and cloud architecture, leverages security-first principles, and incorporates AI/ML algorithms to deliver real-time actionable insights. We started in 2010 with the mission to provide organizations with the ability to ingest and analyze complex unstructured machine data, such as logs, events and security data for a cloud SIEM solution. However, we always had the vision to expand our data analytics capabilities to address less complex structured machine data, such as time-series metrics from applications and infrastructure, to provide a cloud-native operational intelligence solution. In 2012, when we released our service, we discovered that developers, IT operations, and security analysts were leveraging our platform to initially ingest and analyze log and event data in order to monitor and troubleshoot their mission-critical applications, systems, and services.
Our platform scans an average of 873 petabytes of data per day and an average of 18.6 billion events per second.21 Our platform integrates and analyzes structured, semi-structured, and unstructured machine data, both historically and in real time, to provide actionable intelligence around what happened, why it happened, and how to resolve business, technology, or cybersecurity issues.
We deliberately architected and built our analytics platform to address the technology challenges and gaps in intelligence that arise from siloed development, operations, and security teams in order to enable organizations to adopt a more modern DevSecOps operating model. DevSecOps is the philosophy of integrating security practices within the DevOps process, and involves ongoing, flexible collaboration among developers, release engineers, and security teams. DevOps is a combination of practices that automates the processes between software development and operations teams in order to build, test, and deploy modern applications faster. Ultimately, it enables teams to gain more insights and intelligence in order to release software faster, optimize processes, and better deliver digital solutions to customers. We offer a suite of solutions to address the intelligence gap: Operational Intelligence, Security Intelligence, Business Intelligence, and Global Intelligence.
We address both cloud-native businesses, as well as traditional on-premise businesses that are seeking to build, manage, and secure modern applications as they undertake their digital transformation and cloud adoption initiatives. We serve organizations of all sizes, from large enterprises to small and mid-market businesses, regardless of their cloud, digital transformation, security analytics, or DevSecOps maturity. Representative customers include 23andMe, Alaska Airlines, Brown University, JetBlue, Land O’Lakes, LendingTree, Major League Baseball, Netflix, PagerDuty, Petco, Pitney Bowes, Qualtrics, Salesforce.com, Twilio, ULTA Beauty, and Xero. Our customer count changed from 1,626 as of January 31, 2018 to 1,900 as of January 31, 2019, to 2,137 as of January 31, 2020, and to 2,130 as of July 31, 2020.22 Customers that had ARR greater than $100,000 or more grew from 187 as of January 31, 2018 to 234 as of January 31, 2019 to 323 as of January 31, 2020, and to 330 as of July 31, 2020.23 Customers that had ARR greater than $1 million or more grew from seven as of January 31, 2018 to 17 as of January 31, 2019 to 25 as of January 31, 2020, and to 29 as of July 31, 2020.
The power of our platform, and the benefits that it delivers to customers, has driven rapid growth in our revenue. For fiscal 2018, 2019, and 2020, our revenue was $67.8 million, $103.6 million, and $155.1 million, respectively, representing a year-over-year growth rate of 53% and 50%, respectively. For the six months ended July 31, 2019 and 2020, our revenue was $70.2 million and $96.6 million, respectively, representing a period-over-period growth rate of 38%. We generated net losses of $32.4 million, $47.8 million, $92.1 million, $29.0 million, and $35.8 million for fiscal 2018, 2019, and 2020, and the six months ended July 31, 2019 and 2020, respectively, as we continued to invest in our business.
Industry Background
Nearly every business must transform into a digital business or be disrupted. Customers now expect real-time, instantaneous, always-on experiences. To meet these expectations, successful businesses need to
21 | For the month of July 2020. |
22 | See the section titled “—Our Customers” for a description of how we calculate our number of customers. |
23 | See the section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations” for a description of how we calculate ARR. |
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