The overall trends we saw in the quarter remained consistent with the prior quarter. Customers want to do more with Elastic. There are three compelling reasons customers pick Elastic in the current business climate.

First, our platform innovation to drive multiple use cases with any kind of data on a single stack. Second, a lower total cost of ownership and third, the flexibility of our consumption model. In addition, our many years of experience in AI and ML and the broad adoption of Elasticsearch for all sorts of search analytics use cases is enabling new conversations with our customers on generative AI. At the same time, we are helping customers optimize current consumption in the near-term. Being a reliable partner to our customers in challenging times increases our strategic importance to them for the long-term. As they bring more workloads onto the Elastic platform over time and as data volumes grow substantially, customers see greater business benefits, which in turn drives growth for us.

This sets us up nicely for the long-term. Let’s get into the results for Q4. Total revenue in the fourth quarter was $280 million, up 17% year-over-year or 19% in constant currency. Subscription revenue in the fourth quarter totaled $256 million, up 16% year-over-year or 18% in constant currency, comprising 91% of total revenue. Within subscriptions, revenue from Elastic Cloud was $112 million, growing 28% year-over-year or 30% in constant currency. Elastic Cloud represented 40% of total revenue in the quarter, up from 37% a year-ago. Elastic Cloud revenue based on month-to-month arrangements continue to be 16% of total revenue similar to the prior quarter and compared to 17% in the same quarter last year. Professional services revenue in the fourth quarter was $24 million, growing 35% year-over-year or 38% in constant currency.

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 deal flow, the Americas grew the fastest, followed by EMEA and APJ. We also saw a healthy balance across the solutions and continue to maintain a similar solution mix in annual contract values versus the prior quarter. Moving on to customer metrics. In the over $100,000 ACV customer category, we added approximately 50 customers, bringing us to over 1,160 such customers as of the end of the fourth quarter. As we’ve said before, this customer category provides a strong foundation for our land-and-expand motion as we build a multi-billion-dollar company over time.

The strength of this motion is also reflected in the number of customers over $1 million ACV which was over 140 customers at the end of this year compared to over 115 such customers at the end of the prior year. Looking at customer additions more broadly. We added approximately 100 customers above $10,000 in ACV to end at over 4,100 such customers. Our total subscription customer count was approximately 20,200 at the end of the quarter. Turning to the net expansion rate. Our net expansion rate was approximately 117%, which was in line with our expectation. As we’ve shared before, for customers on consumption arrangements, our net expansion rate reflects only their actual consumption and not their commitment. Also, as a reminder, since the net expansion rate is a trailing 12-month measure, it will decline for a couple of more quarters as higher expansion rates from prior periods roll off.

Our customer metrics indicate that our strategy of focusing on customers with a higher propensity for growth is working. Customers can consolidate workloads both within and across our solutions, growing their commitments to Elastic over time. Moreover, they can flexibly scale with our consumption model. Now turning to profitability for which I’ll discuss non-GAAP measures. Gross margin in the quarter was 76.3% versus 75.5% in the prior quarter, with the sequential improvement driven by both better subscription gross margin and better professional services gross margin. As we’ve said before, professional services gross margin can fluctuate based on the timing of service delivery. Our operating margin in the quarter was 8.6%, which was better than expected given the revenue outperformance, higher gross margin and continued focus on managing our expenses.

Diluted earnings per share in the fourth quarter was $0.22. Free cash flow margin on an adjusted basis was 9% or approximately $26 million in the fourth quarter. We ended the year with adjusted free cash flow of $57 million, which was a substantial improvement against the prior year consistent with our overall operating profitability improvement. We continue to maintain a strong balance sheet. We ended the fourth quarter with cash, cash equivalents and marketable securities of $915 million. Turning to guidance. Our overall guidance for fiscal 2024 is predicated on assumptions similar to those in the framework we had outlined on our prior call. We are assuming macro conditions will remain unchanged. While our customer momentum, as reflected in contractual commitments we have already secured will translate to revenue, the pattern and timing of consumption may fluctuate.

We believe that it is prudent to anticipate that consumption trends in the near term may stay similar to recent quarters. We are reflecting this expectation in our guidance for the first quarter. Further, as we’ve shared earlier, we expect first half year-over-year growth in total revenue to be slightly lower than our expectation for the full-year given tougher comparisons against the first half of fiscal 2023. In terms of operating expenses, we are investing with discipline in the business and are continuing to grow enterprise and commercial sales capacity. We intend to carefully monitor our progress each quarter ensuring we are getting the right outcomes as we consider further investments in the business. This will help us not only achieve our 10% non-GAAP operating margin goal for fiscal 2024 but also set us up for further margin expansion in fiscal 2025 as we drive natural operating leverage inherent in the business.

