Elastic N.V. (ESTC) Q2 2019 Earnings Report, Transcript and Summary

Good afternoon and welcome to the Elastic Second Quarter Fiscal 2019 Financial Results Conference Call. All participants will be in 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 Anthony Luscri, Vice President of Investor Relations. Please go ahead.

Thank you. Good afternoon and thank you for joining us on today's conference call to discuss Elastic second quarter fiscal 2019 financial results. On the call, we have Shay Banon, Founder and Chief Executive Officer and Janesh Moorjani, Chief Financial Officer. Following their prepared remarks, we will take questions. Our press release was issued after the close of market and is posted on our website where this call is being simultaneously webcast. Slides which accompany this webcast can be viewed in conjunction with live remarks and can also be downloaded at the conclusion of the webcast from the Elastic Investor Relations website at ir.elastic.co. On this call today, our discussion may include predictions, estimates or other information that might be considered forward-looking statements within the Safe Harbor provisions of the U.S. federal securities laws. While these forward-looking statements represent our current judgment on what the future holds, they are subject to risks and uncertainties that could cause actual results to differ materially. These risks and uncertainties include those set forth in the press release that we issued earlier today, as well as those more fully described in our filings with the Securities and Exchange Commission, including our prospectus dated October 4, 2018 as filed with the SEC. You are cautioned not to place undue reliance on these forward-looking statements, which reflect our opinions only as of the date of this presentation. Please keep in mind that we are not obligating ourselves to revise or publicly release results and any revision to these forward-looking statements in light of new information or future events unless required by law. In addition, during today's call, we will discuss certain non-GAAP financial measures. These non-GAAP financial measures which are used as measures of Elastic's performance should be considered in addition to, not as a substitute for or in isolation from GAAP. Our non-GAAP measures exclude the effect of our GAAP results of stock-based compensation, amortization of acquired intangible assets, acquisition related expenses and non-GAAP tax rate adjustments. You can find additional disclosures regarding those non-GAAP measures, including reconciliations with comparable GAAP measures in the press release and on our Investor Relations website and slides accompanying this webcast. The webcast replay of this call and slides will be available for two months on our Company website under the Investor Relations link With that I'll turn it over to Shay.

