Cloudera, Inc. (NYSE:CLDR) Q4 2018 Earnings Conference Call April 3, 2018 5:00 PM ET
Kevin Cook - Vice President, Corporate Development and Investor Relations
Tom Reilly - Chief Executive Officer
Mike Olson - Co-Founder, Chairman and Chief Strategy Officer
Jim Frankola - Chief Financial Officer
Sanjit Singh - Morgan Stanley
Mark Murphy - JPMorgan
Kash Rangan - Bank of America/Merrill Lynch
Walter Pritchard - Citi
Karl Keirstead - Deutsche Bank
Michael Turits - Raymond James
Greg McDowell - JMP Securities
Jack Andrews - Needham
Rishi Jaluria - D.A. Davidson
Abhey Lamba - Mizuho Securities
Good afternoon. My name is Chantal and I will be your conference operator today. Welcome to the Cloudera Fourth Quarter Fiscal Year 2018 Quarterly Results Conference Call. All participant lines have been placed in a listen-only mode to prevent background noise. After the speakers’ remarks, there will be an opportunity to ask questions. [Operator Instructions] Please note this conference is being recorded.
Your host is Kevin Cook, VP, Corporate Development and Investor Relations. Kevin, you may begin your conference.
Thank you, Chantal. Good afternoon and welcome to Cloudera’s fourth quarter fiscal 2018 conference call. We will be discussing the results announced in our press release issued after market close today. From Cloudera with me are Tom Reilly, Chief Executive Officer; Mike Olson, Co-Founder, Chairman and Chief Strategy Officer; and Jim Frankola, Chief Financial Officer.
During the course of this call, we will make forward-looking statements regarding future events and the future financial performance of the company. Generally, these statements are identified by the use of words such as expect, believe, anticipate, intend and other words that denote future events. These forward-looking statements are subject to material risks and uncertainties that could cause actual results to differ materially from those in the forward-looking statements. We caution you to consider the important risk factors that could cause actual results to differ materially from those in the forward-looking statements in the press release and this conference call. These risk factors are described in our press release and are more fully detailed under the caption Risk Factors in our quarterly report on Form 10-Q for the quarterly period ended on October 31, 2017 and our other filings with the SEC. Cloudera’s quarterly report on Form 10-Q which also includes an explanation of our net expansion rate, was filed with the SEC on December 8, 2017.
During this call, we will present both GAAP and non-GAAP financial measures. Non-GAAP measures exclude stock-based compensation expense and amortization of acquired intangible assets. In addition, we provide a non-GAAP weighted average share count that assumes the conversion of our preferred stock into common stock and the weighted impact of common stock issued in our IPO as if the issuance occurred on the date of effectiveness. These non-GAAP measures are not intended to be considered in isolation from, a substitute for, or superior to our GAAP results and we encourage you to consider all measures when analyzing Cloudera’s performance.
Additionally, our commentary today and the guidance we provide are under existing accounting standard ASC605. For complete information regarding our non-GAAP financial information, the most directly comparable GAAP measures, a quantitative reconciliation of those figures and updates to our Global 8000 list, please refer to today’s press release regarding our fourth quarter fiscal 2018 results. The press release has also been furnished to the SEC as part of a Form 8-K.
In addition, please note that the date of this conference call is April 3, 2018 and any forward-looking statements that we make today are based on assumptions that we believe to be reasonable as of this date. We undertake no obligation to update these statements as a result of new information or future events.
I will now turn the call over to Tom Reilly.
Thank you, Kevin. Hello everyone. Thank you for being with us today to discuss our fiscal fourth quarter and full year 2018 results. We are reporting a solid Q4 and finished to a fiscal year of considerable accomplishments for Cloudera and our team. In our first few quarters as a public company, we introduced 6 major product offerings, completed a strategic acquisition and delivered significant technological innovations with the open source community and also proprietary to our products. Our focus remains at significant opportunity ahead for the company and our market. Our journey is just beginning.
The next several phases of Cloudera’s growth have already begun to take shape. Enterprises of all sizes are just embarking on their digital transformation to enhance competitiveness in today’s increasingly connected world. In this new world, our customers are benefiting from these machine learning and artificial intelligence to gain competitive advantage. And with the availability of vast amounts of low cost compute and storage in the public cloud, enterprises are able to perform work they simply couldn’t do before thereby expanding our market. Cloudera is well-positioned for these dynamics and we will be spending time in today’s call discussing our unique advantages of machine learning, analytics and the public cloud.
First so, I would like to quickly summarize our financial results. Revenue for the fourth quarter was $103.5 million representing year-over-year growth of 42%. More importantly, we generated subscription software revenue of $84.3 million representing year-over-year growth of 50%. In addition, we added 32 net new Global 8000 customers in the quarter and we graduated a sizable group of customers to greater than $1 million of annual recurring software revenue. This class now comprises more than 60 customers with ARR greater than $1 million, collectively contributing half of our subscription software revenue. The consistent growth in consumption of our platform and adoption of the use cases represented by the large enterprises drives our land and expand model.
Our net expense rate for Q4 continues to be strong at 136%. For the full year fiscal 2018, we reported revenue of $367.4 million representing year-over-year growth of 41%. As in prior periods our high margin subscription software revenue grew at a faster rate than total revenue, 50% year-over-year to $301 million. We added 132 net new Global 8000 customers during fiscal 2018, exceeding our annual objective. Finally, we are pleased at the leverage has been demonstrated in our model. Annual revenue grew 41%, while expenses grew only 16%.
Now Mike Olson, our Chief Strategy Officer and Co-Founder will discuss the market outlook and reflect on the innovation that we have produced to capture more opportunity.