Additionally, as we’ve said before, Q1 will be the low point on non-GAAP operating margin, given our seasonally higher expenses in the first quarter and considering revenue ramp over the year. Finally, though we don’t formally guide to cash flow, we are expecting free cash flow margin on an adjusted basis for fiscal 2024 to be slightly above the non-GAAP operating margin for fiscal 2024. Cash flow on a quarterly basis will fluctuate given timing issues and seasonality, so we continue to look at this primarily on a full-year basis. With that background, for the first quarter of fiscal 2024, we expect total revenue in the range of $283 million to $286 million. This represents 14% year-over-year growth at the midpoint, both on an as-reported basis and in constant currency.

We expect non-GAAP operating margin for the first quarter of fiscal 2024, in the range of 5.6% to 6% and non-GAAP earnings per share in the range of $0.10 to $0.12 using between 100.5 million and 101.5 million diluted weighted average ordinary shares outstanding. For full fiscal 2024, we expect total revenue in the range of $1.238 billion to $1.250 billion. This represents 16% year-over-year growth at the midpoint both on an as-reported basis and in constant currency. We expect non-GAAP operating margin for full fiscal 2024 in the range of 9.7% to 10.3% and non-GAAP earnings per share in the range of $0.94 to $1.06 using between 102 million and 104 million diluted weighted average ordinary shares outstanding. In summary, we remain focused on delivering profitable growth as we build a multibillion dollar revenue business.

We are confident that we are still in the early stages of this growth journey. And with that, let’s go ahead and take questions. Operator?

Q&A Session

Operator: Thank you very much. We will now begin the question-and-answer session. [Operator Instructions] Today’s first question comes from Matt Hedberg with RBC Capital Markets. Please go ahead.

Janesh Moorjani: Hey, Matt. Are you there?

Matthew Hedberg: Yes. Can you hear me okay?

Janesh Moorjani: Yes, we can. Go ahead please.

Matthew Hedberg: Sorry guys. Okay. Sorry about that, double muted. So yes, I wanted to dig into vector search and AI. To us, it seems like a large opportunity for you guys to see higher density models on the Elastic platform. Just kind of curious about what the early interest has been. Are you seeing any increased activity as it relates to vector?

Ashutosh Kulkarni: Yes. Hey, Matt. This is Ash here. I can talk about this. So ever since we made the announcements of the Elasticsearch Relevance Engine literally, we’ve been having conversations with customers on a daily basis. Like it’s – the interest has been just wonderful to see. And even with vector search, but it’s when you think about generative AI, there are really two aspects to generative AI to build applications that are incredibly important. You can’t do without either of these two components. So the first is the large language model itself. Whether it’s GPT-4 or Bard or what have you. But these models are trained on publicly available data, and these models have no concept of businesses proprietary private data.

And so if you are a business and you’re trying to build a generative AI application, you really need to provide that private context to these large language models for it to be contextual to your business and your needs and for those answers to make sense in the context of the business. And that’s really where Elasticsearch comes in. So the announcements that we’ve made, all the developments that we’ve done around vector search, in the last year and a half bringing that vector capability together with the textual search functionality, the BM25 functionality that we’ve had in the past, providing the hybrid search functionality and more importantly, doing it all on the same platform. So our customers don’t need to purchase anything different and they don’t have to get used to a new technology.

They can just start to use the machine learning functionality and the vector functionality that’s in the product with the same APIs, like this is a huge differentiator. And so from our perspective, we believe that we are uniquely positioned to be a winner in this space, especially when it comes to generative AI in the enterprise. So we’re seeing that momentum in terms of customer conversations. We are very excited about what this opportunity represents in the long-term, how this translates into the expansion of the total addressable market. I think that we’re going to get a sense of as we progress because there are lots of things that customers are working through. How do you do all these things in a way that your data privacy, your data security is handled in a good way, how do you think about model biases.

So there’s a lot of the stuff that you typically tend to see getting worked out in the early days of a new platform emerging. So that’s what I expect we are seeing right now and what is happening. But in the long-term, I believe that this is going to be massive, and we are going to be in a really, really strong position to take advantage of this.

