© 2024 Alpha Spread Limited. All Rights Reserved.
www.alphaspread.com is not operated by a broker, a dealer, or a registered investment adviser. Under no circumstances does any information posted on www.alphaspread.com represent a recommendation to buy or sell a security. The information on this site, and in its related newsletters, is not intended to be, nor does it constitute, investment advice or recommendations. The information on this site is in no way guaranteed for completeness, accuracy or in any other way. In no event shall Alpha Spread Limited be liable to any member, guest or third party for any damages of any kind arising out of the use of any content or other material published or available on www.alphaspread.com, or relating to the use of, or inability to use, www.alphaspread.com or any content, including, without limitation, any investment losses, lost profits, lost opportunity, special, incidental, indirect, consequential or punitive damages. Past performance is a poor indicator of future performance.
You don't have any saved screeners yet
Intrinsic Value is all-important and is the only logical way to evaluate the relative attractiveness of investments and businesses.
Greetings, and welcome to the Alteryx First Quarter 2018 Earnings Conference Call. At this time, all participants are in a listen-only mode. A question-and-answer session will follow the formal presentation. [Operator Instructions] As a reminder, this conference is being recorded.
I would now like to turn the conference over to your host, Chris Lal, thank you, you may begin.
Thank you, operator. Good afternoon and thank you for joining us today to review Alteryx’s first quarter 2018 financial results. With me on the call today are Dean Stoecker, Chairman and Chief Executive Officer; and Kevin Rubin, Chief Financial Officer.
After prepared remarks, we will open up the call to a question-and-answer session. During this call, we may make statements related to our business that are forward-looking statements under Federal Securities Laws. These statements are not guarantees of future performance but rather, are subject to a variety of risks and uncertainty.
Our actual results could differ materially from expectations reflected in any forward-looking statement. For a discussion of the material risks and other important factors that could affect our actual result, please refer to our SEC filings available on the SEC’s website and our website as well as the risks and other important factors discussed in today’s earnings release.
Additionally, non-GAAP financial measures will be discussed on this conference call. Please refer to the tables in our earnings release in the Investor Relations portion of our website for a reconciliation of these measures to their most directly comparable GAAP financial measure.
With that, I’d like to turn the call over to our Chief Executive Officer, Dean Stoecker. Dean?
Thanks, Chris, and welcome, everyone, to our Q1 2018 earnings call. This was another very strong quarter for Alteryx. For the first quarter, we reported revenue of $42.8 million, an increase of 50% year-over-year, and a non-GAAP operating loss of $1.3 million. Q1 marked our one-year anniversary as a public company, and I could not be more proud of our teams in what we’ve accomplished. Since our IPO in Q1 of last year, our trailing 12-month revenue increased 52%. We have grown our headcount by more than 150 people to 629 employees worldwide. We’ve expanded our customer base by more than 1,100, while also maintaining industry-leading net revenue retention rate.
We’ve also seen higher gross margins and a shorter customer acquisition payback period. We’ve extended the functionality, improved the usability and expanded our platform. Including the introduction of Alteryx Connect and Alteryx Promote, delivering an end-to-end platform to ensure Alteryx is the heartbeat of analytic enterprises around the globe. This has been a tremendous first year our life as a public company, and I’m even more excited for what has to come.
Our modern end-to-end platform is altering nearly everything for our enterprise customers, how they work with disparate data, how they prosecute the entire continuum of analytic processes, the functional use cases finally able to be addressed with an agile end-to-end platform and yes, altering their business outcomes in significant ways. The Alteryx platform provides the analytic flexibility that the 30 million business analysts and citizen data scientists, trained statisticians and IT professionals need, to create an operationalized analytic models through a collaborative, scalable and governed platform.
Every day, the worker, regardless of technical skill, once they be able easy to find and understand the information assets at their disposal, have the flexibility to prep, blend and, most importantly, analyze more data from more sources, and easily operationalize analytic workflows and predictive models in a self-service manner. We believe Alteryx can become synonymous with analytics by helping enterprises alter their view and understanding of analytics across the enterprise.
One of our key strategic imperatives entering 2018 was to build the business for meaningful growth and scale, and to do so through continued innovation that furthers both the sophistication and ease-of-use of our platform, and addresses an even broader set of use cases. We made great progress on this initiative with the general availability of Alteryx Promote, an add-on to Alteryx Server. Promote is our advanced analytics model management product for deploying, managing and monitoring statistical, predictive and machine learning models.
Promote simplifies last-mile of analytics by allowing models to be deployed and scaled in minutes, not months. For example, in Q1, a current customer strategic funding expanded their footprint with Alteryx by adding Promote to their server implementation. They have been an Alteryx customer for almost three years, primarily running predictive models in R and Python through Alteryx Server to qualify hundreds of incoming applications on a daily basis and produce real-time scoring for pricing.