Thanks Tom. In a digital and hyper-connected world, data has become the world’s most valuable resource. Enterprises in every industry are going through a digital transformation. There are three fundamental trends that underpin this change. The first is re-architecting our legacy platforms, moving beyond cumbersome and expensive technologies like traditional data warehouse which simply can’t capture and analyze the vast amounts of – types of data generated by our increasingly connected world. The second is machine learning and AI applying powerful new techniques to that data to get insights never before possible and then acting on those insights. The third is the adoption of the public cloud, taking advantage of the agility and flexibility that it offers. Against this backdrop Cloudera is positioned to be the partner of choice for enterprises in pursuit of digital transformation.
Let’s go through each of these three trends and our differentiation in a bit more detail. To start, we are successfully disrupting the traditional data warehouse market. For many years data has been locked in silos making it impossible to build integrated analytics across all the organizations data. Our enterprise customers are re-platforming, building data lakes instead of data warehouses that allow them to secure the data once and then process, analyze and serving for any application under exactly the same governance and regulatory controls. SQL access is critical to capturing data warehouse workloads. We deliver Apache Impala for SQL at a cost and performance is genuinely disruptive to legacy players. But our modern platform also allows customers to go further doing text analytics, stream processing and machine learning on that same data, it’s extraordinarily valuable to customers to be able to run both traditional and cutting edge jobs on the same platform, same platform, same data, different jobs. What makes our multifunction analytic capability possible is the Cloudera Shared Data Experience, or SDX. SDX delivers a consistent framework for data management governance and security enforcement across all types of processing and analysis. SDX eliminates the need to copy or move data to perform these different types of workloads. We are moving cost, complexity and risk.
The second trend in digital transformation is the rapid advance of machine learning and artificial intelligence. Many large enterprises are struggling to take advantage of these new capabilities because there are no clear market definitions, industry standards or best practices. As a result, we have set ourselves on becoming the leading platform for machine learning in the enterprise through product innovation and industry expertise. To help obtain the lead, we made two important acquisitions in the past 2 years. We acquired Senstar I/O an innovator in data science. The IP that the Sens team brought has become the Cloudera Data Science Workbench, a self-service data science framework that enables developers and data scientists across an enterprise to collaboratively build, scale and deploy machine learning applications using the most popular programming languages and deep learning algorithms. Data Science Workbench is positioned to solve the full lifecycle of machine learning application development. More recently, we acquired Fast Forward Labs, a leading applied machine learning and AI research company specifically to focus on helping customers take advantage of state-of-the-art machine learning capabilities, including the latest open source algorithms to solve real world problems.
Lastly, IoT workloads benefit enormously from machine learning. Over the past 5 years, we developed Apache Kudu. And last year, we contributed it to the open source community. Kudu is a one-of-a-kind open source data store specifically designed for IoT use cases in its first year of general availability as part of Cloudera enterprise, more than 100 large enterprises have adopted Kudu. The third trend for digital transformation is the embrace of public cloud. Our customers want to take advantage of the flexibility that public cloud infrastructure provides. They benefit from large scale storage and compute. They were able to run transient or bursty workloads without buying lots of hardware. Cloudera is capitalizing on cloud adoption by allowing large enterprises to run analytic workloads anywhere they choose. Our large enterprise clients typically maintain a hybrid approach. They operate their own data centers and want to run applications on more than one public cloud.
We allow them to move workloads among the major public clouds to private clouds and to and from their own data centers to meet their business needs enabling any analytic workload on any cloud in any location. In fiscal year 2018, we made significant advancements in our cloud capabilities with the introduction of the Cloudera Altus family, our platform-as-a-service offering. Altus delivers the speed, convenience, elasticity and ease-of-use expected in native public cloud services. Altus is uniquely multi-cloud and multifunction running on both AWS and Azure for data engineering and analytics. We continue to innovate in cloud and we expect to introduce new Altus offerings in the future. For these platform-as-a-service offerings, we handle deployment management and operations allowing customers to concentrate on their data processing and analytical work.
We recognized the importance of analytics machine learning and cloud years ago. We invested early and substantially in these areas, including strategic acquisitions. This investment has resulted in a modern platform and differentiated offerings that positioned us well for our next phase of growth. Ultimately, we intend to automate decision-making and to deliver insight into applications in real time to fulfill the promise of a digitally transformed enterprise, more on that in a future call.
I will now turn it to Tom to review the priorities for fiscal 2019 and other updates.
Thank you, Mike. We are very proud of all our product and innovation achievements this past year. But our business is really defined by our customer’s success in their digital transformation. One of the most powerful elements of our platform is its broad applicability across dozens of industries and hundreds of use cases. Data is at the core of every digital transformation. Every industry is being transformed, some industries ministries are well along in this journey and some are just beginning, but every company in every industry must transform in the coming years or risk being disrupted. For example, the telecommunications industry is being disrupted by over-the-top players and is characterized by intense efforts by competitors to take away each other’s subscribers. In response, telcos are focused on creating new revenue sources and protecting existing ones. They are leveraging data to gain insight for promotions, enhance customer support and to reduce churn.
One of our customers, Deutsche Telekom, is aggressively transforming their business using our platform from machine learning. These machine learning applications have enabled Deutsche Telekom to reduce churn 5% to 10% and revenue loss from fraud by 20%. Healthcare and life sciences companies are also being transformed with data. To remain competitive and keep drugs affordable, they need to innovate, get product to market faster and improve patient outcomes. Use cases like population health, precision medicine, genomic research and streamlined drug development are benefiting from machine learning in modern analytic techniques. For instance, our customer GlaxoSmithKline is focused on accelerating the mapping, conformity and analysis of clinical trial data across multiple trials. It would ordinarily take months to complete this work. Today, GSK’s researchers performed the analysis in minutes. Using our platform, GSK has increased its processing of clinical trial data by approximately 100x, accelerating time to market and creating significant business value. And of course we are all familiar with the major transformation taking place in banking and financial services. In retail banking, institutions are focused on the digital customer experience including next best offer, cross-selling and up selling, in order to capture wallet share and grow revenue. At the corporate level, regulatory use cases such as fraud prevention, any money laundering, risk analysis and legal document review are all Board level concerns.