Matthew Hedberg: Maybe just a quick follow-up to that. Do you think when you start to see more of a monetization effort; is that one of the things that could start to inflect Elastic Cloud growth regardless of sort of broader macros? Like do you think that some of these trends are sort of stronger than sort of the depressed macros and you could start to see a rebound in Elastic Cloud growth maybe even sooner?

Ashutosh Kulkarni: Yes. So when I think about the way in which we monetize vector search and all this AI functionality that we’re talking about here, it’s all in our premium additions, right? And the other thing is the machine learning capabilities tend to be pretty compute intensive. And as you know, both these factors tend to drive consumption for us. So obviously, as customers move from today, it’s mostly individual consumers using something like a ChatGPT for all kinds of fun use cases and businesses are still trying to understand what are the kinds of use cases they want to build, what are the generative AI applications that they want to build for their own use cases, and we are at that stage. And as this turns into actual production, this is when we believe that it’s going to really become very impactful and meaningful for us.

It’s still at this point where it’s hard to predict how fast this will move, and we are appropriately just focusing on the execution right now and not thinking too much about when this turns into significant tailwinds for us. But in the long run, I’m very confident this is going to be significant.

Matthew Hedberg: Thanks guys.

Operator: The next question comes from Tyler Radke with Citi. Please go ahead.

Tyler Radke: Yes. Good afternoon. So Ash, another question for you on generative AI. I’m curious just as you look at the new customers that have come on to the Elastic platform I think you added about 300 this quarter, which was up from the 200 last quarter. Are you seeing any of these new kind of next-gen AI companies using the Elastic technology and using some of your new products that you announced? If you could just kind of talk about the composition of customers and maybe the use cases within kind of these next-gen generative AI companies where you’re seeing your technology used?

Ashutosh Kulkarni: Yes. So what we talked about even last week, when we announced at Microsoft Build, even there, we gave some customer examples, right? We talked about relativity, the customer that’s using us for search use cases using us in conjunction – our vector search functionality in conjunction with large language models to deliver the kinds of use cases that they are looking to deliver for their customers. In my prepared remarks, I also talked about the large home improvement store in the U.S. that’s looking to do something similar. They’re working very closely with us. And these kinds of use cases, I believe, are not just going to be for the tech first kinds of organizations they’re going to be for just about every business out there, right?

So if you just think in terms of the home improvement customer that I mentioned, today, they use Elastic for all the product search on their platforms. So if you go on to their website and you search for miter saw or you search for a hammer, like it’s Elastic that’s figuring out what’s the best product to actually like what’s the most relevant product to show them. Now what they’re interested in is effectively the kind of chat experience on their website which would be tremendously interactive and powerful. Like I’ll give you an example. Like if a user comes to their website and says, I want to build an irrigation system for my two-acre backyard, what do I need? Now if you ask this question to ChatGPT, you’re going to get very generic answers because ChatGPT has no idea what this particular store sells.

And so the experience that this store – this company wants to deliver is effectively something along the lines for what you’re trying to build based on where you live, you’re going to need three sprinkler heads, you’re going to need these kinds of pipes that are rated for the temperature that is right for where you live and so on. And by the way, these are available in store and can ship to you in the next 24 hours, click here if you wanted that. That’s the kind of powerful experience that effectively helps them monetize and improve their own business performance in a very significant way. And we are talking to customers and hearing about all kinds of interesting use cases, not just for search, but even for observability and security for observability once – if I have an issue in – if I get an alert and you see something in my logs that’s related to some Kubernetes cluster that’s not performing well, you can imagine an ESRE wanting to know, “Oh, what do I do about this?

Is there a prescriptive set of steps that I need to follow here? And this notion of copilots can be incredibly helpful, like we are seeing that interest in security to be able to take remedial action on threats that you see without needing very sophisticated threat hunters. So there is a tremendous amount of interest and we are seeing use cases and we are seeing active interest across the board. And that’s one of the reasons why I also talked about the fact that we have a lot of experience with machine learning. And we’ve been working with customers on machine learning for many years now. So this is just taking it to the next level.

Tyler Radke: That’s helpful. So Janesh, just on the cloud revenue here. So could you just talk about, did you see any incremental macro headwinds in the quarter? And then as you think about the guidance for FY2024, what are you assuming just to get to that second half acceleration that’s implied? And then – and apologies if I missed it. Are you targeting a certain percentage of revenue is Elastic Cloud by year-end? Thank you.