The risk management group also needed to perform overnight predictive analytics under existing clientele of over 5,000 businesses to monitor credit health and support active loans. But their sophisticated modeling and pricing workflows needed to run for each of their thousands of clients simultaneously, so they require a more scalable solution. This was an ideal use case for Alteryx Promote, which they tested with a baseline requirements of running 5,000 predictive workflows in a few hours.
Promote significantly outperformed these expectations, successfully executing over 25,000 predictive models in just 10 minutes. Promote is enabling them to grow their analytic infrastructure with version insight and control and streamline of processing for immediate predictive model deployment without any recoding required. What Promote brings to strategic funding isn’t just predictive model deployment and performance, they now have a platform to support their aggressive business growth objective.
With Promote, they’re drastically reducing amount of manual loan review time by automating data processing so that they can scale for the future and service more customers, while still ensuring client engagement and satisfaction, all without the concern of outgrowing their infrastructure. Our vision for an end-to-end data science and analytics platform has been getting attention from Gartner, who named Alteryx as the leader in the 2018 Magic Quadrant for Data Science and Machine Learning Platforms. As the only publicly traded company in the leader category, we believe we are well-positioned for enterprises in our digital transformation journey.
We also saw continued success with Alteryx Connect, which enables the difficult first-mile of analytics. Connect is our collaborative data exploration platform, where discovering straight information asset, documenting lineage and sharing these assets across the enterprise, all in a governed and secured environment. Demand for Alteryx Connect is coming from, not only our existing customer base, but also from new customers.
In Q1, we added a new customer who chose to land with Alteryx Connect, Raiffeisenbank, based in Bulgaria, provides banking products and services to corporations, retailers, and institutional clients in Eastern Europe with a network of nearly 200 branches. Raiffeisenbank selected Connect as the solution for their data cataloging and governance initiative in adherence to the regulatory requirements, risk management and enhanced reporting practices. Before Alteryx, they were limited to spreadsheets and document files to define their business glossary, which became extremely cumbersome to manage.
The bank needed a solution to aggregate, and standardize data and provide analysts with an on-demand access and search capabilities for curated information. Attracted to the user-friendly interface and overall flexibility of Connect, they now leverage it for defining terms in a centralized dictionary. They started cataloging their assets and reports, and they are now able to utilize the data lineage capabilities for comprehensive visibility of data inputs and outputs across their systems. Our customer expect significant business value by removing duplicative efforts in enabling their data analysts to quickly find the trustworthy data they need for regulatory reporting and performing advanced analytics for decision making processes.
Another key imperative is to leverage our innovation and expanded use cases to bring our addressable market even more within reach. Coupled with investments we’re making to expand our enterprise class sales organization on a global basis, we are driving our land and expand model more efficiently, while reaching a diverse and growing cohort of customers. Our success was also driven by the business analysts, citizen data scientists and trained statisticians, who use our platform every day, and who continue to expand their usage into more of the platforms advanced capabilities over time.
During the quarter, we added 281 net new customers, exiting Q1, close to 3,700 active customers, who represented nearly every industry segment and an ever expanding set of use cases. New customers included some well-known companies such as 3M, Intel, Merck, Waste Management and Under Armour. And as we’ve noted in the previous calls, with the tailwind of our IPO, the acute focus enterprises have on analytics and the emergence of CDO persona, we are beginning to see larger land.
For example, in Q1, the data analytics team in the investment banking group at Barclays Bank adopted Alteryx to support internal and external reporting across global operations. In today’s highly scrutinized regulatory environment, management at Barclays is committed to providing service performance and progress measures across the various business units and global entities. As a large and complex organization, reporting requirements have become much more of bespoke and it is mission-critical to articulate internal processes to regulators.
The team needed to create a new suite reporting with drilldown, self-service analytic capabilities for analysts at a business unit level. But organizing and leveraging data with any lien team has become an enormous challenge. Time-to-market for analytics and reporting is paramount, and their existing infrastructure and manual processes weren’t enabling the scalability and flexibility they needed. As a lean organization was cumbersome, it was a cumbersome process to allocate technical resources, assign project managers and engage business analysts and SMEs to execute task.
Team members were forced to do lots of modeling and data wrangling outside of their data warehouse, and it didn’t make much sense to write hefty customized stored procedures only to have to unpack later for ad hoc changes, or have individual team members drafting scripts and isolation using C#, Access databases or Excel macros. It was too much team independency, too much technical depth, and too much risk to manage. The team chose Alteryx as their solution, with Server providing the centralization, governance and control they needed.
With Alteryx, they’ve been able to streamline data management and analysts across the company are now able to work directly with standardize data and reporting outputs in real time. Building workflows in Alteryx gives them a visual, practically structured and controllable way for them to demonstrate internal processes and logic to stakeholders or regulators as needed. Analysts have embraced Alteryx works ease-of-use and gives them a platform to support the growth of their advanced analytic capabilities, where everything from machine learning and risk mitigation for revenue divisions executing trade.