Thank you, Anthony. It’s good to be here today and have everyone listening in on our first earnings call as a public company. I would like to start by taking a moment to thank our wonderful community of users, customers, developers, partners, investors and our employees and their families for contributing to our success. Q2 was a special quarter on many fronts, but ringing the bell on the New York Stock Exchange on October 5th was a very special moment for us. While it was a truly remarkable day, it was only one day in a long-term journey and there is much more to tell with our story. With that in mind, I'm pleased to share some high-level results from our very strong second quarter. In Q2, revenue grew 72% year-over-year to $63.6 million. We had more than 6,300 subscription customers at the end of the quarter, including over 340 with annual contract value of more than $100,000, and our Net Expansion Rate was over 130%, which we've maintained for eight quarters in a row now. Before Janesh gets into the details of financial performance, I would like to provide an overview of our business for those who are new or less familiar with Elastic. I will also highlight some recent product announcements and customer wins. Elastic is a search company. We believe search is foundational for a wide variety of experiences and use cases. You may not realize it but you probably use Elastic every day. When you catch a ride on Uber, we are the engine that matches the driver with you; when you look for groceries on Instacart, Elastic provides you with relevant results and recommendations; when someone swipes left or right on Tinder, Elastic gives powers finding a match you might like and who might like them back. Now, all of these experiences I just described need to be monitored, checked and observed. Elastic powers that to you. So, customers like Tinder and Barclays take their infrastructure logs or remote server metrics and put them into Elastic to understand what's working and what's not, both on the technology side and on the business side. And if you think about it, it doesn't take much to go from analyzing machine data to analyzing security events. So, a customer like Indiana University can build their cybersecurity operations on top of Elastic in order to protect thousands of devices and critical data. Everything I just talked about is search. So, what is about our search technology that makes us different? Three things: speed; scale; relevance. If something isn't fast, that's a problem. Users won’t wait minute for results to appear on sites like Wikipedia. Why should they wait for any other use case. If something takes more than a second, we cringe inside. It's all about having a discussion with your data, not running aquarium stepping away to make coffee only to come back and forget what questions you asked in the first place. At the same time, you need to have these fast experience at scale. So, going from one laptop to thousands of machines, you should all still operate the same. And it’s not acceptable to be fast and scalable and then return lousy results. So, relevance is critical here. These three elements, speed; scale; relevance, they are the core of the Elastic Stack. Now, at the heart of the stack is the Elasticsearch. It’s what stores, searchers and analyzes data, structured or unstructured, and it’s what everything gets built around. Beats and Logstash are ways to ingest data into Elasticsearch from many sources, and Kibana is how you visualize data in Elasticsearch. We also build solutions that are vertically integrated into our stack. They include app search, site search and enterprise search; logging, metrics and APM; business analytics and security analytics. You can think of solutions, as ways we've made it easier for users to get started with our software to address a particular use case. For example, today with our logging solution, you can start analyzing log files or add search to your website with our faster service in a matter of minutes. We also give users the flexibility to deploy our software the way they want. For our self-managed offerings, they download the software and then manages themselves on-prem in a public cloud or private cloud or even in hybrid environments. We also provide a hosted service, Elastic Cloud, which is our family of SaaS offerings and it includes our Elasticsearch Service, Elastic Site Search Service and Elastic App Search Service. We’ve also found that as customers grow their self-managed Elastic deployments and scale to many and many clusters, they want to enjoy a SaaS like experience to centrally provision, manage and monitor our products. Elastic Cloud Enterprise or ECE lets some do that. It’s a paid proprietary product that customers download and run in the environment of their choice. As we consider our market opportunity, we believe that it expands for current use cases and also as our technology deployed towards new use cases. For example, when we founded Elastic, many of our users took our products and applied them to solve use cases like apps search and enterprise search. And as we stated previously, this space had a total addressable market of $3 billion back in 2012. As our users deployed our products to power new used cases and we expanded our offerings, our TAM has grown to $45 billion in 2018. I will also take a minute to talk about our business model. It starts with our distribution model. We have an open source approach to distributing our software, which allows rapid adoption and innovation for our millions of users with little investment. And what this means is that users have an opportunity to experience the value of our products long before they ever speak to a salesperson. And by the time they do, it’s a warm customer value-driven conversation. We have a sense of who they are, what their projects look like, and what they are hoping to accomplish with our products. Our business model is based on a combination of open source and proprietary software that we make available to paid subscription, which also includes support. Some of our proprietary features like monitoring and Canvas are free, and some proprietary features like machine learning and security are paid. It’s also important to note that we do not build a separate enterprise grade version of an original open source projects like some companies do. Instead, we develop and test one codebase that we control. This allows us to guide and direct our product to meet the needs of our users more efficiently. So, it’s this combination of free and paid offerings alongside our open source solution and distribution model that has really allowed us to build powerful, user-driven, commercial business model on top of open source. As I reflect on customers and product activities over the past several months, I’ll start by saying that we travelled a lot, specifically for Elastic{ON} Tour events to engage with our community of users, customers and partners. These events are designed to deliver training and helpful content to our users that cover recent product developments. We went to 11 cities including Melbourne, Sydney, Boston, Chicago, Toronto, Minneapolis, Denver, Washington D.C., Stockholm, Frankfurt, and Santa Clara. We’re in our fourth year of hosting these events and we are humbled by their popularity. A few weeks back, I attended the Washington D.C. tour event. It attracted over 800 people. And I was amazed to see how many -- so many users building their future on top of us. As you might imagine, security is an important topic in the public sector. For many years, we’ve invested in creating really powerful security features, ranging from basic authentication and encryption to granular access control at the document, field and attribute levels. And at this D.C., event I noticed there was a lot of discussion around new security features we released in this quarter. This included support for running Elastic and FIPS 140-2 mode, which is critical to defense space, and