At TD Bank for example, over 25 corporate units use our platform for a variety of functions, including product recommendations and sentiment analysis. Factoring 5 years of transaction data for 11 million customers in minutes, these initiatives have improved customer service, increased revenue and reduced risk all the while lowering data management costs of the firm by 60%. In the simplest terms, our software empowers people to translate complex data of any type into clear and actual insights in order to grow their businesses, connect their products and services and to protect themselves in a world of increasing risk. As demonstrated by these use cases, we understand that the greatest opportunity exists in the large enterprise segment of the market what we have labeled the Global 8000.
While we surpassed our objectives for net new Global 8000 customer additions this past fiscal year, we still expected too much from our valuable selling resources pursuing customers outside that market. I know because we use our own technology to analyze sales activity. Gaining customers outside our target market hurts our initial deal sizes, expansion rates and ultimately annual recurring revenue. Recognizing enterprises in various industries are commencing their digital transformation journeys at different times in adopting the technology at different rates. It is important that we focus resources on the right entities at the right time. As we enter fiscal 2019, we take stock of all that we have learned in the past few quarters and we are making strategic changes to position us for greater success.
For example, customer size as in the case of the Global 8000 is only one factor in determining our most attractive customers. Our ideal target customer is defined by many attributes including propensity to buy, propensity to expand, industry vertical, use case, number of data scientists, IT spend, legacy data spend and so on. As a result using our technology we have refined our near-term target market to a subset of the Global 8000, which allows us to optimize our go to market efforts for the greatest return. This will enable us to grow faster and generate cash sooner. In addition to improved customer segmentation, we have implemented a number of go to market and field organizational changes to support our new customer acquisition goals and our existing customer expansion objectives. These refinements are excellent examples of how insight gains in data can make an organization more effective. Constant refinement of focus on the high quality customers fuels our land and expand model as evidenced by our 136% net expansion rate.
I would now like to shift to important corporate changes we are also making to align our organization and priorities with the three market trends that Mike described disrupting the legacy analytics market, leading the machine learning revolution and capitalizing on public cloud adoption. To drive these initiatives and assure focus, we have added three general managers in the number of targeted resources for each of these areas. Our GMs report to the newly appointed Senior Vice President, who oversee these high growth businesses. In addition to work on the product, we are making field investments in analytic database skills, adding specialists in machine learning and introducing dedicated cloud computing experts. Furthermore, as part of the field reorganization and new go to market initiatives, we have commenced a formal search for a new global sales leader to drive these changes in segmentation and specialization.
As we plan for fiscal 2019 and beyond we have recognized that we are at the cusp of the data age, a technological revolution disrupting multiple sectors and creating a large market opportunity. At this early stage in the markets development, we are focused on extending our position as one of its biggest and most enduring players. You should expect us to be an exemplary data-driven business by continually refining our strategy based on data. We have the category leads. We have differentiated technology and we have widening competitive modes, especially in machine learning analytics in the cloud. We believe that Cloudera is well-positioned to continue to grow that the changes we have undertaken have strengthened our prospects.
Now, I would like to have Jim provide a detailed financial update and then I will conclude with a few remarks. Jim?
Hello, everyone. As Tom indicated, we had both a solid fiscal Q4 and 2018 growing nicely and exhibiting strong investment discipline and expense management in our steady climb toward operating cash flow breakeven. Subscription software revenue for Q4 was $84.3 million, an increase of 50% year-over-year. In total, revenue was $103.5 million for the fourth quarter, representing 42% growth over last year. Subscription software revenue equals 81% of revenue, up from 77% in Q4 of last year. International revenue grew 66% from Q4 ‘17 to Q4 ‘18. For Q4, our net expansion rate was 136%. Recall that net expansion rate factors retention expansion and churn on a dollar basis average for the four prior quarters.
As Tom highlighted, we now have more than 60 customers with annual recurring software revenue in excess of $1 million, up from 50 in the prior quarter and 30 at the time of our IPO just four quarters ago. These customers collectively contribute half of our subscription software revenue. Subscription software revenue for fiscal 2018 was $301 million, an increase of 50% year-over-year. In total, revenue was $367 million for the fiscal year representing 41% growth over fiscal 2017. International revenue grew 62% year-over-year. Finally, we added 32 net new Global 8000 customers in Q4 and 132 in total for the year. As I review the remainder of the income statement, note that unless otherwise stated, all references to expenses and operating results are on a non-GAAP basis. Historical non-GAAP results are reconciled to GAAP results in the press release issued earlier today.
In Q4, subscription gross margin was 86% over 200 basis points higher than the year ago period. For the full year, subscription gross margin was 85% over 300 basis points higher than fiscal year ‘17. Services gross margin for the quarter was 24% versus 29% a year ago. For fiscal 2018, services gross margin was 17% versus 24% for fiscal ‘17. As compared to subscription revenue, services revenue and margins have a high degree of quarter-to-quarter variability due to the timing of project work and the nature of customer subscription agreements. Services revenue recognition is often deferred when services are sold at the same time as subscription software while services cost or expense as they are incurred. These timing differences sometimes lead to substantial revenue and margin variability. Total gross margin for Q4 was 75%, up more than 300 basis points compared to 71% a year ago. Cloudera’s continued gross margin expansion is due to subscription software revenue growing faster than services revenue as well as the increased efficiency of our technical support organization.