In the first quarter, the expanse side of our go-to-market model also continued to perform well. Our dollar-based net revenue retention was 132%, again, fueled by an uptick in the percentage of customers expanding their use of our platform, as well as an uptick in the size of their expansion. We believe our expansion opportunities within an enterprise to remain strong over time. Let me illustrate with Quest Diagnostics. A clinical lab testing company, serving one in three adult Americans and half the physicians and hospital in the United States.
With Alteryx, Quest optimizes test order process and trafficking efficiencies that previously required weekends to perform manual data cleanup. Quest was able to identify instances where doctors that improve how the order tests, in which tests make sense at certain point in time, while also being cost-conscious, which has a direct positive impact on patient care. Quest also looked at other use cases, including monitoring, medical quality and business operations.
Prior to Alteryx, Quest relied on request to a backlog IT department where we are at sometimes take months to understand whether a request can be supported. However, with Alteryx’s self-service empowerment, when user request commented that, I can do things faster, better, actually I can do things that we’re never capable of doing before. When I use Alteryx, I feel powerful, I feel exhilarated, because it leads to insights that no one had before.
At Quest, the spread of Alteryx has been viral. We now have an internal user group and see new Alteryx users from corporate business units and regional labs from across the country representing multiple functions. We also took steps in Q1 to further extend our presence globally, making several key investments and announcements. We know the demand drivers for our platform internationally are strong and we are increasing our investment in select geographies to build the foundation for our growth throughout Europe and Asia.
We open our Asia Pacific headquarters in Singapore to expand our footprint and support the success of hundreds of current customers in the region longing for self-service data science and analytic platforms like ours. We also launched our Tokyo office and we’ll be begin the build out of a team to service the analytically savvy Japanese market.
Additionally, we acquired our distributor, Alteryx ANZ in Sydney, Australia, and are expanding team with additional sales, channel support and technical resources to address this growing market. In Europe, we opened our office in Paris and begun to build out of the team to drive business from France through Southern Europe. We also plan to extend our presence in Dubai, to better service the growing activity in the Middle East and Africa.
We believe these investments will enable us to capture a greater percentage of our total addressable market and we’re excited about our ability to grow and provide localized levels of support. To illustrate our global strength, several prominent companies landed or expanded with us in Q1, including ANA Holdings and KDDI Corporation in Japan, BNP Paribas and Temasek Holdings in Singapore, Cathay Pacific in Hong Kong, Campofrio Food Group in Spain, Consolidated Bank of Kenya, MMI Holdings in South Africa, Opticas Visión in Costa Rica, BLOM Bank in Lebanon, Banco Santander in Mexico and Abu Dhabi Islamic Bank in the UAE. In Q1, we did business in more than 70 countries, and international revenue accounted for 27% of total revenue, increasing 92% year-over-year.
Importantly, we also continue to advance our data and analytics culture here at Alteryx to drive better decision making across our organization, another one of our strategic imperatives. This is improving sales and marketing efficiency, a lower customer acquisition cost payback period and improvements in gross margins. We’ve successfully on-boarded more new employees in the first quarter than at any time in our history and continued to improve our customer experiences.
This was a great quarter and we believe the momentum in the business continues to build. The global excitement around the Alteryx platform will be highlighted in a wide variety of customer use case presentation at our annual Inspire Conference next month in Anaheim. This is sure to be a great event.
With that, for more color and commentary on our Q1 financials, let me turn the call over to Kevin Rubin, our CFO. Kevin?
Thank you, Dean. I am also very pleased to be speaking with you this afternoon. I will begin with our first quarter performance, followed by our second quarter and 2018 guidance. Revenue was $42.8 million, an increase of 50% year-over-year. International revenue was $11.4 million, an increase of 92%% year-over-year and 27% of our Q1 revenue. In the quarter, we added 281 net new customers compared to 237 net new customers in the prior-year period, and we ended the quarter with 3,673 active customers, an increase of 43% compared to the first quarter of 2017.
We delivered a strong Q1 dollar-based net revenue retention rate of 132%, our sixth consecutive quarter above 130%. Dollar-based net revenue retention can fluctuate depending on many things, such as mix of business and seasonality.
Before moving on, I would like to remind everyone, that unless otherwise stated, I will be discussing non-GAAP results. Non-GAAP measures including our guidance for the second quarter and full year 2018, excludes stock-based compensation, amortization of intangible assets, changes in fair value of contingent consideration and related income tax adjustments, offering costs related to our follow-on public offering and impairment of long-lived assets.
In addition, non-GAAP net loss per share, basic and diluted, excludes the accretion of Series A redeemable convertible preferred stock outstanding prior to our IPO, and non-GAAP weighted average shares used to compute non-GAAP net loss per share reflects the conversion of preferred stock into common stock as if such conversion had occurred on January 1 of 2017 and 2016 respectively.
In periods of non-GAAP net income, we adjust non-GAAP weighted average diluted shares outstanding to include the effect of diluted shares. A reconciliation of GAAP to non-GAAP financial measures has been provided in the financial statement tables included in the earnings release we issued earlier today.