Kerberos authentication, which has broader applicability to not only government audience but also to larger enterprises across the world. Take a company like Liberty Global, one of the largest telecom companies in the world, they became our customers, thanks to our advanced security features that I just mentioned, as well as our world-class support and additional commercial features. They are using us to analyze their log data, monitor systems, and investigate intrusion events. They expanded their usage with us in the second quarter, because of the further rollout and innovation of their next generation platform called Horizon 4. It was also amazing to see the positive reaction at our tour events to the pre-release of our cross-cluster replication faithful feature, which was in our 6.5 release a few weeks ago. This feature is important for fast searches and data locality. It is also important for high availability and disaster recovery. So, we’re excited to offer this robust and highly requested feature that would support search and replication across multiple public and private environments, including hybrid clouds. Another highly requested feature we released is Kibana spaces. When users adopt Elastic and probably ingesting data, one of the first things they do is create a handful of visualization and dashboards. And that handful often grows to be hundreds or even thousands very quickly. And we saw that users needed a better way to organize their visualizations into defined workspaces. One for the marketing team, another for DevOps, another for finances and so on. Kibana spaces makes this possible by allowing users to segment and secure Kibana for different audiences and used cases. Now, speaking of different audiences, I’m particularly excited about the preview release of another Kibana beneficial that we call Canvas. We are inspired by the fact that our users are proud to display their data. And we took this to heart and spent the last year working on Canvas to give users a personal way to display living dashboards that are not just pleasant to use but also pleasant to look at. It's been fascinating to see the adoption of Kibana in the places you'd expect, like a network or security operations center but over time we’ve seen it in less expectations, like office entrances and executive board rooms. To give an example, Brazil's Ministry of Health renewed their business with us in Q2 through one of our partners. They have Kibana dashboards permanent display in the Health Minister office. They show real-time health spending and service quality information that is aggregated from 400 data basis in systems. This is awesome. I'm excited about how easy it would be for them to deploy Kibana spaces and Canvas to further share and visualize information across the organization. Hopefully when I visited Brazil next year for our tour, I will see them both in action. In the logging and metric use cases, we’re continuing to execute well and are seeing strong momentum. Oracle’s cloud native engineering team selected Elastic software to help accelerate development and operations of common cloud services running in Oracle cloud infrastructure to support multiple SaaS applications. Elastic’s product allow for rapid collection, presentation and analysis of logs and key performance indicators. We’ve also doubled down on making it even easier for people to implement Elastic for the logging and metrics use cases. Recently, we provided two new user interfaces that provide curated experiences for logging and monitoring, various aspects of infrastructure, so things like servers, Kubernetes pods, Docker containers and services. We have also provided easier ways for users to ship data from more data sources like serverless applications and cloud services, and efficiently summarized data to save on space with roll up support in Kibana. So, as I talk about these features, I think about how they could streamline logging and metrics for customer’s like the car2go group, one of the largest car sharing companies in the world and a subsidiary of Daimler AG. They use Elastic to do things like monitor car connectivity and detect fraud, finalizing logs and metrics from Kubernetes and Docker, payment services as well as physical and virtual machines. In the second quarter, we renewed and extended with them, and I look forward to them getting started with our new logging and metrics UIs. Related to this is APM, which is another area where we’re continuing to invest by enabling our loving users to simply add APM data into their work flows. And I’m happy to share we recently integrated machine learning into APM and we lead support for additional programming languages like Java and Go. We also previously distributed interesting feature that lets user observe how application requests flow through services. We also had exciting development in our SaaS business this past quarter. We enabled a major feature on our Elasticsearch service that gives users more freedom and control over how they deploy our product. We’ve made it easy for users to deploy custom topologies like hot warm architectures, which is especially useful for logging use cases. What this means is, users can separate their department into hot and warm data nodes so they can query recent data quickly while retaining all the data for longer periods of time without breaking the bank. For example, the wireless sound system company Sonos is a new logging customer of ours that’s analyzing some device diagnostics and player telemetry. They chose our hosted Elasticsearch Service offering because of these features and upcoming developments that only we can provide. It's worth pausing to remind everyone that we are the only offering that provides features like Canvas, roll-ups, logs and infrastructure UI and many others that I mentioned earlier, no one else does. This is also true for the custom topologies feature, I just talked about. We are the only hosted Elasticsearch offering that provides this flexibility. I'm particularly excited about this feature because it allows our users to more efficiently run our products and manage costs. It also makes it easier for users to adopt our service or move self-managed workloads to a SaaS environment if they want. We also change and enhance our SaaS pricing model in order to reflect this flexibility. Now, all of these SaaS features I've just mentioned, we've also made them available in our 2.0 release of ECE. The new release makes the complexity of managing multiple Elastic Stack environments simpler, with many new features such as host tagging, customizable deployment templates including hot-warm architecture, automated index duration and more. For instance, we expanded our relationship with one of the largest U.S. broadband providers. A few years ago, they started out with a few nodes of open source and then grew to become a gold subscription customer. As of Q2, they are an enterprise subscription customer using ECE 2.0. The Company uses ECE for logging use case, ingesting 15 terabytes of machine generated data per day, over 200,000 events per second, providing real time visibility into everything occurring in their content delivery network. We believe this is a great validation of the value of our ECE products as well as our business model. As you can tell, we saw a strong momentum with our products and customers in Q2. Beyond the many customer stories I just highlighted, we saw a number of other notable wins. We also continued to invest heavily in all parts of the business, growing our engineering team, expanding our marketing reach and our sales coverage and investing internally for scale. I'll close by saying that we are very pleased with our Q2 results. With the continued strong demand across our business, we are uniquely positioned to capture that tremendous opportunity in front of us and we are pursuing it aggressively. With that, I’ll hand it off to Janesh to talk about our financial results in detail. Janesh?