Turning to operating expenses, the most significant year-over-year improvement was in sales and marketing expense, which was $54 million for the fourth quarter or 52% of revenue. This compares to 74% of revenue in the year ago period. For the full year, sales and marketing expense was 56% of revenue and approximately 1,900 basis point reduction compared to fiscal ‘17. As Tom mentioned, we have been building deep understanding of what it takes to drive customer success and have been able to deliver the resources to support that success more cost effectively. Overall, operating loss is $70 million in Q4 representing a negative operating margin of 16%. This was an improvement of approximately 3,000 basis points compared to the year ago quarter when we had an operating loss of $33 million.
For the fiscal year, operating loss was $97 million representing a negative operating margin of 26% as compared to a negative operating margin of 54% for the prior fiscal year. Non-GAAP net loss per share was $0.10 in the fourth quarter based on 143 million weighted average shares outstanding compared to a net loss per share of $0.30 in the fourth quarter of fiscal ‘17. For fiscal ‘18 non-GAAP loss per share was $0.59 based on 133 million weighted average shares outstanding compared to a loss per share of $1.26 for fiscal ‘17. Please review the tables in today’s press release for additional information regarding historical and forward-looking stock based compensation expense and historical shares outstanding.
Now turning to the balance sheet and cash flow, we exited Q4 with $461 million in cash, cash equivalents, marketable securities and restricted cash which is down from $484 million at the end of Q3. Demonstrating continued improvement in operating efficiencies, operating cash flow for the fourth quarter was negative $22 million as compared to negative operating cash flow of $32 million in the year ago period. Capital expenditures were $4 million in the quarter. Operating cash flow for the fiscal year was negative $42 million or 12% of revenue. This is a substantial improvement over last year when operating cash flow was negative 45% of revenue. Capital expenditures were $13 million for all of fiscal ‘18. Total deferred revenue was $292 million at the end of the fourth quarter and short-term deferred revenue was $257 million, up – each up 34% year-over-year.
I will conclude by providing initial guidance for fiscal Q1 and for fiscal 2019. As we offer guidance, it is important to understand that we take into account to transition the leadership and our refined go-to-market strategy to ensure focus on those customers and prospects with the highest propensity to buy and consume our software. Although potentially producing uneven results in the short run we have initiated these changes to enhance the company’s posture for sustained long-term growth. We expect Q1 total revenue to be between $101 million and $102 million representing approximately 28% growth compared to Q1 of last year. With subscription software revenue in the range of $85 million to $86 million, up approximately 32% year-over-year. Non-GAAP net loss per share is projected to be $0.19 to $0.17 based on approximately 147 million weighted average shares outstanding.
For fiscal year 2019, we expect total revenue to be between $435 million and $445 million representing approximately 20% growth. We have subscription software revenue in the range of $370 million to $375 million, up approximately 24% year-over-year. We expect gross margin for the year to expand by 150 basis points driven by the same factors as in fiscal ‘18. Non-GAAP net loss per share is projected to be $0.62 to $0.59 based on approximately 152 million weighted average shares outstanding. We expect operating cash flow for the year to be negative $40 million to $35 million. Seasonally, we expect operating cash flow to be positive in the current quarter of fiscal Q1 ‘19 and approximately breakeven in Q4 with most of the year’s losses occurring in Q2 and Q3 of fiscal ‘19.
Consistent with the objectives we established at the time of the IPO, we expect operating cash flow to be positive in fiscal Q1 2020 and for the full year of fiscal 2020. Capital expenditures for fiscal ‘19 should be around $12 million driven by leasehold improvements occurring primarily in the first half of the year. Finally, we expect deferred revenue to grow at roughly 21% for the year with short-term deferred revenue growing at roughly 23%.
I will turn it back to Tom.
Thank you, Jim. Our guidance reflects all of the changes we have discussed including our refined go-to-market strategy and sales leadership transition and a realistic view of time required for these actions to take effect. Our conviction is high with respect to our business model and the macro forces driving our market. Data will continue to explode and use cases will grow. Machine learning and AI are reshaping every industry. The Internet of Things is wholly relying on data and the cloud makes data more accessible and easier to analyze benefiting our customers and our business. It is still early in the markets development. Most enterprises are just beginning their digital transformation journeys. In a rapidly evolving and disruptive market the investments we have made have us well positioned to lead them on that journey.
We are eager to get your questions. The team and I remain grateful to our customers, our employees, our developer community, our partners and of course to our investors, thank you all. Operator, can we please begin the Q&A portion of the call.
[Operator Instructions] Your first question comes from Sanjit Singh with Morgan Stanley. Your line is open.
Thank you for taking the questions and congrats on a nice fiscal year ‘18. So, I guess I wanted to dig into the fiscal year ‘19 guidance and specifically the assumptions in terms of the assumptions that we are used to talking about – when we talk about the bottle, so subscription revenue is essentially being cut in half and so what I would understand, Jim, is the net expansion rate that that’s likely takes the hit in the near term and then it also seems like current billings growth also was pretty strong in fiscal year ‘18. I am just trying to get understand what are some of the dynamics that would cause such a rapid slowdown in the subscription revenue growth line?
Yes, let me break that into two pieces. When we look at growth in a fiscal year, the vast majority of the software growth comes from the expansion piece. Several percentage points will come from new customers if we pickup from the year. So, most of that change is due to the expansion rate, what is factoring into that perspective is the transitions that we are making in the field. We do expect them to produce some uneven results in the first part of fiscal year ‘19 and that is reflected in the guidance.
Got it. And just in terms of like the timing of the changes, was there certain – when you looked at sort of your customer cohorts, was there a larger mix of the customer base that wasn’t expanding at the rate that you projected or was there any sort of other metrics that came out that is causing the sort of toggle in terms of the go-to-market approach?
Yes. The business is fundamentally helping. Our net expansion rate for Q4 was 136 and as we drill down into that, our oldest cohorts and the cohorts that represent our largest customers are still growing at roughly that 136%. So the land-and-expand model is really working. What we thought is in late Q4 some softness in expansion bookings as well as we look at the changes that we are putting into the first half of next year, we expect that to impact our bookings for the first half which will eventually reflect in billings and revenue for the year.