Our gross margin was 90% in the first quarter, an improvement compared to 84% gross margin in the first quarter of 2017. One of our core imperatives is to drive better decision-making throughout the organization by leveraging our own data and capabilities to improve performance.
Our gross margin is benefiting from this effort as evident by our customer support and professional services costs, which have not increased proportionately with our increase in revenue, demonstrating the leverage in our model. We also incurred lower royalty costs on third-party syndicated data. We continue to believe that the general availability of both Alteryx Connect and Alteryx Promote will have some additional slightly higher cost of services due to the sophistication of these offerings.
Finally, as we continued to expand internationally, we expect to add local customer support personnel as well. Operating loss was $1.3 million, which equates to an operating margin of negative 3%. This is a significant improvement compared to an operating loss of $3.6 million or negative 13% margin in the first quarter of 2017.
We continue to focus on sales and marketing investments in Q1 2018 on programs to drive awareness and adoption and through the addition of quota-carrying sales people. As Dean mentioned, we also accelerated investments in Europe and Dean mentioned, we’ve also accelerated investments in Europe and Asia, and intend to continue to invest to drive international expansion. Net loss was $595,000, and net loss per share was $0.01. This is based on 60.1 million of weighted average shares outstanding, basic and diluted.
Turning now to our GAAP balance sheet. As of March 31, we had cash, cash equivalents, short-term and long-term investments of $205.7 million compared with $194.1 million as of December 31, 2017. We generated $12.1 million of positive cash flow from operations in the quarter. Finally, we ended the quarter with 629 employees, up from 469 employees at the end of the first quarter 2017.
Now let’s review our guidance, which we are raising for the full year of 2018. For the second quarter of 2018, we expect GAAP revenue in the range of $43 million to $44 million. We expect our non-GAAP operating loss to be in the range of $6 million to $7 million and non-GAAP net loss per share, basic and diluted, of $0.10 to $0.11. This assumes 61 million non-GAAP weighted average shares outstanding, basic and diluted.
As a reminder, we have our U.S. Inspire Conference in June, and our Q2 expenses are typically seasonally higher. For the full year of 2018, we now expect GAAP revenue in the range of $183 million to $186 million, representing year-over-year growth of approximately 39% to 41%. We now expect our non-GAAP operating loss to be in the range of $14 million to $70 million and non-GAAP net loss per share, basic and diluted, of $0.22 to $0.27. This assumes 61.5 million non-GAAP weighted average shares outstanding, basic and diluted.
Q1 was a strong start to the year for Alteryx. We’re executing well against our strategic imperatives. We continue to make investment to support our go-to-market initiatives and our platform, taking advantage of the many growth drivers for our business. Our strong revenue growth and raised revenue guidance, industry-leading dollar-based net revenue retention rate and improving CAC payback period all support these continued investment. We intend to manage the business with a reasonable, balance of growth and profitability and continue to expect to generate positive cash flow from operations again in 2018.
With that, we will open up the call for questions. Operator?
Thank you. At this time, we will be conducting a question-and-answer session. [Operator Instructions] Our first question is from Brent Bracelin from KeyBanc. Please go ahead.
Good afternoon, and thanks for taking the questions here. I have a couple here as I want to drill down into – maybe we’ll start with Kevin here in the Q1 results. 50% growth, clearly, much stronger than the midpoint of the guide at 38%. You talked about larger lands, larger expands, but could you just provide any more color on what drove the strength? What surprised you from a demand perspective in Q1 versus your guide?
Yes. Hey, good morning or good afternoon, Brent. Look, I think, we saw strong momentum in both sides of our business. You saw, with respect to the net new lands, we had a lot of momentum in terms of the land portion of the business, and on the expansion side, that continue to work well, 132% net revenue retention. So I don’t know that I would necessarily characterize it as surprised us, but we were encouraged to see strength in both aspects of the go-to-market.
Okay, fair enough. And then Dean, question for you on Promote. Obviously now, that its integrated with Designer, I think, since the March release, have you seen any sort of change and uptake of Promote? I know it’s really early days, but you did cite a couple examples of customers using Promote. I’d love to hear your early view on attach rates you’re seeing so far since that March release?
Well, it is early. We don’t have a whole lot of data on attach rates. We are comforted by the fact that there’s lots of activity around it. We’re getting good questions, good inbound activity on – particularly data scientists who have been struggling to advance their models in a deployable fashion. So it’s still early. I think that we’ll start to see pickup on attachment rates over the next few quarters, kind of like what we had suggested with the Connect part of the platform, where too early, maybe 6 to 8, 10 quarters before we really start to see the activity.
We are very encouraged though, particularly for the folks that rely on sort of real-time actioning around machine learning algorithms, using call centre activities, banking applications, website activity, much like you saw with strategic funding. And so we’re encouraged by the results and stay tuned for that because we built that last-mile of analytics for a purpose, only 13% of data scientists’ data models always get deployed. And we intended to make sure that data scientists and debt because of that.