Thanks Shay, and thanks again to everyone for joining us. To our new public shareholders, we enjoyed meeting many of you on the road show and look forward to building a long-term relationship with you. Because this is our first earnings call and some maybe new to the Elastic story, let me first go over some important aspects of our business model. Approximately 90% of our revenue typically comes from subscriptions, which represents recurring revenue. Our subscriptions for self-managed deployments generally range from one to three years for which we typically invoice customers annually in advance. Our SaaS customers purchase subscriptions either on a month to month basis or on a committed contract of at least one year in duration. Subscription fees typically vary based on subscription levels and the underlying memory and storage. The remainder of our revenue comes from professional services, which consists of consulting and training. The primary objective of our professional services team is to make our customer successful, which in turn drives higher subscription revenue as these customers expand their usage of the Elastic Stack and our solutions. Our direct sales team is organized by geography and by customer segments and we have a growing partner ecosystem. As Shay mentioned, our sales and distribution approach starts with a massive top of funnel that is fueled by the strength of the open source distribution model. Because users deploy our software long before they engage with the sales reps, sales engagements often start with warm leads and in many instances there is existing executive mindshare. All this leads to efficient sales cycles. There are a number of levers that drive our growth. I just touched on how we expand our customer base by acquiring new customers with an efficient model. Our customers also often significantly expand their usage of our products over time. Expansion includes increasing the number of users using our products, increasing the utilization of our products for a particular use case and applying our products to new use cases. Our Net Expansion Rate or NER is one measure of this. NER indicates the average increase in the spend of existing annual subscription customers net of churn compared to one year ago. Our Net Expansion Rate has been more than 130% in every quarter for the past 8 quarters, including Q2. With that, let me move to our second quarter results. I’d like to thank our employees for their hard work as we had both the strong second quarter and successfully executed our IPO. As Shay mentioned, total revenue for the second quarter was $63.6 million, growing 72% year-over-year. Subscription revenue totaled $58.4 million, an increase of 68% year-over-year and comprised 92% of total revenue. Within subscriptions, revenue from our SaaS products was also strong at $10 million, growing 79% year-over-year. We launched a significant update to our SaaS services, offering customers much more flexibility, and we revised our pricing model in conjunction with that. We’re excited about this change and the SaaS opportunity ahead of us. Professional services revenue was $5.1 million, an increase of 128% over the same period last year. Professional services revenue is typically recognized at the point in time the services are delivered and therefore can fluctuate quarter-to-quarter. We expect professional services will remain a small proportion of our overall revenue as our business grows. In terms of geographic breakdown, given our roots in open source and our globally distributed model, 14% of our revenue came from outside the U.S. with the majority of this coming from EMEA. We are very proud to have achieved such geographic diversification so early in our life as a company. We believe we have a rich market opportunity outside the U.S. and remain dedicated to investing appropriately to capture that opportunity. Moving on to calculated billings. We define calculated billings for any quarter as total revenue recognized in the quarter, plus the sequential increase in deferred revenue as presented on our statement of cash flows, less the sequential increase in unbilled accounts receivable. Calculated billings in Q2 was $88.5 million, an increase of 73% year-over-year. Calculated billings can fluctuate from quarter-to-quarter based on the timing of renewals and billing duration for larger customers. We also tend to see our strongest billings in the second and fourth quarters as a result of the buying patterns of our growing customer base. Given these factors, an additional way to look at calculated billings growth is on a trailing 12-month basis which provides a longer term view of the business. Trailing 12 months calculated billings growth ending Q2 was 77%. We were very pleased with the calculated billings throws this quarter and the underlying demand that is driving our business. The strong growth in Q2 was driven by a broad array of growth vectors including new customer additions, new use cases at existing customers, and larger deployments. As of the end of Q2, we had over 6,300 paying subscription customers compared to over 5,500 such customers at the end of Q1. We continue to see strong momentum with new customer additions. We also remain focused on growing the number of our larger customer accounts and ended the quarter with more than 340 customers with an annual contract value about $100,000 compared to more than 300 such customers at the end of Q1. Our existing customers continue to expand their relationships with us, reflecting increasing spend for existing use cases and adoption of new use cases. As I mentioned earlier, our Net Expansion Rate remained over 130% for the eighth consecutive quarter. When viewed connectively, these customer metrics provide insight to our execution against the enormous market opportunity ahead of us. Now, turning to profitability and other results, which are all non-GAAP. Gross profit in the second quarter was $46.6 billion, representing gross margin of 73%. Total subscription’s gross margin was 80%, compared with 82% in Q1. As planned, we continued to make investments in the SaaS business in Q2 and are tracking well relative to our expectations. In addition, I earlier referenced the more flexible pricing model together with the new SaaS features launched in August. In conjunction with scaling the adoption of our SaaS offerings, we also anticipate driving reductions underlying unit hosting costs. In the near-term SaaS will remain a modest segment gross margin overall. Over time, as the business scales and as we capture the significant market opportunity ahead of us, we expect to drive natural gross margin improvements. Our professional services gross margin was negative 4.9% as we added further capacity in advance of revenue and as existing hires ramp to productivity. As a reminder, since the professional services business is small, even relatively insignificant amounts can swing the gross margin and either direction. So, we expect that the gross margin and professional services will fluctuate significantly from quarter-to-quarter. Turning now to operating expenses. We remain focused on investing to drive top line growth. Sales and marketing expense for Q2 was $31.8 million, up 97% year-over-year, representing 50% of total revenue. While we expect to realize leverage in sales and marketing as we scale the business, our primary near-term focus remains adding sales capacity and expanding market coverage as we drive growth. I’ll also point out here the we replaced our annual Elastic{ON} User conference, which in the past happened in Q4 with series of local events spread over the course of the entire year. Shay mentioned our tour locations from Q2 earlier. R&D expense in Q2 was $20.5 million, up 88% year-over-year, representing 32% of total revenue. R&D remains a major investment area as we expand our innovation advantages. We don't feel open source is a mechanism to outsource R&D to the community. In fact, as the sole committers of code, we believe it is important for us to invest heavily in R&D to both widen and deepen the portfolio. G&A expense was $9.2 million, up 80% year-over-year, representing 14% of total revenue. This includes costs associated with our global expansion and continuing to build the infrastructure to scale for the future. Our operating loss in the quarter was $14.8 million with an operating margin of negative 23%. Overall, we continue to invest at a consistent pace in the business compared to recent quarters, as we continue to drive strong growth. Net loss per share in Q2 was $0.38 using 44 million basic and diluted shares outstanding. This compares to a net loss per share in Q2 of last year of $0.17. Free cash flow was negative $1.4 million in Q2 compared to a positive $3.6 million in the singular year-ago, reflecting the investments we are making in the business. Although we are slightly positive year-to-date on free cash, there are seasonal effects. Free cash flow is seasonally stronger in the first half, particularly in Q1 and weaker in the second half. There can also be some happiness with inflows and outflows. So, we look at it mainly on an annual basis and expect the full-year to remain negative. While we don’t formally guide to free cash flow, we expect to continue to gradually improve free cash margin on a an annual basis but it may not be in a linear trajectory, given period to period fluctuations. Turning to the balance sheet. We ended the second quarter with $318.6 million in cash and cash equivalents. We raised approximately $264 million in our initial public offering in October, net of all expenses, including some that remain payable at the end of the quarter. Lastly, we ended the quarter with 1,129 employees, adding 135 people in the quarter across all functions. Moving on to guidance. Before I provide the outlook for Q3 and the full-year, let me share with you our investment philosophy. Over the near to mid-term, given the significant market opportunity, we expect to continue to invest in our go-to-market operations, people and infrastructure to drive future top-line growth. In addition, innovation remains a top priority for us and we will continue to invest in R&D as well as pursue inorganic opportunities to pull our future into the present such as the Insight.io acquisition announcement that we made earlier this year. Long-term profitability is an important objective for us, and we see multiple paths to achieving long term profitability goals, depending on how fast we can continue to grow the top-line. Turning specifically to the third quarter and the full-year fiscal 2019. For the third quarter of fiscal 2019, we expect revenue in the range of $64 million to $66 million, representing a growth rate of 56% year-over-year at the midpoint. We expect non-GAAP operating margin in the range of negative 30% to negative 28%, and non-GAAP net loss per share in the range of $0.32 to $0.30, using approximately 71 million ordinary shares outstanding. For the full-year of fiscal 2019, we expect revenue in the range of $254 million to $258 million, representing a growth rate of 60% year-over-year at the midpoint. We expect non-GAAP operating margin in the range of negative 26% to negative 25% and non-GAAP net loss per share in the range of $1.35 to $1.30, using approximately 56 million ordinary shares outstanding. In closing, Q2 was an exceptional quarter. We delivered top line growth of 72%. I am very excited about the strong results and our momentum, and we continue to invest in the business given the significant market opportunity ahead of us. I look forward to sharing our progress with you throughout the rest of the year. With that, let's open it up for questions. Operator?

