Koji Ikeda: Hi guys, 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 ads the $100,000 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 $100,000 or is it customers that are well above $100,000, that’s driving that cloud tread, maybe it’s a combination of both, just looking for some more color here?
Janesh Moorjani: 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. 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 and then that then drives the mix of revenue So our strategy to focus on customers that have a higher propensity for growth is working quite nicely.
We are seeing those customers expand, we are seeing that make larger commitments and I think that’s actually been working quite nicely for us. And then if I look at the customer metrics for more than $100,000, 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 $100,000 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 and so that’s very consistent with the theme of consolidation that we talked about in continuing commitments from these customers, it 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.
Koji Ikeda: 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?
Janesh Moorjani: Yes, the net expansion rate in the first quarter, it moved as we had expected it would. You’ll recall that we had covered this on the prior earnings call as well, and 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 had 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 committees are not in the number, but the slower consumption is. 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 prior quarter.
So the slower net expansion rate has been from slower expansion. 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 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 will continue to monitor that as we go, but so far it’s playing out as we had previously predicted.
Koji Ikeda: Super helpful. Thank you so much for taking the questions.
Operator: Thank you. And our next question today comes from Jacob Roberge with William Blair. Please go ahead.
Jacob Roberge: Hi, thanks for taking my questions and congrats on the great results. Just going back to those hundreds of paying customers using ESRE in vector search, how would you characterize kind profile of those customers? Are you seeing that more from existing customers kind of upgrading platform SKUs and lifting expansion rates or is that actually starting to drive some new logo activity of – to Elastic as well?
Ashutosh Kulkarni: Yes, so we’re seeing a mix of both, right? So keep in mind that our motion has always been a land and expand motion. So, new customers come to Elastic typically onto Elastic Cloud using the monthly subscription 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, even in the monthly cloud use cases that we’re seeing. We are seeing customers use us for the generative AI use cases that I mentioned. The examples that I gave were all customers using us with annual contract rates in my prepared remarks. And keep in mind that when you think about the value that we bring in the area of generative AI, like what I’m hearing from customers is that really there are four key reasons why we tend to win and why we tend to do very well.
First is, we simply have really, really good vector database implementation. It performs very well, 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, et cetera, 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. And lastly and this maybe comes back full circle to the point the question that you’d 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 that data is already sitting in some Elasticsearch instance. So if you are in 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 is a massive Elastic Search community out there that might not be paying us today, 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. They 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 Elastic Search looking to us for this.
Jacob Roberge: 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 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?
Ashutosh Kulkarni: 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 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 had some wonderful stats of what they were able to do in terms of saving hours for their support engineers and making their job a heck of a lot easier and better. 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 and years. But discreetly, we are not looking at that as a significant impact for fiscal ’24.
Janesh Moorjani: 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 particularly 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’re providing, it’s about the same in the aggregate. 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.
Jacob Roberge: Great. Thanks for taking my questions and congrats again on the great results.
Ashutosh Kulkarni: Thank you.
Operator: Thank you. And our next question today comes from Matt Hedberg with RBC Capital Markets. Please go ahead.
Matt Swanson: Yes, thank you. This is Matt Swanson on for Matt Hedberg and I’ll echo my congratulations as well. You know 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? Basically, when you’re having those C-level conversations, how much this 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?