Great. And last question for you, Dean, obviously, with the Tableau Prep product out now as a free component of the Crater bundling in included with the desktop products at Tableau. What’s your first blush view? I know you continue to be a sponsor of their user conferences, they sponsor your user conference, so walk us through your first blush view on the Tableau Prep as a free component of Crater?
Well, I think it does a couple things, Brent. First of all, it validates the space we created four years or five years ago. The second thing is, I think that it validates the fact that lightweight data prep is a feature in a product, not a critical component in a platform like ours. Just remember that our use cases tend to be very sophisticated, and they don’t rely on visualization very much. And when I say that, you think about hyper local merchandising to improve same-store sales, but the range of data sets that you would need to be able to access, the scale of those data sets. The output typically is not visualization. It tends to be other output that drives the decisioning at the store level.
We’re rationalizing CapEx has been for store development, complex gravity models being run, leveraging four, five, six different data sets. So I think they’ve done a good job for locking people into the Tableau experience, and the fact that you can write TDEs and spreadsheets. But our users, I think, as we’ve illustrated in many of the past calls, only 15% of the outbound traffic from Alteryx goes into any visualization product. And of the people who write to those visualization products, 50% of their work goes into something other than the visualization. So it’s early. We – our teams are still talking and doing deals together and working on bigger, more interesting accounts together. So I think they do the right things for themselves and validated our actions many years ago.
Very helpful color. I’ll leave the floor. Thank you.
Thank you.
Our next question is from Brad Sills from Bank of America Merrill Lynch. Please go ahead.
Hey guys, thanks for taking my question. I’m hearing very positive feedback on Connect, having that integrated as part of the Alteryx stack. I’m just curious if you thought about where that could go in terms of penetration? How pervasive do you think Connect could be in your installed base over time?
Well. Obviously, Nirvana would be to have all of our enterprise customers consuming the entire end-to-end experience. And while we started with Designer and Server in a code-free and code-friendly environment for the citizen data scientists and the trained statistician, what we’ve learned over the last four years, which led us to the acquisitions that culminated with Connect and Promote over the last few months, is that, that first mile of analytics are really challenging.
So our goal would be to take the 37% of time that analysts spend that looking for data, now that we’ve given them all their time back by empowering them with the capabilities of designer. We – I would hope that the larger number of designers would ultimately lead to Connect having a very strong attachment rate. And to Brent’s question, I think, that once people are finding the data assets they need for their analytic pipeline more easily, they’re going to get to more powerful analytics outcomes, like machine learning algorithms. That will drive the attachment rate for Promote. Probably time will tell. I think we’re early. I think we’re very optimistic about what we’re seeing in the market today with our customers who have embraced the entire platform. And so, it was a good timing for us to these acquisitions, and we’re seeing the results.
Graet, thanks, Dean. And then maybe if you could any commentary on Server. I know that’s just a function of expansion and they more of the published scenario across multiple users. But are you seeing that attachement of Server happening perhaps sooner in the expansion in the customer lifecycle?
Well, no, I think our percentages are still about the same, about half Designer and half Server in terms of revenue. I think that when a Chief Data Officer is in the mix or a proxy for a CDO is in the mix, we tend to see expansions happen larger and earlier. We don’t – we see some lands happening earlier, but it’s not a huge number at this point. That may change in the future based on what we’re seeing with CDOs coming into the mix and large enterprises more frequently.
But CDOs’ goal is to harness the networking affect of people, data and technologies. They’re all-in, they’re not going to limp their way to greatness by buying a few designers this month and a few you designers this month and a server the quarter after that. They typically end up expanding quicker, which, again, is reflective I think in our 122 net retention number.
Great. Thanks, Dean.
Our next question is from Michael Turits from Raymond James. Please go ahead.
Hi guys. You mentioned that you are doing better in terms of payback period, and it sounds like cost of acquisitions as well. Can you peel a little bit more detail about that? If you can quantify grade and tell us how you get there?
Well. I think there’s maybe a couple of points I’ll give, my perspective on what we’re seeing in the marketplace. Part of this is the market just opening up. You remember that we’re early on in this cycle. We’ve got a $30 billion TAM, $10 billion net new in line of business. Today, were sitting at that trailing 12-month number of $146 million, so this is really early on. We are seeing the tailwinds, however, the IPO. We – one of our imperatives this year was to get smarter as an organization to leverage our own technology to drive better in size for our own teams.
So I think that, that is having an impact on the business overall, not just in a cap payback period. We’re seeing it in gross margin improvement. We’re seeing it in almost every aspect of the business. So I think a lot of this has to do with the effect that the markets continuing to open up before recognizing that analytics is critical and I think that’s the result. Kevin may have some additional comments on the numbers.
Yes, Michael, I think Dean kind of hit the nail on the head. I mean I think we’ve continued to do a better job internally at executing in a lot of these different dimensions. And so specific to cat payback period, we have continued to be more efficient around our sales and marketing spend as it relates to revenue generations. So I think my commentary around guidance and how we think about it for the remainder of the year is just as we continue to see – continued efficiency, then we will continue to invest in go-to-market resources when these dynamics are as favorable as they are today.