Janesh Moorjani: Hey, Tyler. So overall, when I step back and just look at our performance in Q4, we were actually quite pleased. The quarter played out as we expected it would. There were many positives for us to highlight in the quarter. We touched on the number of customers earlier, the customers in the greater than $100,000 category. We generally saw from a macro standpoint – to answer your question, we generally saw the same trends that we saw in Q3. They continued into the fourth quarter. So we didn’t see anything significantly different customers continue to engage with us. They are looking to bring more workloads on to the Elastic platform. They’re looking to both do that to drive TCO savings but also just get greater business value.

And at the same time, they are continuing to focus on ways in which they can optimize their consumption in the near term. And we’re continuing to help them with that because our belief is that if we work closely with partners at this time, we emerge from this much more relevant to them. And as they bring more workloads on to Elastic, that actually helps us scale the business even better and faster over time. So that’s what we saw. It was a consistent pattern. I’d say it was also consistent throughout the course of the quarter. It did not change in any meaningful way. And as I said earlier, it was sort of what we expected would happen. And also just a reminder for folks that Q4 is a bit of a shorter quarter than Q3, so that does have an effect on the sequential growth rate in Q4.

And then looking ahead, as I mentioned earlier in the prepared remarks, we’re excited about the momentum that we’re enjoying with our customers. We’re entering the year with a pretty strong base of commitments that we’ve already secured. And just given the nature of our contracts and how we think about the structuring of those contracts Keep in mind that our contracts typically have their one-year contracts or if they have – if they are longer term, then they have annual breakpoints. So there are very natural mechanisms that we have embedded in the contracts to ensure that certain amounts of revenue do get recognized within fiscal 2024, particularly as you think about the base of contracts that we’ve signed here in the second half of fiscal 2023, as those anniversary in the second half of fiscal 2024.

And you can see that, for example, if you look at the growth in the total dollars of short-term deferred revenue that we added in the second half of fiscal 2023, and you compare that to the total dollars that we had added in the second half of the previous year, you will see that it’s a substantial increase. So that’s one of the pieces that we thought about as we built the plan for the year. And finally, as I think about just ongoing sales execution and other things within the business, we feel pretty good about the increased capacity that we’ve got as we entered fiscal 2024 with the right amount of capacity in our sales team, as we have talked about before, we continue to hire both enterprise and commercial sales reps. And so overall, when I step back and look at the quarter, it played out as we expected it would, turned out to be a pretty good fiscal year overall despite the macro climate, and we feel pretty good about this year coming up.

Operator: The next question comes from Koji Ikeda with Bank of America. Please go ahead.

Koji Ikeda: Hey guys. Thanks so much for taking the questions. I wanted to ask another one on vector search. And thanks so much, Ash, on the use case examples. I think that’s super helpful. And I just wanted to ask a couple of questions here on vector search. One, I think you mentioned that vector is only available on the premium edition. I just wanted to confirm that it’s a paid feature only and there’s no vector search in the open source or in the free version, question number one. And then number two, I totally hear you on Elastic being differentiated. I mean when I’m doing my checks out there, I hear that all the time from your user base, too. But could you help maybe explain it very simply on how Elastic’s vector search is differentiated from the other vector search vendors out there?

Ashutosh Kulkarni: Yes, great question. Koji respond to both of them in order. So in terms of the product features and the monetization, the vector searching functionality itself is in all editions, but the machine learning, how do you actually do the ingestion and creation of all of the vectors, all of that functionality, the ESRE model that we announced, the hybrid search capabilities that we announced, all of those are in the premium editions. So for all practical purposes, you need the premium editions to be able to build generative AI applications on our platform. So that’s the monetization model. Now in terms of the differentiation, I can break it down for you in a few ways, right? So the first thing is, when you think about the emerging AI Stack, right, like I mentioned, there are two things that you’re going to definitely need.

The first is you’re going to need an LLM, a large language model. And the second thing that you’re going to need is some system that will allow you to provide the relevant context, and this is the most important piece because for every business, they don’t want to ship all of their private data to the LLM. And more importantly, the LLM won’t even be able to use everything because they are not built on having everything in real time, right? So your private data is constantly changing. It’s moving in real-time. So the key is to provide for any given query from the – any interaction with the large language model, just a relevant context. And for this surface, you need at times the vector search functionality. At times, you need the textual search functionality and more recently, what people are discovering is you actually need a combination of the two in many, many different cases.