Got it. I will leave it there. Thank you very much guys.
Your next question comes from Mark Murphy with JPMorgan. Your line is open.
Yes, thank you. So, Jim as you pointed out, the net expansion rate remains very healthy at 136% and then as we look to the revenue guidance for fiscal ‘19 it’s well below that level, closer to 20%? And that is what I am trying to reconcile. I am curious do you think that the expansion rate is going to end up substantially lower by the time we are at the end of fiscal ‘19 for instance do you think it would be sub 120%, because I actually would not think that changes in the go-to-market strategy would have a material effect on the net expansion rate? That just seems to be more the natural cadence or the natural trajectory that your larger customers are on and have been on for quite some time. I could see – I would think that, that could have some effect on new bookings, but that doesn’t seem to be the primary driver of your total revenue growth rate, so that’s the main kind of discrepancy in the guidance that I am trying to reconcile?
Yes. So, there is couple of different pieces if I don’t cover all of them pull me back. So, our revenue guidance for the year is up roughly about 20%. The software revenue guidance is up about 24% year-over-year and the way you can bifurcate that is when we have looked at our net expansion rate over the past 4 years now, it has ranged between 120% and 150%. We have traditionally built our longer term models at the lower end of the range. And as we are looking forward into fiscal year ‘19 looking at the changes we are making in the field we are modeling literally at that low end of that range, it’s very close to the 120 and then we are adding some degree of revenue associated with new customers, that’s where you get that 124%. Regarding our ability to sell into large accounts, we are looking at the behavior of our larger customers and are still internally working to drive that net expansion rate to 130, 135, 140 or more. So, we are optimistic on the long run of the market, but we want to be prudent and reflect the potential disruption associated with the field changes.
Okay. And as a follow-up, so I mean I guess to just say this a little more directly could that expansion rate end up you are assuming 100 – could that end up in 120%, 125% range in fiscal year ‘19, is that a reasonable assumption for us?
The answer is yes. So clearly, we are just starting off the fiscal year. Our operating results that we chalk up over obviously in Q1, Q2, Q3 and so forth will directly cause the expansion rate and the growth rate for the year to be whatever it’s going to be.
Okay. I wanted to ask as well Tom, you made a comment something to the effect of you expanded too much in terms of sales resources pursuing customers outside the Global 8000 and something along those lines and I am just wondering if you can shed more light on what it was that you experienced and maybe when did that become apparent and how did it manifest?
Yes. Mark, I will provide a little more color and I will use our Q4 results to be more specific on that. As you know we are a land and expand. Our lands are in investment, our opportunities in expand. And what we want to do is we want to land the right customers that will show the best expansion attributes for our model to work. The way we have been organized each of our salespersons had a mix territory of new and existing customers and therefore they are always challenged where to spend their time going for new versus expansions. So if you look at Q4 we did well in landing. We are very pleased with the G8K customers we landed. It exceeded our annual target. But what we noticed was our reps didn’t spend enough time on their expansion opportunities focused on the land which is the investment for the long-term. And then I will go one step further which we don’t disclose, we would like to talk about our best customer is G8K, but opportunistically we always have other customers outside that market. And frankly in Q4 we pursued too many of those new customers outside that target market. And I think these new customers aren’t going to reflect those expansion opportunities. So what we are doing going forward is some of the changes and we talked about re-segmentation. I will take a moment to share with you what we are doing. Within that Global 8000 which is defined by revenue size customer revenue size or their total revenues we are even further segmenting to who are the best of that Global 8000. And we are going to be much more disciplined in selling just to them and not rewarding sellers who are being outside of market. Second, we are introducing two new roles. We are introducing a new logo hunter. These individuals are solely rewarded on pursuing new customers in our target market and we are very disciplined. These guys should increase the quality of our customers, improve our acquisition costs and increase our competitive win rates. We are also introducing new dedicated expansion reps, who are solely working with our largest customers that would drive expansions. And then finally around our focus on these high growth areas we are introducing new specialists in the field of our machine learning, analytics and cloud specialists. Hopefully it gives you a little more color on that dynamic when I mentioned new customers kind of outside our target market we have probably expanded too much effort landing some new customers that probably don’t fit our long-term profile.
Your next question comes from the line of Kash Rangan with Bank of America/Merrill Lynch. Your line is open.
Thank you very much for all the details Tom as well as the management team. How long do you think it would take to find a replacement for your head of worldwide field operations if I got that right and what is the certainty that the incoming head of sales is not going to make further transitions or tweaks granted that you might have identified what seems to be a more focused go to market strategy, just curious if they are going to be additional just along a little bit before you finally settle them on what the right approach is and that’s the only question for me? Thank you so much.
Kash, so I have – I would like to say my job is to take my time hiring really fast. We have open search, it is well underway. Our focus is to bring the right leader to take us to the next stage of our company. Our last leader did a tremendous job taking us roughly to $100 million to $350 million plus company expanding internationally, building out our platforms and now we look up to the leader take us to $1 billion and beyond. This is part of a broader transition that we have planned. We are in our third phase of Cloudera. If you were with Cloudera, when we are a private company we were selling into IT in Phase 2 which we are just kind of transitioning out of. We have focused on a platform that we effectively sold to CIOs. In Phase 3, we are helping our customers exploit that platform into machine learning and analytic applications. And so now we are broadening to selling to line of business executives as we work our way towards the true digital transformation of selling to CEOs and C-suites. So, our new leader is going to focus on this transition not only just in the segmentation, but extending our message to line of business beyond the CIO and to the digital transformation. It’s my number one priority. I am very pleased with the candidates. Cloudera has the tremendous brand and people recognized the unique position we are in to lead this digital transformation. So, I don’t want to set expectations when we will finalize it, but it’s a top priority.