[Operator instructions] Our first question comes from Heather Bellini with Goldman Sachs. Please go ahead.

Great. Thank you so much for the question and congratulations on your first quarter being public. I was wondering if you could share a little bit -- I was looking at the customers with ACV over a $100,000, and there was a net increase this quarter of 40, which had great growth of 70% year-over-year in total. I was wondering if you could share with us how you see the split between existing customers ramping their deployments and as such getting to that greater than a $100,000 number as time goes by versus the number of customers that are attaining that status in their first purchase. Are you seeing kind of the balance between what you've normally been seeing there start to change? Thank you.

Hi, Heather. This is Shay here. Thank you very much for the compliment. We're very excited about our first quarter and being a public company, and we're very excited about the results. And thank you for covering us obviously as well. So, we’re -- personally and as a company, we're very happy with the balance between both new customers that ends up spending more than 100k with us and existing customers. This is reflected by the fact that -- first of all, we’re very happy with our NER number, which means that customers that start to spend with us grow in their spend with us year-over-year. We’d like to also start small. This is part of our distribution model; this is part of the small project starting, using our software, zero to no touch from us and then immediately starting to see value to the products themselves, and then eventually engaging commercially with us and then growing within the organization. But also at the same time, we do see opportunities that ends up being reflected through large deployments from the get-go that tends to be logging or security type deployments. I think Indiana University is a great example of a win versus Splunk in this case in the context of the security space. And we also see this new customers coming in directly above 100k.

And then, just a quick follow-up if I will, then. Is it fair to say then that you’re starting to see the average or the initial purchase of Elastic get bigger compared to the initial -- the initial bite of the apple is becoming larger from customers? Is that fair based on your comments you just made?

Heather, this is Janesh. In terms of the ASPs or deal sizes, broadly, I’d say, they are roughly consistent with where they’ve been. It’s still early innings for us. As I look at the numbers here in Q2, it was perhaps slightly higher than it’s been in the past. But, I wouldn’t necessarily call it a significant uptick or a trend at this point in time. But, we’re still pretty bullish about the future.

And our next question comes from Mark Murphy with JP Morgan. Please go ahead.

Yes. Thank you. And I will add my congrats on the robust results. So, Shay, I wanted to ask you at a very high level, how important, do you think machine learning technologies are going to be for the future of Elastic in areas like anomaly detection and root cause analysis, and also other areas? And also, just given the strength of the relationship that you have had with Google and Google Cloud, how do you think you can best fit in and leverage some of the frameworks like TensorFlow?

Thanks, Mark. Let me address this question, specifically. So first of all, we are great believers in machine learning. Specifically, in the context, machine learning is very broad, in the context, as you mentioned, of anomaly detection. And this is reflected by the fact that we acquired a company called Prelert almost three years ago, deeply believing in the fact that once data is in Elasticsearch, magic can happen. And part of it is the ability to automatically detect anomalies and then being able to immediately go and send it to the user. I will mention that part of the beauty of our stack is the fact that it’s fast, it’s very fast. So, first of all, users can go and suddenly refresh dashboards that they never thought would get refreshed within milliseconds, and then being able to see the results of it. And obviously, that’s immediately reflected by the ability to apply machine learning algorithms on top of the data. The fact that we can run their dashboards very fast also means that we can run machine learning algorithms on top of it very fast. So that’s one aspect. The other one to address your second question. We’ve built a foundation where you can store your data and execute search queries and search algorithms on top of that data, as I mentioned in an extremely fast manner. Our stack has always been extremely open. So, if you go and for example, see what the community has built on top of our stack, you would see integrations with TensorFlow, integration with R, [ph] integration with Pandas other very popular machine learning libraries and obviously we’re help the committee to drive this level of innovation. So, that's one tier. So, we definitely see that level of development and it’s happening every day. But also, we are developing our own set of machine learning algorithms and built-in features that are integrated directly into the stack. If I had to qualify between the two, I would say that our focus in more for more self-sufficient machine learning algorithms that don't require someone to be a data scientist to run them, that's reflected by our anomaly detection feature. At the same, obviously someone that knows how to run TensorFlow or Panda, or R, [ph] they are more in the proficiency level of a data scientists. To finish it, to touch on your point about Google, first of all, we’re super excited about the relationship that we have with Google and the fact that we are the official search or Elasticsearch hosting provided on top of Google Cloud together with Google or the Google Cloud platform. And we’re very happy with the fact that when data is stored in Elasticsearch, you can go and run almost any type Google machine learning algorithm out there on top of the data in Elasticsearch; that's very easy and very simple integration. So, all the innovation that Google does in machine learning, immediately applies to the benefit if someone ends up putting data in Elasticsearch itself.