And then for practical use cases, as you’re building these applications, you need to be able to incorporate things like filtering, things like aggregation of these results. So for that reason, if you – if all you have is a vector database, you then need to still combine it with some technology like Elastic’s to be able to bring all of this together, in our case, we’ve built everything in one consistent platform. The APIs are consistent with each other, and you can actually get – take advantage of all of these capabilities, including the ability to bring in external models directly from HuggingFace or any PyTorch model and run them on Elastic. So it’s just a much more complete and much more capable solution than anything that’s out there on the market.

And that’s the reason why we feel so confident about the unique opportunity that we have to be a real winner in the space of generative AI for enterprises.

Koji Ikeda: Got it. Loud and clear, Ash. Thank you so much. And just one follow-up here for Janesh. Just thinking about the 2024 guide in cloud, it was just 40% of revenue in the fiscal fourth quarter. So for the guide, does that assume that, that mix of – that 40% mix, does it assume it goes up stay flat or go down throughout the year? Thanks guys.

Janesh Moorjani: Yes, Koji, great question. So we don’t disaggregate the guide across the pieces. But overall, just given the momentum that we’ve had in cloud, given all of the product investments we are making, given the go-to-market focus that we’ve had, I would fully expect that cloud will grow significantly faster than the overall rate of growth in the business. So we should see a mix shift in cloud over the course of the year. We’ve just not quantified it, but we fully expect that, that will happen.

Koji Ikeda: Got it. Thank you so much guys. Thank you so much.

Janesh Moorjani: Thank you. Looking forward to seeing you next week.

Operator: The next question comes from Pinjalim Bora with JPMorgan. Please go ahead.

Pinjalim Bora: Hey guys. Thanks for taking the question. Shockingly, another question on generative AI, ESRE. Ash, maybe help us understand for – obviously, Elasticsearch is known by developers. For somebody who has been working using and deploying, implementing Elasticsearch, how difficult would that be for them to now shift and deploy ESRE? Can that become kind of that familiarity with Elasticsearch, could that become an advantage for you guys as you kind of pivot towards this generative AI opportunity?

Ashutosh Kulkarni: Yes. It’s – Pinjalim, thank you for the question. It’s a massive differentiator for us, right. If you think about the fact that Elasticsearch is the de facto platform when you think about search within the enterprise. And the way we have built the ESRE functionality, the relevance engine like it effectively brings together all of the vector functionality along with all of the BM25 textual search functionality, the hybrid capability to bring all of those to – these two things together. And it’s all in a common platform with consistent APIs. And that last part about the consistent APIs is huge because that means that if you are familiar with Elasticsearch you now are naturally going to be able to take advantage of all of these capabilities easily.

You don’t have to learn completely new APIs. You don’t have to figure out how to manage a new system and monitor it. Like effectively, what you have from Elastic, whether you have it in Elastic Cloud as an example, like you could just get started with this immediately. And like that’s the reason why we feel very good about it. The conversations that we are having with customers is sort of reflecting this excitement. And like I said, the key is going to be seeing how this evolves and how businesses start to move these things into production. And I’m personally very excited about what this means for us in the future.

Pinjalim Bora: Got it. Very helpful. And one for Janesh. Janesh, the guide, when I’m looking at it, you talked about the sequential growth in Q4, the subscription sequential growth is basically flat. You’re guiding to about 16%. It sounds like it’s more of a second half story. Help us understand the kind of the confidence on that second half build from what you’re saying, it sounds like there are some mechanics with the contracts that I guess we can’t see. But obviously, you have a strong RPO. But I’m just trying to understand what gives you confidence for that to kind of reach that guide in the second half? And maybe help us understand the consumption trends so far in Q1 that you’re seeing?

Janesh Moorjani: Yes. Pinjalim, as I think about the full-year, a couple of things, and I touched on this a little bit earlier, but I’ll elaborate a bit further. So if you think about the way our contracts mechanically work, because we have either a one-year contract or we have – if we have multi-year contracts, you typically have annual breakpoints. And given the strength that we saw in contractual commitments that customers have made to us over the course of Q3 and Q4, and we were actually quite pleased with the outcome overall, even here in this quarter that we just wrapped up. As I look at all of those commitments, there are effectively natural mechanisms embedded in those contracts so that as customers consume against those contracts over the course of this year, we will see that translate to revenue.