Tom, my very best wishes for finding the best candidate for the job, because we understand that maybe Cloudera is the story that’s got great products, good management team at this point, it’s all about the selling as we all understand scaling these businesses often requires the right kind of leader that’s a good fit, so best wishes on adding this?
Kash thank you.
Your next question comes from the line of Walter Pritchard with Citi. Your line is open.
Hi, thanks. Actually just a follow-up on Kash’s questionnaire, so from a rep turnover and management layers turnover, what did you experience I guess so far since the end of Q4 and what are you expecting in terms of that sort of disruption in personnel during this transition that they haven’t worked out?
So with every – so first off, we are not seeing any unexpected attrition or spikes in attrition, as you always start a new year when you go from your Q4 to Q1 that’s when you have the most attrition in a salesforce and that’s not unique to us, it’s how the industry works. We haven’t had any spikes in that or anything that raises concerns. We have – despite we are going through a leadership transition we have very strong sales leaders in each of our theaters and our operations team and we are executing extremely well through the transition that everyone is very focused on our Q1 and beyond.
And then just maybe a question to follow-up on what Mark was asking you about with expansion rate, so you mentioned there are three components to that and one of those is churn, do you expect in the Altus that you are focusing on the subset of what you are focusing on before from a customer perspective, do you expect that churn is more of a headwind in fiscal ‘19 and that’s something that as you get to expansion rates on a net basis is impacting the metric?
Yes, Walter, so just little more color. We do believe that Global 8000 remains our target market and enterprise of all sizes will benefit from our platforms. What we are trying to do is prioritize by industry in use cases and regulatory use cases timing of who is adopting now the fastest. And we are being more disciplined on understanding the use cases in those customers by focusing on the right customers with the right use cases early on we reduced churn in that first year. A lot of these non-target customers is where we experienced a lot of our churn. So we just want to churn them out quite frankly and focus in on the right customers and so that’s some of the discipline that we will be putting in place going forward.
So but as it relates to the metrics it sounds like Global 8000 number that you give we shouldn’t expect – we should expect some pressure on that metrics, it sounds like even if it doesn’t necessarily impact revenue meaningfully because of smaller customers that metric should see some pressure with that churn?
No, Walter, we should see – so first off, our goal of landing new customers every quarter in quantity should remain consistent and same as we have in the past, if we land that roughly 30ish new customers every quarter, it feeds our model perfectly. What we are doing is we are making sure those 30 are at even higher quality and therefore will have less churn and will hopefully drive better expansions.
Okay. Thank you.
Your next question comes from the line of Karl Keirstead with Deutsche Bank. Your line is open.
Thank you very much. Maybe one for Tom and one for Jim, so Tom I think one question that some on the line might have is what is this actually isn’t the sales issue, what if this isn’t about a lack of focus but your end market demand deteriorated, so I am wondering if you could address that are there emergence of any new rivals or old Cloudera use cases becoming less relevant, maybe you could just talk about maybe the end market shifts that prompted this beyond your own sales focus. And then maybe for Jim, maybe one of the things I don’t quite understand is on your guidance you are assuming that subscription revenue growth goes from 50% in fiscal ‘18 to 24% in fiscal ‘19, but the DR growth, the deceleration is much less severe where it’s 34% growth in fiscal ‘18 to 23% in fiscal ‘19, so why would the DR only come down slightly, but we would get a significant decel [ph] on the subscription revenue growth? Thank you very much.
I am glad you didn’t address latter question to me. So Karl thanks for the question about the broad market. The reason in our prepared remarks we focused so much on the opportunity ahead, we fundamentally believe that this market is happening and every enterprise is going through the digital transformation at some point in the future. Here is our proof point, in our focus on executing against it. By introducing these new general managers into the growth areas of analytics that is the re-platforming of legacy technologies like data warehouses, that is happening. Data lakes has now become project of every IT shop in a large enterprise and we are well-positioned to do that. Machine learning, as evidenced by our rapid adoption of Cloudera Data Science workbench while we are not disclosing the actual numbers for that product, it is the fastest growing product that we have ever introduced. In the appetite for machine learning and artificial intelligence and large enterprises is very large, but the challenge here is it’s very early. They are trying to learn what it means, they are trying to understand what their options are, they are trying to understand what are these open source algorithms, how they bridge between IT and data scientists who happen to be in the line of business. And so when we talk about our strategy in machine learning, we want to lead that industry. We are in a unique position not only with technology, but with thought leadership. The acquisition of Fast Forward Labs in our Cloudera Fast Forward Labs gives us the preeminent applied research team on the planet to help our customers there. So that is the growth area. And then finally, the cloud is turning out to be a tremendous tailwind for us. While it introduces new competitors each of the cloud guys has their own house offering, we have figured out how to win in that market and stay focus on large enterprises, value our enterprise features around security governance you can’t find in the public cloud house offerings who value our hybrid approach, our multi-cloud and more importantly our multi-function integrated capability where I would like to say the customers all the time is we are better than Amazon and Amazon. Our products on Amazon are integrated better and operated better than Amazon’s own offerings. So what we are seeing the move to the cloud takes shape unlike it did 2 years ago. So I see nothing that gives me concern about the market. I do think we need there is high expectation for us to be a high growth company. And for us we just have to be very facile on how we attack that market. No changes in this competitive landscape or end market demand.
Got it. Thank you, Tom.
So I get the easy question. So Karl, what I will say is the model works where clearly we book a deal then we bill it, which generates deferred revenue, then we have recognized revenue. So there is timing lag. In the long run all the metrics should match it themselves, so bookings growth should match billings growth, matches revenue growth, matches deferred revenue growth. In any given period you have the lags and that may impact that. So very specifically for the year just ended our software revenue growth was 50%. Our revenue growth was 41% and clearly deferred revenue is correlated with revenue growth, so the gap in the current year 41% and 34% is a bit less and then heading into next year, the total revenue growth is 20%, deferred revenue of 23%. There you see the fact of quite frankly us building in the uneven bookings that we see in the first half of the year into the model. What I will say is if you can – if you want to take the time to see this into your model and then we can address maybe in the callbacks, I think when do you put the assumptions in, it may make a little bit more sense.