Thank you for that Shay. And Janesh, as a quick follow-up, as the product stack is going to be evolving here over many, many years, where do you see the longer term mix of logging in terms of both the use cases, and I guess the logging related revenue, where do you think that would settle out? I think that it has currently been running around a third in terms of the use cases.

Sure, Mark. So, just in terms of a little bit of context to that. When we think about use cases in different projects, very often a project can actually span multiple use cases. A great example of that is a customer decides to put a search box on a website and you can call that a site search use case, but they’re also then reading the log files and analyzing those using the Elastic Stack. And so, that’s a case that touches two different use cases, which is why within our own CRM systems, as we try and track that information, it’s a multi pick list and any project can have multiple use cases assigned to it. And as we look at that data, logging represents a little bit over third of the self-reported use cases from that standpoint. Over time, obviously, we’re super excited about the opportunity in logging and security more broadly that represents significant opportunity for us. But, one of the things that’s really made us successful is following the community and evolving the stack and the features in the stack, based on what the community’s and users’ needs are. So, I can't look ahead and tell you that it will be a significantly larger or smaller portion, we will take that as it comes. Right now, we’ve just pleased with the execution we are seeing against Splunk in the logging space.

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

Shay, since it’s the first quarter, I’ll ask a more basic question. I was wondering like, I used to cover the first generation of search guys, proprietary, like the autonomies and the fast search, and I know what you usually engaged as well with the other open source projects around UC. [Ph] What makes Elastic so special, why did the other guys not succeed where you clearly are seeing a lot of success? And then have a follow up for Janesh.

Yes. Maybe I can touch on it a bit. So first of all, ever since we created Elasticsearch and then when we formed the Company, our goal was to try to build a product suite that allows for very easily add many different type of data sources on top of Elastic, whether it's through the ease of use of the API-driven development, whether it's through the ease of use of creating visualization for many different use cases. Whenever we develop a feature, we think about it from a pure search perspective and then we're always curious about the fact how will that end up applying to many different use cases, the new use cases down the road. I would say, previous companies, even though they had sometimes similar vision by the way when they started, they ended up constraining themselves towards the enterprise search use case. And for that reason, when you concern yourself to a specific use case, you end up communicating it to your user base. I like to say that, when I created the Elasticsearch, I never thought that someone will end up taking a log message or log files and end up putting them in Elasticsearch. I was 100% sure that search applies to many use cases, I just didn't know which ones. But, then, someone decided to put a log message in Elasticsearch and they decided to put the log message in Elasticsearch but not in any type of the enterprise search products out there. They decided to put their log message in Elasticsearch and not in any of the NoSQL solutions out there, they decided to take a log message and put it in Elasticsearch and not into Hadoop vendors out, especially in the early days. And that speaks to the fact that we're building products that allow to people to innovate and imagine what could happen when they put different types of data into Elastic and then see the results of it.

Okay, perfect. This very clear. Thank you. And Janesh, can you just give us an idea about your framework as you're thinking around cash? Because you seem like much, much better than a lot of the other group companies around cash generation and how you run the Company. Is that kind of like the framework around cash breakeven if that’s kind of the right way to think about it or what are scenarios to kind of move away from that one? Thank you.

Hey, Raimo. Thanks for the question. So, in terms of cash investments, we actually think that the appropriate thing for us to do at this point in time is to invest in the business. And so, if I think back to fiscal ‘18, our free cash flow margin was negative 15%. We've been skating close to positive breakeven here in the first half, but that's really the effects of seasonality. There are seasonal effects here and the cash flow. The back half tends to be seasonally weaker and that's mainly because of strong collections that we typically have in Q1. So we look at it really on an annual basis ourselves. And we expect that from a full-year perspective, the free cash flow margin will be negative. We don't formally guide to it as I mentioned in my prepared remarks. But, we do expect to see some improvement in free cash flow margin over the course of this year and on an annual basis. But, it won't be a linear trajectory. Right now, we're still focused on investing to drive growth.

And our next question comes from Matt Hedberg with RBC Capital Markets. Please go ahead.

Hey, guys. Thanks. I’ll offer my congrats as well. Shay, on the call, you gave a few examples, but I'm wondering if you can give a few more details on the adoption of your Elastic Cloud Enterprise offering. So, what customers are you seeing are the primary adopters there? And is there a particular preference for where these customers are deploying ECE?

Sure. Hi, Matt. Thanks for covering us. Yes. So, our ECE product, which is part of our enterprise subscription is geared towards the more higher tier type spend of our customer base. It's definitely priced like that. And our go-to-market with it is, I would say two-fold. The first one is, as I mentioned in our adoption model, we start to see people or customers or companies adopting us in one project, and then another, and then another, and you suddenly see 20, 30, 50 projects, very different use cases. By the way, some of them, we explicitly define; some of them can be fraud or others that always keeps on surprising us to be completely honest. In that case, once a company needs to manage 20, 30, 40, 50 clusters or 50 deployments of Elastic, e can give them the product that will basically make it into a seamless experience, a SaaS like experience, if you will, within their own deployments, and within their own infrastructure. So, that’s one aspect of ECE. The other one is, we see customers wanting to go and deploy logging as a service, for example. So, I call it use case as a service for the rest of the organization to start with one project and see that it’s very successful in the logging projects, they suddenly look around and ask who’s using Elastic for logging, and suddenly, there’s 5 or 6 more teams that raised their hands and say that they use us for logging as well. And then, they use ECE as a way to provide logging as a service, again, in a SaaS like experience. It’s exactly the same as you go to our SaaS service and provide it to the rest of the org. And that’s critical. That’s like another level of multi tenancy that people don’t necessarily expect to have. And we worked really hard to make sure that our user base or our customer base will end up having the SaaS like experience within the org if they want to when it comes to use case as a service. So, those are two typical use cases or two typical patterns that I see of the adoption of ECE that I’m super excited about. And obviously, that works towards being more of a high end product and something that will end up selling when the increased usage of Elastic ends up going above a specific threshold.

