Alteryx Inc (AYX) 2017 Q2 法說會逐字稿

Greetings, and welcome to the Alteryx Second Quarter 2017 Conference Call. (Operator Instructions) As a reminder, this conference is being recorded.

It is now my pleasure to introduce your host, Chris Lal. Please go ahead.

Thank you, operator. Good afternoon, and thank you for joining us today to review Alteryx' Second Quarter 2017 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 risk and uncertainty. Our actual results could differ materially from expectations reflected in any forward-looking statements.

For a discussion of the material risks and other important factors that could affect our actual results, 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. We are very pleased with our second quarter financial results. We achieved strong revenue growth, improved bottom line performance and generated positive cash flow from operations. During the second quarter, we reported revenue of $30.3 million, representing an increase of 52% over the prior year period. Our non-GAAP operating loss was $5.5 million in the second quarter, leading to non-GAAP loss per share of $0.09.

In June, we held our Inspire Conference in Las Vegas, which attracted a record number 1,700 attendees from around the globe. The 3-day event, themed the "Icons of Analytics," showcased successful partners, innovative use cases and our tremendous customers. Inspire is an energizing event and reinforces that we are on the right track extending the functionality of our platform for the self-service data analytics market, delivering value to our customers, strengthening the Alteryx community and meeting the untapped needs of citizen data scientists wanting to escape the drudgery of the spreadsheets and trained data scientists focused on high-value analytic outcomes.

At Inspire, we further detailed what we believe is driving our market opportunity and how we are effectively capturing share. This includes continued platform innovation, the launch of Alteryx Connect and our Yhat acquisition.

Let me elaborate on each of these areas. We continue to enhance the end-to-end Alteryx analytics platform for the enterprise that allows users to solve the impossible. And as illustrated by our new corporate messaging, our platform is built so business analysts can experience the thrill of solving nearly any analytics problem. This is further demonstrated by the more than 160 vertical and functional use cases for the Alteryx platform we launched on community.alteryx.com during Q2.

To the 21 million citizen data scientists who are stuck in VLOOKUPs in brittle spreadsheets, we deliver a business-friendly code-free platform that enables them to ask the right questions and get the answers they need from their data to drive better decisions.

We are also addressing the trained data scientists around the world who are looking for a code-friendly platform that supports open source tools like Arc, Python and Scala, to help them more effectively do their jobs and get more of their models deployed and operationalized in an efficient manner.

And for both audiences, we offer a world-class data prep and blending capability, which represents the on-ramp for the entire continuum of analytics delivered by the Alteryx platform, ranging from descriptive analytics, typically revealed via interactive dashboards and visualization tools, to high-value analytics, including spatial, predictive, prescriptive and cognitive modeling, including machine learning. We view Alteryx as the heart of the analytics enterprise.

Along with the millions of analysts and statisticians around the world, we see the emergence of leaders within enterprises who are focused on weaving a data and analytic culture into the DNA of their company, effectively turning every data worker into a discoverer of marginal profitability. The emergence of these chief data officers, or CDOs, is becoming increasingly important as they are advocates for modern analytic platforms such as Alteryx.

The CDO is looking for an end-to-end business-friendly platform, with both simplicity and sophistication to win with analytics in their digital transformation. They are driving the networking effects of people, data and technologies and want to accomplish it in a social, collaborative and yet governed manner. Thus, our vision is to make the analytic journey even more thrilling by providing enterprises with a modern data cataloging and metadata management module to discover and share all the relevant data, reporting, dashboarding and spreadsheet assets that CDOs, business analysts and data scientists might need to make their journey efficient and productive.

At Inspire, we announced the upcoming launch of Alteryx Connect, our social data exploration platform that enables users to discover and utilize relevant information assets in their organization to drive better business outcomes. Gartner indicates that companies who leverage these types of data cataloging services will realize twice the value from their analytic investments. With Alteryx Connect, we believe we have the only platform for data cataloging combined with the best-in-class data prep and advanced analytics.

Alteryx Connect is based on the Semanta acquisition we have previously discussed. Connect will be made available as an add-on module to Alteryx Server later in Q3.

We are also really excited about our recently announced acquisition of Yhat. Today's data scientists are spending considerable time building advanced statistical and machine learning models and then struggle to deploy and manage them. We believe the only thing worse than building a bad predictive model is not being able to deploy a good one. According to a 2015 report by Rexer Analytics, only 13% of data scientists say their models always get deployed, and 25% say that deployment often takes months or years. With Yhat, we expect to offer a robust and highly reliable architecture for deploying, managing and scaling advanced analytic models. This way, the models built by both data scientists and the business analysts can be deployed, managed and monitored to help the CDO maximize the value from their analytic investments.