Okay, got it. Thank you, Jim.
Your next question comes from the line of Michael Turits with Raymond James. Your line is open.
Hi, guys. It’s a pretty steep decline in the cash flow guide by about $24 million relative to consensus obviously didn’t guide to it for this year. If I were to calculate at the billings implied, it seems like billings is about $50 million less than consensus, I know you didn’t guide it instructions, but it kind of implies that you will have to make some cuts to keep it all from coming to the bottom line. So, how do you manage that and then how do you pivot if you will from kind of casual lawsuit to coming back to being back on plan seemingly for cash flow in 2020?
Yes, so let me restart out with that from a financial mechanical standpoint. To put things in perspective, we started out with $117 million of cash burn in fiscal year ‘17. We had a path to get to cash flow positive in fiscal year 2020 and there were number of levers that we had at our disposal. Some of that was leveraging past investments. Part of that is understanding the nature of our current investments both in R&D and sales and marketing. So what has happened over the past year is we are still very confident that we are going to get to our positive cash flow in fiscal year 2020 yet billings for the fiscal year ‘19 are somewhat less than what we had penciled in a year ago. On the other hand, we have a better grasp of certain of our spending, especially the spending associated with expanding customers. So, we put all those pieces together and still are confident to get to that cash flow positive in 2020. And what you see in fiscal year ‘19 is the $35 million to $40 million cash burn guidance allows us to continue to invest in the field and invest in the initiatives that we have discussed in terms of machine learning analytics and cloud. So, we think that we have everything well-balanced.
I guess as one follow-up question would just be, Tom, in your estimate weighing all of these changes that are taking place, when do you think essentially that you will be through the changes and we should start to see things ramp and we start to get more productive in the sales force and reacceleration of growth?
Yes. As you know, as we have planned our guidance, we want to be prudent with respect to that question. Some of these changes are underway are ready, some of them we still have to implement, but I think we will in the second half start benefiting from these changes in the field, but like we are just hiring up a bunch of our specialists and training specialists the new leader will come on hopefully not too far out. So, the stuff I think we will see the benefits for the second half. And these are the right changes both to address some of the challenges that we saw, but also the broader transition as we start focusing in on Phase 3 of our company and getting us to the line of business users with these unique powerful applications.
Thank you, Michael.
Your next question comes from the line of Greg McDowell with JMP Securities. Your line is open.
Great, thank you very much. Jim, one quick question for you and I am sure we will discuss this more next week at the Analyst Day, but I wanted to hear a little bit about the puts and takes of the long-term model and with the changes we have discussed in the last hour, how we should maybe think differently about the long-term model and if the timeframe for the long-term model is effectively the same as it was at the time of IPO and I think you alluded to turning cash flow positive in FY ‘20. So, that sounds consistent, but I was wondering if we can talk about maybe some of the puts and takes with other components of the long-term modeling in light of the changes? Thanks.
Yes, Greg for sure. And what I will do is I will just cover it at a very high level right now, because we will be spending a lot more time on this at our Analyst Day. So, in the past year, as Tom alluded to we have been using our own data to better understand the selling behavior of our sales reps or cost of selling. The path of our customers through various stages of their journey through acquisition, through just getting that first use case, second use case, where I’d say we are doing really, really well is on the expansion side is that we are still very effective quite frankly even more effective than we had expected in terms of our ability to invest sales resources and drive expansion even in customers that have been with us for 4, 5, 6 years or at $0.5 million to $1 million or more. On the other hand, we have found that our cost to acquire customers quite frankly was even higher than we thought it was last year. And that understanding of how different the sales motion is for expanding customers and acquiring customers is one of the factors that led us to this change in the field where we really wanted to make sure that we were optimizing each of these sales motions, the expansion one which we are doing really well, but obviously we can do even better and then the acquisition one which we need to make more substantial improvements. So to highlight that’s the new news in the model over the past year.
That’s helpful. Thank you.
Your next question comes from the line of Jack Andrews with Needham. Your line is open.
Good afternoon. Thanks for taking my question. I was wondering if we could drill down a little bit more specifically around the topic of machine learning, I mean, it’s clearly a hot topic of discussion these days. So, I guess I mean as you or talking with your customers, I mean, how much I guess a pent-up demand is there really to harness this power and embed this technology into the business processes versus how much evangelizing do you need to do around machine learning use cases at this point?
Jack, it’s Mike Olson and I want to thank you for giving the wallflower. I will take the question and Tom may want to pile on. Machine learning, all the rage, loss of hype, plenty of excitement. In fact, we see in our large enterprise clients real and serious business value being driven by ML techniques applied to new business problems, but also all business problems using weighing more data than ever before, advising people on how to make decisions better and scoring risk in recommending treatments for patients and understanding which loans are worth giving in predicting which machines are going to fail and fixing them early. We have got real and repeatable customer use cases in all of those areas. The challenge is brand new technique, enterprises don’t understand how the algorithms work with which ones to choose and don’t know how to operationalize that apply those algorithms to their business problems. So, we have got a lot of technical capabilities. Thanks to Data Science Workbench. Our investment in Fast Forward Labs last year brings on deep expertise in the algorithms and also in applying them to real business problems. We are seeing plenty of interest in an uptake. Both of those offerings as Tom shared, Data Science Workbench is our fastest growing product in the company’s history and we are very excited about what that means. We have established as you have heard 3 GMs, one each for analytic database, traditional data warehouse disruption for cloud adoption and significantly for machine learning, we see that as a very big driver going forward.