And then, Janesh, your international exposure at 40% is impressive for a company of your size. Can you talk about the rate of pace of investments overseas? I know it’s primarily in Europe, but just sort of wondering how you think about deploying dollars internationally relative to the U.S. opportunity.

So, in terms of the investment profile, let’s say, we’re investing really in all geographies and segments at this point in time. We’re aren’t necessarily focused on limiting it to certain parts. We’ve made pretty significant investments across the world in Asia Pacific and Europe, and clearly right there in the U.S. is enormous opportunity. So, as I think about where we’re adding, not just sales capacity but all the other elements of the go-to-market operations that help make a sales rep successful, it’s really across the board in every geography that you can think of.

And our next question comes from John DiFucci with Jefferies. Please go ahead.

Janesh, you said you’re an early innings here. And Shay, you I think have gone through all the technology and all the use cases. By the way, Shay, I think you’ll that guy or that woman who put log messages in Elasticsearch, [indiscernible], that was great. But, maybe move something else, like I think Elastic and I think of all the various use cases, [ph] and I’m just curious, are there any new use cases starting to emerge, like logging that you didn’t anticipate and even things that perhaps we didn’t have solutions for and now people are like, you know what, we can actually solve this problem, we never could before. Because like when I look at the opportunities for Elastic and I can looking at log analysis and I can look at APM and I can look at all those markets. But something inside tells me that there is a lot of other things, that I just -- I don’t have defined yet. And you’re going to see them before anybody else is, and I'm wondering if you’re seeing that yet.

Sure. Thanks, John, and by the way, we do hope better than just buying that percent, we actually hired them. So, we’re comfortable with them being with us in the company and obviously I thank every day that I see them. But so maybe I can address it. The first bit that I would say is that actually we treat APM and security and to a degree business analytics as well, as the early innings of these use cases, specifically for example if you look at security and APM, it feels to me -- and the way that I judge is the way that we saw logging five years ago. So, it's only getting started. We are in the process of making sure that the experience is smooth for the user, we’re doubling down that use case, curated UIs, curated injection of data sources, everything that user expects us to have as a logging solution. I would argue that we have it today and even this last quarter you’ve heard about this dedicate infrastructure UI that we build and logs UI and being integration with new systems like Kubernetes and Docker and others. So, when it comes to security and APM, we’re just in the beginning. Actually the way that we position AMP is not as a replacement to other APM vendors, we just think it’s a net add to any logging and metric solution out there that we have customer using us today. Also, I would like to call out Canvas as another -- as something that is early innings as well. Canvas is a way to take data that exists in Elasticsearch and expose it to a whole new audience that we didn’t necessarily see. And I’ll admit like, this is something that we saw happening and then we ended up developing it as a result of it. When I would go and visit customers, whether it’s walking through the customers’ halls and see Kibana dashboards on screens in their office entrances or talking to CCOs and CIOs and seeing those screens on their main screens in their office, and I would cringe a bit inside because that's a dashboard that I would want to use as an operator, not necessary dashboard I would want to use and put as an entrance to my office. So, we’ve developed Canvas to try to expand these -- the data that exists and to other audiences. So those are -- to be honest, because we’re an open company and an open source companies, what we’re doing and how we're moving forward and the investments that we do is out there. And we’re very open with you and with the community around what we develop and some of these projects are in the early stages of them. Canvas has been in development for a year and has been out there for almost 9 months now. So, we’re super excited about the investments that we do in these three segments, for example and see where they take us.

And our next question comes from Kash Rangan with Bank of America Merrill Lynch. Please go ahead.

Shay and Janesh, we did a survey of enterprise search, we were stunned to find out that majority, 90 plus percent of respondents were actually legacy technologies for search. I’m curious how you see a replacement opportunity for Elastic that it’s third generation technology vis-à-vis to old landscape of old legacy search technologies? Secondly, as you get into the next 12 months, how does your sales capacity growth plan looks like?

Maybe I can address the first one, it was a bit spotty but I think I got the question. So, if I may repeat the question for a second. The way that I understood it is, well, there's a lot of search projects out there today already that don't necessarily use Elastic but people are super excited about using Elastic in order to solve them. So, how do we see the opportunity in that context. And I would say that I'm also super excited about it, like that's the beauty of what we’ve built. The use cases are out there and some of them are actually we can go in and put a whole breadth of fresh air into them. So, specifically for example, we acquired a company called Swiftype, and as a result of it, we immediately got the ability to add a search box to a website with Swiftype site search. Within minutes, we go and call the websites and create this customized UI and what have you. But also Swiftype developed this enterprise search product that I'm super excited about. It's in beta today, it’s in close beta today. We did redirect investment in Swiftype when we acquired the company towards site search and what we call app search, but we’re super excited to get back to enterprise search and invest in creating this as we call use case or solution-based product that is mix replacing or investing in just new projects in the enterprise search market.