Great. And then one follow-up, I think for Kevin. Just on the cash flow from operations was very strong this quarter, pretty much came in where we’ve been modeling for the full year. So I didn’t really drill down to the cash flow statements also did that and then one – is it just timing over the quarter and what lies in the character in the full year?
Yes. So I mean we don’t guide full year cash flow from operations other than I think my commentary was we expected to be positive. Q1 is typically a strong collection quarter coming off of a strong billing quarter in Q4. And the team did a good job collecting. So I think it’s more probably timing than anything else fundamental to any kind of change in the business. The team did a good job collecting, and we were managing cash flow pretty effectively through the quarter.
All right. Thanks, Kevin. Thanks, Dean.
Thank you.
Our next question is from Jack Andrews from Needham & Company. Please go ahead.
Good afternoon. Thanks for taking my question. I was wondering given your increased investments in the Asia-Pacific region in particular, could you just talk about the macro trends of things like self-service and the rise of CDOs? Is that – are those trends on par with what you’ve seen in North America? Or how do we think about that? Or is it maybe earlier stages in that particular region?
No, I think what we’re witnessing is the appetite for analytics across-the-board in most every country. We did business in 70 countries last quarter. We continued to – even though they are relatively small numbers, we have 90% growth year-over-year, International is now 27% of our total revenue base, up from 21% a year ago. And I think what we’re seeing, and whether it’s Asia-Pacific or Latin America or Southern Europe, Northern Europe, I spent last weekend the Middle East and it’s really no different.
People are trying to contend with this deluge of data that exist out there and its only 6% of analyst that all the data behind their firewall that’s just kind of the universal theme around the world to. And so I think it’s not necessarily theater-specific. I think as a general trend, the personas are almost the same, universally, across all theaters. I think in Latin America, many of the midmarket companies didn’t buy into the last generation of BI platforms and analytic platforms and IT. So there’s a little bit of generation-skipping buying that’s going on.
But it’s not – I wouldn’t say, that, that’s a universal staying. By the interest in analytics in the self-service fashion absolutely it’s a universal thing.
Great. Thanks for taking my question.
Sure, thank you.
Our next question is from Mark Murphy from JPMorgan. Please go ahead.
Yes. Thank you and congrats on the – also the metrics overall. Dean, I wanted to ask you, did you have any view of which of the incumbents might be most vulnerable or most exposed as you’re expanding your footprint into some of the newer areas with Connect and Promote. And also are you sensing any interesting developments in terms of replacing any of the legacy analytics tools?
Great question, Mark. We tend to go in at our land expand model as a net new add to anyone software portfolio. Sometimes, that’s a difficult bill for organizations to swallow because they’re trying to figure out how to get more capabilities and fewer tools but we tend to tell customers that they’ll figure out what they can and wind over some period of time. We have seen – with respect to Connect and Promote, I think that it’s still too early to really know what’s happening there. I mean, we could surmise but it’s probably not worth doing that here on this call.
I think that we’re probably more impactful to the analytic platforms, the people that you see in the Magic Quadrant for Data Science and Machine Learning. We have – I would say, probably even though we don’t have a religious compete today, we probably see SaaS more often than not, clearly, it is a smack dab and cross areas of the TAM . I’ve heard customers begin to unwind legacy BI platforms at the same time, rewriting all the things we would’ve typically done in legacy platform setting in IT. So I don’t think that there’s one universal path. I think that each company has their own challenges in unwinding what was in the IT division. It is all moving out of IT though into the line of business that we know for sure.
Okay, that makes sense. And just as a follow-up, can you help us with how big your ambitions are with the data science orientation of the platform overall? I guess, for instance, when we considered, you did have this positive increase in the R&D expenses in the quarter, any sense of how much of the R&D investment is shifting that way? And I was also wondering if you have thoughts on just how to make the whole category of machine learning more approachable and more usable for all types of rolls out there in the world, because it seems to be a puzzle that no one is really perfectly solved quite yet.
Well, the data science machine learning category is kind of a moving target today. There is a whole bunch of players that are even on the MQ that you have to scratch your head as to why they’re there, or why they can even possibly be a stand-alone enterprise. We’re seeing lots of activity in the space. We think that our first mile and last mile with Connect and Promote were critical to the journey ahead. I think that we’re seeing different kinds of movements across the spectrum regarding things like auto modeling and smart predictive capabilities, natural language processing and natural language generation.
There’s a whole bunch of kind of incentivized isolated technologies that could be interesting. We have a pretty good chessboard of things that we’ve looked at and contemplated building. I think that it’s still too early to make significant moves in some of those directions. Just know that we’re watching the space a very, very closely, because it is going to change.
Thank you.
Our next question from Bhavan Suri from William Blair. Please go ahead.