We’re working actively with them for commitments that they’ve made to bring those workloads on to Elastic and to see that consumption ramp. But consumption can fluctuate from quarter-to-quarter depending on what actually happens with respect to that customer activity. So if the consumption ramps, that’s great. But even if consumption trends stay similar to where they are in the first half, and that’s the way we’ve built the model based on the Q1 guide, I’m just thinking about the first half overall, we will naturally start to see those contracts anniversary, and we’ll then hit those breakpoints in the second half. So that gives us a good degree of visibility to ensure that there are certain amounts of revenue that will be recognized in fiscal 2024.

So that’s the mechanical aspects of the contracts. And that’s why I was referring to the – if you looked at the short-term deferred revenue and you look at how much short-term deferred revenue we’ve added in the second half of fiscal 2023, you’ll see it’s significantly higher than the short-term deferred revenue we added in the second half of last year. And that gives me a degree of comfort and confidence around the full-year. And then the other piece is with respect to the sales capacity that we’ve been adding, we’ve entered fiscal 2024, with the right amount of capacity that we expected to have. We continued hiring in the back half of fiscal 2023. And so those salespeople will also naturally start to achieve their productivity thresholds that we have in the business.

So putting all that together, we feel really good about our outlook for the year. In terms of what May has looked like and Q1 so far, in general, the top of funnel activities that we generally have in the month of May have been very consistent with what we’ve seen in the past. May, because it’s the first month of our fiscal year, there’s always other kinds of activities that happen. We’ve had our sales kick off, for example, in the month of May. But I’d say it’s been a fairly typical May in terms of what we would have expected based on some of the internal activities and some of the general top-of-funnel activities.

Pinjalim Bora: Got it. Thank you.

Operator: The next question comes from Ittai Kidron with Oppenheimer. Please go ahead.

Harshil Thakkar: Hey, guys. This is Harshil on for Ittai. I wanted to ask about the new AWS collaboration. What do you expect this to bring to Elastic in terms of dollars? Is there any color you can maybe give on how the integrated go-to-market activities will look? And then how is this different from how you bid with AWS up to now?

Janesh Moorjani: Hey, Harshil. Maybe I’ll take that one. So as I think about the overall AWS relationship that we – and the contract that we just signed, it builds further on the partnership that we’ve enjoyed with AWS until now. Through these contracts, both parties are committed to significantly greater investments in areas like co-marketing, cloud adoption for workloads and so forth. The partnership itself covers a few broad areas. There’s some of the integrated go-to-market activities that I mentioned, including marketing campaigns, guides, workshops and those kinds of activities. There are technology integrations. There are commercial incentives that we have embedded in them to drive the migration of on-premise workloads to Elastic Cloud on AWS.

And then we’re extending some of these practices globally as well. And within that, there’s also additional work being performed for us to drive certain competency designations. You saw the security competency designation that we already announced. So it’s a comprehensive partnership. It focuses on go-to-market. It focuses on the technology side in terms of additional reference architectures and better integrations. And some of these investments from both sides will happen over time, and they will bear fruit over time. But overall, when I step back and look at the evolution of the relationship and how far we’ve come, we’ve been really proud and pleased with the partnership and we look forward to providing you with further updates on the progress as we go.

Harshil Thakkar: Got it. Thank you.

Operator: The next question is from Shrenik Kothari with Baird. Please go ahead.

Shrenik Kothari: Hey. Thanks a lot. Congrats on the strong execution and the customer commitments. I was just wondering like how do you see the dynamic between – of course, we are hearing customers optimizing the consumption versus the strong commitments that you guys called out. Of course, there are all these prior innovations. You guys announced the relevance engine and the vector search, transform models and the ESQL as well, the feedback has been strong. So on your go-to-market and product strategies, I mean just curious if it involved more flexible kind of solutions, pricing terms, driving more value into existing packages. Just curious if you can unpack some of the go-to-market strategies there?

Ashutosh Kulkarni: Yes. Hey. This is Ash here. Maybe I can take a crack at this. So this is what you’re describing is sort of fundamental to our platform strategy, right? And what we are seeing right now in the market within our customers is everybody is being very cost conscious and towards that aim, they are looking to optimize their current workloads on Elastic, right. So as an example, we often will see customers moving more data to lower-cost object storage. And we often hear from customers that our frozen tier, which is where customers stored a lot of their data in low-cost offering storage tends to be faster than the hot tier of our largest competitor. And that’s really pretty amazing. So we are able to save our customers not only the – in terms of total cost of ownership, but also deliver far greater value at a much lower cost.