And cash, just to touch on the bit about the sales capacity. To give you a sense, we added 135 people in Q2. If you sort of think about general industry trends and ratios of how many people tend to be in sales and marketing and industry standard ratios around sales reps and so forth, our numbers will look and feel similar to that, so you can get a pretty good sense of how we're adding sales capacity. Looking ahead for the next few quarters, I'd say we'll continue to invest as quickly as we can. I think it also just comes down to how quickly we can actually hire people and just the physics of the laws of execution, if you will. There's that piece that plays into it. And then as you hire people in certain territories, you want to give territories time to mature, time to settle, help people ramp to productivity pretty quickly before you start to -- if you inject too much capacity too quickly, you can actually have an unintended consequence. So, we're just thoughtful about that piece as well. But fundamentally, we're investing as quickly as we can to spur growth for the future.

Our next question comes from Tyler Radke with Citi. Please go ahead.

Good evening. Thanks for taking my question. I'm just curious if we could just talk a little bit about philosophically how you're approaching reinvesting back in the business. Obviously the quarter and the top line guidance was very strong, but it looks like you're taking most of that upside and deploying it back into the business where you’re seeing good returns. So, do you feel like you've -- are almost under hiring at this point, and what are the primary areas where you feel like you need to invest the highest? Thank you.

Hey, Tyler. So, in terms of the investment profile, as you mentioned yourself, I think for us, it's all about investing to capture the opportunity that's ahead of us. That's where we're focused at this point in time. We are actually quite pleased that we're able to take at least some of the upside, if you will and see that translate into a little bit of upside on the bottom line as well. But looking ahead, you'll see that we reflected in our guidance that we'll continue to invest as we drive upside in the business. That's the focus area for us primarily. And in terms of where that investment is going, it's really across all the functions. If I think about R&D, it's super important for us to keep investing there as well because unlike some companies, we don't view open source as a mechanism to outsource R&D to the community. In fact, if anything you believe that we need to continue to maintain the pace of innovation and leadership there, on the go-to-market side, it’s about expanding coverage and expanding the different routes market that we have. And then as we still in such a distributed way across the globe, from a G&A perspective, we’ve got to be there to enable the business and make sure that the infrastructure is there for the business to scale. So, it’s really across all dimensions that we are continuing to invest in the business.

And last question, just curious if there have been any type of acceleration, either in the business there, competitively, given the IPO and just greater awareness?

Yes. I can take that. Hi, Tyler. Not necessarily. I mean, the IPO obviously made us well-known. But I would say that open source roots and our broad adoptions, we reported historically about the number of downloads and the number of users and customers that we have. That’s exciting for us. So, the people that use our products, know about us. And that’s the most important thing. And they know us, the use us and they get excited about the products and then they continue to use us and hopefully become our customers.

And our next question comes from Richard Davis with Canaccord. Please go ahead.

For firms at your stage of growth, the key to success is kind of that well oiled sales machine, and then the sales motion that you can replicate. Do you believe you have that -- I mean your numbers are good, obviously, but do you believe you have that sales motion nail down? And could you just -- one of the things that we see with companies like here, just where if your salesmen do start to engage with the prospect, is there a certain size, how do you titrate that so people don’t run like rabbits all over the place to the wrong stocks? Thanks.

Hi, Richard. Let me take that if I may. So, first of all, we’re humbled to have a very senior sales executives that we have in Elastic that have seen this level of growth and scale historically in their life. So, they help us obviously make sure that we don’t only capture the opportunity that is in front of us, but also make sure that we implement the right foundational structures to grow correctly to capture the opportunity that is way ahead of us. I think that the best place that it’s reflected is in our geography -- geographical distribution of our sales force and also the fact that we’ve already implemented segmentation within the sales force. So, these two aspects allow us to have multiple vectors of growth in hiring. And obviously couple that with multiple use cases and other factors in our open source distribution model that makes it to a pretty unique and very exciting combination for us. The other part that I would say is, and maybe that touches into data geographical and segmentation. Our goal is to engage with the customers at the point where they’re already using us. We don’t necessarily want to engage with customers when they don’t -- haven’t used us yet. That’s the whole point of open source and free distribution model. But once they do, we will engage with a customer whether they’re small or big, where they have a small projects or a large project that they start to use us. And we can use that in a more efficient manner, thanks to the segmentation that we have within the sales force obviously. The last thing that I would say when it comes to the sales force, one of the challenges and mistakes that open source companies have done historically is that they’ve engaged with the developer over the first or second tier of engagement within our organization, but then that’s the limit of their skill that they had. We’re building a sales force that can sell all the way up to talking to the CCO or CIO or C level executives and make sure that they -- we can help them make a decision to implement Elastic across the whole organization. And we’re implementing the steered or segmented model to make sure that we address all of these aspects. That’s a in a nutshell our sales go-to-market and obviously, that means that we have a lot of vectors. And as you can see, we’re investing heavily in that.

And then, here is simple question for Janesh. What’s the fully diluted share count so that we can calculate enterprise value?

87.5 I believe when I last checked, but I will confirm that. 87.5, yes.

And this will conclude our question-and-answer session. I would like to turn the conference back over to Shay Banon for any closing remarks.

Yes. Thank you. Thank you all for joining the call. Q2 was a strong quarter for us. And we look forward to seeing many of you at the Barclays conference later this week and continuing our momentum through the remainder of fiscal year 2019. Thank you all very much.

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