Hey, guys, nice job here. I guess, two questions, one initially, just on market sizing. One of the things you picked up is that there is sort of a TAM expansion here, so it’s not the replacement of [indiscernible] or something like that, or data prep pieces of packaging, but there’s new sets of analytical users here. And to one perspective, you’d be like well, but you guys think Tableau, but that’s not really where you play, sort of its not the little part or even sort of the dashboarding part. I guess, when you think about sort of who the new users would be the TAM expansion part of the deal. How would you describe or provide some use cases for that?
Well, it’s across the board, I think that you’re right. The TAM that we have described in the past is made up of two components: It’s the $10 billion sitting in the line of business in the hands of the 30 million disenfranchised analysts who hate their jobs, because they’re living in complex if you look up in Excel. Those people exist in almost every functional area. I think we are beginning to see not only a very horizontal nature to the platform, but within an organization as we begin to expand our footprint across those 30 million disenfranchised analysts. We’re seeing people pop up and departments that we never realized, in part because they don’t have analyst titles but they work with data day in and day out. In this past quarter, we saw lots of use cases around tax and audit and reconciliation. We’ve seen things around security and governance and ethics and compliance. So, I think your point is that, the net new user of technologies like ours is still revealing itself. We’re confident that with the plethora of tools that we have inside the platform and the ability to actually build new capabilities on the platform, not from our perspective, but a user being able to build their own capabilities, that we have a long runway to attack that audience. And we’ve long contended that the winner of that $10 billion net new disruptive innovation in the line of business will be the natural beneficiary of the $19 billionin share shift that will gradually occur from IT.
Yes, got you. That’s helpful. And then one quick one for me, on partners. Just you’ve obviously got a nice advantage channel there, sort of 60-plus SI and bars. Just what was the channel contribution in the quarter? I know your expectation for 2018? And then sort of as you look at the trajectory of consultants trained, not necessarily the pieces you guys are using at internally, but the guys who trade them into go to customers with it. How it is that trajectory looking that sort of a 50% growth rate year-over-year number of consultant 30, 20. Just some sense, and that would be helpful. Thank you.
Yes. Partners are directly responsible for about 20% of the revenue. There is a bit of influence revenue from partners who don’t share margin on a deal, but have influence, where they might be an SI or an analytics consultant, and they drop breadcrumbs in clients when they do engagements they love. They love be able to show their services work inside of Alteryx, because
it makes it easier for them to explain in a transparent fashion what’s been accomplished. I can’t really talk about these numbers of partner SEs that are enabled. We do have a certification programs in place, in fact, one of key imperative this year was activating our ecosystem. Part of that was enabling our new partners more rapidly, again, because of the global opportunity that exists out there, we wanted to enable partners more readily get them certified sooner, each of them not just a land, sales motions, but to expand the sales motions, whether that will have a demonstrable impact on revenue contribution from resellers, I don’t know, I think we continue to see the activity from SIs and analytic consultants where they are showing our platform most everywhere they go.
Okay, thanks for the color guys [indiscernible] congrats again.
Thanks, Bhavan.
Thanks.
Our next question is from Jesse Hulsing from Goldman Sachs. Please go ahead.
Thanks for taking the question. Gross margins were up pretty significantly for the quarter. I know you discussed the benefit from services and lower third-party royalties, but I’m wondering if there’s anything else you can call out here? And how should we think about the sustainability of gross margins in the high 80s and low 90s for the year?
Yes, thanks. So I think, as I mentioned, there were a couple of dynamics. First one being, and I think we mentioned it in a previous question. We just have done a better job, I think, internally executing. And so we haven’t seen the underlying fixed cost associated with customer support and service delivery, have to increase at the same rate that we’ve seen or benefited from a revenue perspective. Some of that is going through case reflection to our community site, et cetera.
So I think from a – just from an over overall execution perspective, we’re seeing benefits. We did incur lower royalty cost, as just a percentage of both revenue and a portion of our cost of revenue, which was great. And then – excuse me, as we think about it, going forward, look, I think we’ve also said as promote and connect become more widely deployed, we do expect those products, just the nature of them require a bit more service and support. So that’s probably going to weigh down on margins just a little bit, but it certainly won’t overtake the benefits that we’ve seen. We don’t guide forward on margins, but I think those are probably the dynamics that you should think about.
Okay, great. Thank you. And then on sales and marketing, it really ramped as a percent of revenue in the quarter. I know you just got this is one of the largest on boarding quarters in company history, but I’m wondering if you can touch on really where that incremental investment is going? And how we should think about the pace of investment for the rest of the year?
Yes. So, I mean, I specifically, I think, called out on our last earnings call that the timing of when we brought revenue-generating resources in late last year and early this year affected Q4 sales and marketing growth rates and now we’re seeing the full burden of those now. We certainly are emphasizing investment in that area, so revenue-generating, customer-facing resources, that’s helped us achieve the growth that we’ve reported thus far and continue this momentum going forward.
Great, thank you.
Thank you.