And that’s one of the reasons why even as customers are optimizing their current workloads, they are making larger commitments to Elastic to be able to consolidate more onto our platform and move workloads that are currently on other competitor products on to Elastic. Now that takes a little bit of time to actually materialize in terms of moving those workloads over, but the commitments are really strong, and this is where, like I get very excited. The fact that we have amazing total cost of ownership, and I gave a very concrete example of this in my prepared remarks where the county in California was able to really get 3x the value. Effectively, these are the kinds of anecdotes that we are seeing. This is the kind of data that we are seeing.

And we are really leaning into it. So we know that as more workloads come into our platform, eventually, that’s going to translate into revenue, and that’s really going to set us up very nicely for strong continued growth.

Shrenik Kothari: Got it. Thanks a lot, Ash. Appreciate it.

Operator: The next question comes from Blair Abernethy with Rosenblatt Securities. Please go ahead.

Blair Abernethy: Thanks very much. Ash, just one more question, if I might, on the relevance engine. I guess I’m looking at this going very important and very powerful technology but I’m wondering, how are you looking at from a go-to-market standpoint, helping your customers to really get full leverage out of this? Is it through a step-up in professional services on your part? Is it through partnerships, training? And if you look back a few years, you guys built quite significant solutions around observability and security. Is there a similar kind of path here eventually?

Ashutosh Kulkarni: Yes. So the best way to think about our go-to-market on this is, effectively, it’s both a combination of the bottom-up motion that we’ve always driven really strongly with developers and the top-down motion that we drive through our go-to-market teams in the enterprise and commercial segments. So in terms of developers, like you’re seeing a lot of blogging from us. You’re seeing us be very involved in terms of the events that we are driving, like stand-ups and meet-ups and so on. And you’re going to see more and more of that from us because right now, this is – in these early phases, it’s the developer community that’s really leaning in and stepping ahead to build new kinds of generative AI applications.

And these developers are in every business, right, in every small and mid and large business. And they are the ones who are experimenting, who are playing with all of these capabilities. So we are making sure, first and foremost, that we are front and center with that community. We are leveraging the fact that Elasticsearch is so well known and really leaning into it. At the same time, our sales teams are going out there and making sure that all our large customers that they are using us for either search or observability or security, understand this new capability and what it can mean for them. We are having sessions where we’re doing brainstorming with our customers on, hey, what are the kinds of opportunities within your enterprise that this could unlock for you.

And so it’s going to be both in the bottom up and the top down. But what we will continue to build on top of is an amazing brand that Elasticsearch has out there in terms of search.

Blair Abernethy: Great. Thank you.

Operator: The next question comes from Raimo Lenschow with Barclays. Please go ahead.

Raimo Lenschow: Thank you for squeezing me in. We talked a lot about AI, but it’s kind of probably more the future. If I think talk more about the current situation, can you see a little bit what you’re seeing in terms of the optimization journeys we see with your clients? Where are we on that? It’s obviously a question that comes up for the hyperscalers, it does impact you a little bit as well. Can you kind of talk a little bit of what you’re seeing there in terms of where customers are in kind of identifying where they could spend less at Elastic and pushing it through versus like most of that is done from now on, people are as efficient as they can tend to start spending more with you? Is there any update there?

Ashutosh Kulkarni: Yes, Raimo. This is Ash here. Maybe I’ll lead off and then Janesh may want to add to it. But in terms of the most common kind of optimization that we are seeing customers doing with the existing workloads is moving more and more data to object storage, right, to our frozen tier. Like that’s one of the most common practices. And frankly, like we are leaning into that and helping them because like I mentioned, we are – the feedback that we are getting is that our frozen tier is actually faster than the hot tier of some of our most common competitors. And so that’s a huge advantage. Now the reality is that there’s only so much that you can move to the frozen tier and also when it comes to the fact that data itself is continuing to grow, like there are natural limits to what you can do in terms of optimization.

The fundamental question that you’re asking in terms of where are we on this journey? Like what – we’re not seeing any increased pressures, right. So like Janesh mentioned, where we are today is roughly like what we saw in the last quarter as well. But the data volume, the fact that data volumes are continuing to grow and the fact that newer workloads are coming on to our platform as customers consolidate onto our platform just means that that’s going to be the offset in the coming year and beyond. And that’s what we’re just leaning into because it also allows us to take market share. So when people become more comfortable in terms of their spending patterns, like that’s just going to be – by that time, we are going to be in such a better position in terms of market share that it’s really going to set us up very nicely for the future.