The market for Alteryx is large, and with the innovation we are building into the platform and our investments to drive awareness and adoption, we believe we are strengthening our ability to further capture this market.

During the second quarter, we added 258 net new customers, bringing our total customer count to 2,823. Many of these new customers are very recognizable brands, landing for the first time with multiple seats of Alteryx Designer.

Headquartered in Atlanta, Mercedes-Benz USA is responsible for the distribution, marketing and customer service for all Mercedes-Benz USA products in the United States. The business intelligence team and the aftersales group has adopted Alteryx Designer and said it -- says it is the most complete answer to their data blending and analytic needs, overcoming limitations of previous tools and enabling them to work at scale and with broader analytic capabilities. At Mercedes-Benz, Alteryx has quickly become an integral part of the aftersales department, with a primary user indicating that Alteryx is "a key piece to how I do my daily job. It's the only way we have to do the analysis we are now attempting, and without Alteryx, we may not have even tried." Mercedes-Benz USA is already finding ways to integrate Alteryx into other areas of the aftersales business.

In Q2, we did business in over 50 countries across the globe, and international expansion remains a key growth driver for us. Weave Services, a new customer in Q2, is a Hong Kong-based supply chain consulting firm focused on planning and building advanced replenishment models for customers. This involves dealing with large data sets, often unstructured data and fragmented across multiple locations. Weave regularly deals with tasks involving hundreds of millions of data combinations, which exceeds the capacity that Excel and VBA-based models can support. The introduction of Alteryx has enabled Weave to dramatically reduce the processing time and increase the granularity of analysis, which has ultimately resulted in improved customer service. Weave now sees Alteryx as strategically important to the company and is developing more in-house Alteryx experts.

With the emergence of CDOs, IT is appearing earlier in the sales cycle and as a result, we believe, over time, there is the opportunity to see a portion of our customers start with larger initial purchases and scale more quickly, complementing our existing land-and-expand strategy.

For example, we experienced a large new customer land in Q2 with the State Department Federal Credit Union, including multiple designers, Alteryx Server and our full data offering. The IT department and head of business intelligence at the State Department Federal Credit Union knew that having the right platform to leverage data was vitally important to helping the C-Suite achieve its strategic goals. Without Alteryx, they faced obstacles in integrating data, ensuring data quality and proper data profiling, resulting in their various departments making decisions based on imperfect information. They are also committed to moving to a cloud-based infrastructure, so they needed a robust and cloud-aware platform to not only cleanse and prepare data sets as the first step in the analytic process, but one that could handle data profiling and help manage a new data governance practice.

Using the Alteryx API, they now enrich their data using the data bundles in Alteryx to deliver the analytics used in both the marketing and loan origination department. The head of BI told us that it was an easy sell to the business as he was amazed at how much he could achieve with Alteryx right out of the box and without time-consuming training needed, not to mention the significant cost advantage over other more complicated products. The State Department Federal Credit Union use Alteryx as the core of their analytics future.

The expand side of our go-to market model continued to perform quite nicely in Q2. Customers continued to realize value in the Alteryx platform, giving them the confidence to expand with us. In the second quarter, our dollar-based net revenue retention was 134%. As a result of the strength of our land-and-expand model, we continue to improve our direct and channel presence around the world. And to help expand our base, in Q2, we released localized versions of our platform in French and German.

These efforts have helped us secure Q2 product expansion in the international customers like BNP Paribas. BNP Paribas' international retail banking division serves millions of customers across its banking network. Simply put, for their business model to work, they need to have retail branches in the right places. To assess individual branch network, they need to blend multiple sources of customer and target market data and compare it against their customer's geospatial data for analysis and model development.

Before embracing Alteryx Server and its ability to expose the Alteryx API, capturing the essential geospatial data for multiple countries would have required a costly purpose-built GIS tool. But within 1 week of using Alteryx Server APIs, the team designed, tested and operationalized an Alteryx workflow that used the Google geolocation API and returned both latitude, longitude data as well as a score for qualifying locations. And with this intuitive and visual user interface, Alteryx gives BNP Paribas' analysts the ability to monitor what they're doing with the data at every step, offering them more choices and more insight, resulting in a stronger view of their global business and where they can at optimize branch locations.

In summary, this was another very successful quarter for Alteryx. We are building the leading end-to-end analytics platform for the enterprise, and our journey is just beginning. We see tremendous opportunity ahead of us and remain focused on building our organization for long-term success.