Our next question is from Derrick Wood from Cowen and Company. Please go ahead.
Great, thanks. You guys mentioned that you moved up the leader quadrant in the Gartner Data Science Magic Quadrant. Are you seeing that – I mean, maybe it’s early, but are you seeing that, that’s new market recognition that could help you drive more dialogue around data science? And then if you look at your pipeline, do you see any major shift between the projects you are working on data science versus analytics?
No, I think if you look at the range of MQs that Gartner has, we would like to – we were dealing with Maslow’s hierarchy of MQs. We’re at the highest order of outcomes for people who work with data. We’ve talked about our continuum of analytics and recognizing that descriptive analytics typically end up in dashboarding capabilities, but when you deploy machine learning algorithms, you’re actually at the higher order of analytic outcomes. And so that’s the place we wanted to be. I think that our customers really haven’t changed. I think, that they truly are, I believe, creating the citizen data scientists.
They start with some basic challenges with data, and they march up the continuum pretty rapidly from descriptive analytics and diagnostic analytics to more meaningful processes like spatial analytics, predictive modeling, machine learning, cognitive learning. And I think that, based on our ability to attract those citizen scientists into the mix, it incensed the trained statistician to leverage their skill set to help those people out. So with Promote, in particular, I don’t think that has to do with the MQ, I think, but Promote in particular, the scientists are excited now because just like we’ve got the analysts out of complex view lookups in Excel. We’re getting the scientists the ability to actually deploy algorithms in minutes instead of months.
Got it. Got it. And then I had a question on the net revenue retention. That’s – I would think, historically, it’s been driven by user expansion, now you’ve got new products to cross-sell, Promote, Connect. Do you think that’s going to have an impact on net retention rate? And any guidance or color on what you would think rates go to over the next several quarter.
No. We wouldn’t guide on what net retention numbers are going to be. I think we – at the IPO, we’d have 120 north for some sustainable period of time. I think the addition of Connect and Promote have the possibility of extending the net retentions for quite some period of time. So it’s still too early to tell on that. Our price points for Connect and Promote are relatively high reflecting the value of what you get out of those platform add-ons. So we would hope that with the rate kind of attachment rate, extending the net retention numbers is a plausible scenario.
Got it, okay.Thanks.
[Operator Instructions] Our next question is from Greg McDowell from JMP Securities. Please go ahead.
Thanks very much. Dean, I liked your Maslow’s hierarchy referenced earlier. My first question, just given Tableau’s radical change to their packaging and pricing and recognizing that visualization is only 15% of Alteryx outputs. I still wanted to ask about your view on pricing power in the marketplace, and whether or not there is a need to sort of rethink how you package core Alteryx? And then I have one follow-up.
Well, I think I would contend that everyone has a $4,000 problem, which is the price of the three-year seat of Alteryx Designer. We think our pricing is fair, particularly when you’re comparing it to a closer comparison, like SaaS. When you compare it to Excel pricing or Tableau pricing or any other point solution at the top of the stack, I think it’s in an unfair comparison.
So do we think our pricing is right? We do. We kind of proven that with our metrics. I think we calculated our TAM in the long haul, for the $30 million disenfranchised that $500 a feet, which is well below our average seat price on larger deployments. So I think our pricing is finally – if there were a bloody ocean in the space that we’ve played in, maybe there would be some reason to consider alternatives. But at this point, we don’t see a reason to do so.
Thanks. Since we’re getting to the end of the call, and we have your annual user conference coming up next month. I was wondering, Dean, if you can – maybe talk about seems of the conference that are similar to past conferences? And maybe some themes that you’re really going to try to get across to the user base this year compared to previous years? Thanks.
Well, I don’t want to let the cat out of the bag too early. I will tell you that’s going to be an unconventional convention. We are going to alter everything. You may never want to go to another conference again for that matter. But we have a lot of things in store. I think what’s most important about the conference that we have dozens of customers who are willing to stand up and describe the powerful outcomes that they’ve achieved with our platform, across the entire spectrum.
There will probably be people talking about the end-to-end experience, people are doing complex algorithmic processing, people who are getting promoted for their use of our platform and driving value for their business. It is a customer event. There are obviously some employees, including myself and Ashley Kramer, who’s our VP of Product Management, and a few others who will be giving presentations, but this is largely customers and the Alteryx community getting together. I guess, you’ll just have to be there.
I’ll be there.
This does conclude the question-and-answer session. I’d like to turn the floor back to management for any closing comments.
Thank you, operator. In closing, let me just say this. We’ve made significant progress on our key 2018 strategic imperatives and the continuation of our journey to make Alteryx synonymous with analytics across the enterprise. We’re building a business with continued strong revenue growth and a long-term sustainable profitability. Before closing today’s call, I’d like to thank all of our employees for the contribution to our success and all of our customers and partners for their continuous support. Thank you for joining us today and we look forward to speaking with you again very soon. Bye-bye.
This concludes today’s teleconference. You may disconnect your lines at this time. Thank you for your participation.