Raimo Lenschow: Yes. Okay. Perfect. Thank you.

Operator: Next question comes from Brent Thill with Jefferies. Please go ahead.

Brent Thill: Janesh, you mentioned the May sales kickoff. When you go into this next fiscal year, are there any major changes or tweaks you’re making on the go-to-market? Or is it pretty much following the same playbook that you followed last fiscal year?

Janesh Moorjani: Hey, Brent. The go-to-market model fundamentally for us will largely continue to be the same. If I think about the structures that we’ve had and the model that we’ve put in place, it’s working quite nicely. We are continuing to focus on building commercial and enterprise sales coverage. We’ve also had success with our focus on cloud, and we see that in the strong commitments and the sales force is effectively much more focused on selling cloud. We are increasing our focus on consumption as well a little bit. And starting this fiscal year, we’ve actually included a small consumption piece to the sales compensation plan as well. I think that will help overall as we think about scaling the cloud business in the future.

And if I think about the other elements of our go-to-market around our partnerships with the hyperscalers and the marketplaces, those are all working very nicely for us as well. As you saw with the announcements from – with AWS, we’re putting a lot of energy into this area. So we feel good about our overall go-to-market structure, but looking forward to executing here in Q1 and the rest of the year.

Brent Thill: And real quickly for Ash, just on the AI solutions. When do you expect the kind of stand-alone monetizable solutions on top of the platform will be able to be monetized. I know maybe you can’t give an exact GA date. But is that front half of the fiscal year, back half of the fiscal year? How do you think about the timing?

Ashutosh Kulkarni: Yes. In terms of the actual features, like they are available now. So it’s not about GA, it’s more about customers themselves building these applications and putting them into production, right? So it’s less about us delivering any functionality. We’ve delivered the core platform, right? The ESRE announcement was like the key announcement there. Now we are also building our own co-pilots, right, for observability and security all built on top of that same ESRE functionality, and those will be coming very shortly. But fundamentally, the platform for building generative AI applications are there today. And it’s more about customers sort of moving from where they are today, where they are trialing things, they’re playing around with things to getting to the point where they put things into production.

And as that happens, that’s – in my opinion, that’s going to follow some of the natural curves that we’ve seen in the past where you’ve seen like major technology platforms emerging but when the pendulum swings it swings in a very big way. So I can’t quite predict the timing, but feel very good about both what this represents in the long-term for us and our ability to be a winner in this space.

Brent Thill: Thank you.

Operator: The last question comes from Rob Owens with Piper Sandler. Please go ahead.

Unidentified Analyst: Hi. Thanks for taking my question. This is Ethan on for Rob. Janesh, I wanted to ask around the 100,000 plus customer base. It seems like consistent net adds here again in the quarter, but I wanted to ask around kind of revenue growth from this cohort for the year, whether that’s in terms of NRR relative to the rest of the base or kind of what the revenue mix was from these customers for the year relative to recent years? Any color you’d be able to provide on that would be helpful? Thank you.

Janesh Moorjani: Yes. Happy to talk about that a little bit. We don’t discretely break out the size in terms of dollars or the revenue from the space on a quarterly basis. But what I can tell you is that larger customers are increasingly focused on to consolidation. They see the benefits of the platform that we’ve talked about. They see the benefits of the consumption model. So when you think about our core land-and-expand motion, that continues to work quite nicely. Most of these customers that we added in this category started off as less than 100,000 and then eventually grew into the 100,000 plus category. And then the sales team, of course, also did well to close a number of meaningful deals in the quarter. So it’s a part of the business that is a good indication of expansion. It’s a good indication of our progress in the enterprise and the commercial side. And we expect that we will continue to drive that motion going forward.

Operator: This concludes our question-and-answer session. I would now like to turn the call back to Ash Kulkarni for any closing remarks.

Ashutosh Kulkarni: Thank you all for joining us today. Like I mentioned, we remain confident in our ability to drive both growth and profitability as we’ve demonstrated and are excited about our unique position in generative AI. We look forward to updating you on our progress as we go. Have a great evening.

Operator: The conference has now concluded. Thank you for attending today’s presentation. You may now disconnect.