With that, let me turn the call over to Kevin Rubin, our CFO. Kevin?

Thanks, Dean. I would also like to say that I'm very pleased to be speaking with you this afternoon. Today, I will be discussing our second quarter results, and then I will review our third quarter and full year 2017 guidance.

Let's start with our second quarter results. Revenue was $30.3 million, an increase of 52% year-over-year and ahead of our prior guidance. International revenue was just under $7 million for the quarter, an increase of 77% year-over-year and 22% of our Q2 revenue. In the quarter, we added 258 net new customers and ended with 2,823 total customers. We delivered a strong Q2 dollar-based net revenue retention rate of 134%. Please keep in mind that our dollar-based net revenue retention can fluctuate a bit depending on mix of business and seasonality.

Before moving on, I would like to point out that I will be discussing non-GAAP results going forward, unless otherwise noted. Non-GAAP measures, including our guidance for the third quarter and full year 2017, excludes stock-based compensation and acquisition-related adjustments, including amortization of intangibles, changes in fair value of contingent consideration and related income tax adjustments.

In addition, non-GAAP net loss per share, basic and diluted, excludes the accretion of our 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, 2017, and 2016 respectively. 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 84% in the second quarter, an improvement compared to an 81% gross margin in the second quarter of 2016. Gross margin was positively impacted by a larger portion of subscription revenue and greater efficiency in our support organization.

Operating loss was $5.5 million, which equates to an operating margin of negative 18%. This was ahead of our guidance and is an improvement compared to an operating loss of $6.4 million or a negative 32% margin in the second quarter of 2016.

We focused our sales and marketing investments in Q2 on programs to drive awareness and adoption and through the addition of quota-carrying salespeople, realizing leverage as we do so. In particular, in the second half of the year, we are accelerating some sales and marketing investments in countries within Europe and Asia, where we see increased opportunities.

In R&D, as we focused on innovation and delivering more value through our platform, you should continue to expect to see the pace of investing increase in 2017 versus 2016. This also includes the May acquisition of Yhat. We remain focused on investing for the future while we chart a course to sustainable cash flow generation and profitability.

Net loss was $5.3 million and net loss per share was $0.09, based on 58.3 million weighted average shares outstanding, basic and diluted.

Turning now to our GAAP balance sheet. As of June 30, we had cash, cash equivalents, short-term and long-term investment of $182.7 million compared with $52.7 million as of December 31, 2016, and $170.5 million as of March 31, 2017. We generated $669,000 of positive cash flow from operations in the quarter and $5.7 million through the first 6 months of 2017. Given our subscription-based business model, in annual billing terms, we expect cash flow to lead our path to profitability.

Finally, we ended the quarter with 491 employees, up from 398 employees at the end of the second quarter of 2016.

Now let's review our guidance. For the third quarter of 2017, we expect GAAP revenue in the range of $31.8 million to $32.3 million. We expect our non-GAAP operating loss to be in the range of $4.5 million to $5 million and non-GAAP net loss per share, basic and diluted, of $0.08 to $0.09. This assumes 59 million non-GAAP weighted average shares outstanding, basic and diluted.

For the full year 2017, we are raising our guidance and now expect GAAP revenue in the range of $125 million to $126 million, representing year-over-year growth of approximately 46% to 47%. We expect our non-GAAP operating loss to be in the range of $18 million to $19 million and non-GAAP net loss per share, basic and diluted, of $0.32 to $0.34. This assumes 56.5 million non-GAAP weighted average shares outstanding, basic and diluted. We expect to generate positive operating cash flow for the full year 2017.

We are pleased with our performance in the second quarter and believe we are building a differentiated business with strong growth and profitability.

With that, we will open the call for questions. Operator?

(Operator Instructions) Our first question today is coming from Jesse Hulsing from Goldman Sachs.

So net revenue retention rate ticked up versus the first quarter, and it looks like billings growth also accelerated versus the first quarter. I'm wondering, are you starting to see any sort of meaningful increase in ASPs, particularly in your expansions? And I guess, in general, are the sizes of the deals that you're doing growing as you start to involve the Chief Data Officer and move up from a strategic priority point of view?

Hi, Jesse. Well, yes, we're starting to see CDOs coming into the picture earlier. We don't see any changes in sales cycles necessarily yet. We don't see increases in ASP yet, what we do see though is that the overall market, in part because of CDO awareness, people are beginning to expand faster. In fact, you'll note that for the same quarter last year, we're now up 7 points on net retention. So some of that is the awareness of the market. Obviously it's a huge space. And some of that is just us better prosecuting the land-and-expand model, iterating on our playbooks for both the sellers as well as our demand-gen efforts. And we would hope to see this continue.