Jack, just to pile on, the appetite for machine learning is significant, but the way you do it is not to talk about machine learning, talk about the end use cases that uniquely we can solve. Mike touched on every auto manufacturer is trying to make safe self driving vehicles or autonomous vehicles. Healthcare is focused on precision medicine. Telco need to do churn reduction. Financial services need to do any money laundering. They were trying to solve these problems, but the answer to all of them is through ML. So, our part of our pivot is to become experts in these use cases and lead our customers there as one of our differentiations and that’s why Fast Forward Labs was such an important acquisition for us.
I appreciate that commentary. Just as a quick follow-up, I was wondering if you could if its possible drilldown on the incremental on 10 plus customers that are now – have reached the $1 million revenue per year in the subscription side of things. Are you seeing any different characteristics or trends among these latest groups that have reached that milestone than you have historically and is that impacted the way you are thinking about customer segmentation moving forward?
Yes, Jack. So, one of the projects that we have underway is we look at the journey of any customer from the time they come on board and how they move through five phases of the journey. And what we look at is what actions does a customer do in each of these phases as they grow to that $1 million and beyond and what actions can we take to move them through those phases effectively from one to the next. So, I don’t have all-in analysis, but we have clear understanding of what moves a customer from sub $1 million to that $1 million and what are the patterns. We know exactly how many customers we have in the next class to graduate and were taken actions to move that class forward. And we are doing this through each kind of stage of our customer journey. As a matter of fact one of the things that we just did our recent SKO was to train our sales force on the customer journey and not so much on what’s the initial transaction but how we manage the customer from typically less than $100,000 starting point to get them above that $1 million and beyond.
Right. Well, thank you for taking my questions.
Thank you, Jack.
Your next question comes from the line of Rishi Jaluria with D.A. Davidson. Your line is open.
Hi, thanks guys for taking my questions. Just want to kind of go back to some of the changes in sales strategies and go-to-market strategies and take a step back, I mean, how should we gauge the success of these changes, is it something that should payoff first in the higher ASPs, higher net expansion rates, accelerating revenue growth, combination of all of the above? Then I have one follow-up.
Yes, Rishi, this is Tom. So, the changes – let me take what the objective of the changes we are making. First off, to have reps dedicated to bring in the highest quality customers into our portfolio, if they do that, we should see higher initial ACVs, we should see better churn, improved churn and we should see faster expansions. That is our objective in doing that. By having our next class of reps dedicated to our largest customers with the greatest opportunity to expand that should also affect our expansion rate. We know that we are one of the preeminent land-and-expand opportunities because of this expansion rate that we have yet to see the lifetime value of a customer. So, we are really honing in on just optimizing around his land-and-expand. So, I think what you will see hopefully is better retention, better expansions with this tighter focus. And initially also by having reps dedicated to just competing for new logos, we are going to – we think we can lower our customer acquisition costs.
Okay, got it. That’s helpful. And one more follow-up for you, Tom, I mean, you have mentioned that there might be within that G8K segment specific verticals that are more attractive than others at least some of those near-term in terms of propensity to consume? Can you give us a sense for maybe what industries you consider to be the most attractive for Cloudera right now? That’s it. Thanks.
Yes. So, well, one I would tell you looking back we have always done very well in financial services and we continue to expect high growth out of financial services. In large part that business has been driven by the regulators, but now financial services companies are really seeing fin-tech competitors and so they are really trying to do the digital experience. We, the technology industry, continues to be very strong for us. Every technology manufacturer with our hardware software is instrumenting their software. And telecom has been very good. What we are now seeing new emerging verticals, the automotive manufacturing industry is very, very active and we are all over that vertical, healthcare, because of all the cost pressures and penalties for like return patients in chronic diseases is very, very active. And so this is how we kind of go through and look at priorities. We – companies that are susceptible to GDPR is a focus for us. So, GDPR is a great driver for our platform and at some point we are going to why, but – so we identify these kind of catalysts or industry trends to understand the urgency.
Thank you, Rishi.
Your next question comes from the line of Abhey Lamba with Mizuho Securities. Your line is open.
Yes, thank you. Tom, I am trying to reconcile your commentary to Karl’s question with what happened in Q4 in your guidance, lastly, you laid out all the positive drivers, the secular tailwinds helping your end-markets, but at the same time, clearly there are pockets where the market is not performing as you expected maybe 6 months ago or so? So, what is happening in the markets that have underperformed versus your expectations, the companies where expansion activity was lighter, what happened, why did that happened and is the market narrower than what you thought 6 months ago?
Abhey, I want to give – I want to answer your question directly and using Q4. And this is really where I think we made mistakes where we directed our sales resources. So, in Q4 to peel back, we fell short of our overall booking goals. However, if you now peel that, we were satisfied with our new customer acquisition within expansion number, where we fell short. And expansion is the larger part of our business, because new customers start small, our expansion deals are more sizable. So, we were just over rotated and I can even be more specific that was really in our Americas theater. So, these are things that we can correct and impact now that bookings miss in a subscription business is what rolls over into our guidance for the Q1, Q2 here and so forth. Hope that Abhey that gives you a little more transparency into what happened and how that affects our guidance.
Yes, that helps. Thank you.
Alright. Operator, I think this is the time we need to wrap up. We went over a little over, but we knew that you guys would have good questions for us. So, I do want to thank you all for your time today and your questions. Thanks for being on this journey. We are in the early stages of this market and enterprises are just embarking on the digital transformation. We touch on a number of those drivers. Cloudera is super well-positioned. We have many competitive advantages. We have increasing technical moats, especially in machine learning analytics and the cloud. These are the high-growth areas of our business and I think we are well invested to capture this market. So, thank you for your time today and we look forward to talking to you in the future.
This concludes today’s conference call. You may now disconnect.