Got it. And, Kevin, a question on leverage. Based on your guidance, you all have averaged about 1,000 basis points of leverage per year over the last 2 years on the operating margin side. Is that something that we should expect over the medium term? Do you see opportunity to ramp investment as we move into '18? How are you thinking about that, I guess, over the next 4 to 8 quarters or so?

Yes. Hey, Jesse. I mean, we're not guiding out into '18 yet. I guess what I would say is we've certainly demonstrated leverage in the model. We continue to invest, and yet we're still being able to realize that leverage and indicative of the guidance we have for '17, at least, that's what you're seeing.

Our next question today is coming from Mark Murphy from JP Morgan.

This is Matt Coss for Mark Murphy. At your user conference in early June, we spoke to some of your customers who indicated a vision of going really big onto Alteryx. And one example, a customer spoke of imaging going from a dozen to perhaps in the thousands of users. And I know you already have some customers of this scale, but what are some of the characteristics of the organizations that will get to this scale with you? And are you seeing an increase in the number of organizations like this? And are you actively engaged in discussions with some customers that will potentially deploy on this level of in the thousands of users?

Well, so analytics is a prerequisite for success in business, and so we see all kinds of businesses engage with Alteryx. Having said that, though, there are a certain class of customer, whether it's by vertical space or by employee class size, that tend to have a better cohort performance. And so part of the reason we have that 7-point improvement in our net revenue retention rates this year over last year is that we're beginning to understand, through our own use of Alteryx and our own data on customers, to know who to spend more time with in going after. Yes, and I think the other part of it is that there's 21 million disenfranchised analysts around the world living in complex VLOOKUPs and Excel and we barely scratch the surface. And I think the emergence of CDOs is bringing an awareness to business that it's no longer a talent gap, it's actually a platform gap, and Alteryx fills that need because our whole mission is to provide these analysts with the thrill of solving almost any problem.

That's helpful. And then just one more quickly. I know you don't guide to this, but billings in Q3 last year was pretty strong. It's going to be your toughest comp, billings, and Q1 and Q2 this year so far exceeded our estimates. How do you -- I guess, maybe how should we think about the outperformance we've seen thus far, coupled with the strong billings from last year? And how should we view this to sort of think about Q3?

Yes, so I mean I would just point you to the metrics we do guide to with respect to Q3 as indicative of the trend we're seeing.

Our next question today is coming from Brent Bracelin from Pacific Crest Securities.

This is Alyssa Johnson on for Brent. I was hoping you could talk a little bit about what you're seeing internationally and kind of pairing this with your decision to invest a little heavier. Is that coming from along the lines of bigger customers over there, broad-based strength? Help us walk through that strength you're seeing over there.

Hey, Alyssa. Great questions. So yes, we saw a certain uptick in international revenue last quarter, $7 million, 77% growth, relatively small numbers. However, we see a huge opportunity around the world. Just kind of an illustration, we did business in more than 50 countries last quarter, most of which are places we don't have either partners and/or direct sellers. And so we have a fairly prescriptive approach on how we rationalize the investment that we're making overseas. We look at everything from the number of trial downloads from each country, we look at the inbound activity on interest from potential partners, we look at social media and what countries they're coming from. And so we have a fairly disciplined approach to where we're going to invest, and Kevin mentioned parts of Asia Pac and continued investment in Western Europe. We extended our capability to the platform by localizing in both German and French last quarter, and we have plans to continue to roll out that capability, not just in help and documentation, in UI, UX localization, but community localization. And I think your point is well taken. We -- in our IDC study that we conducted prior to the S-1, they found 21 million of these disenfranchised analysts around the world. Only 5 million of them were in North America. So we know that there's the same kind of business problem that exists in every business in every land and we see this as an opportunity to continue to grow and scale Alteryx for quite some time.

Great. And then a follow-up question I have. You mentioned these APIs that you have, kind of BNP Paribas and the State Department Federal Credit Union. Can you kind of walk us through what exactly those are, what those do? Is it something you've had for a while? Or why are these noteworthy? It seems like maybe a new trend? Or how do you characterize those APIs?

Sure. So the API capability has been around for quite some time, really from early versions of our Server product. And I think the illustration of this is that customers are beginning to expand their footprint of Alteryx to incorporate server deployment, which leads to even the next big economy, which is the App and API economy. So within the Alteryx platform, whether it's a citizen data scientist or a trained data scientist, they can build analytic workflows with 250-some-odd tools, allow them to ingest and clean and organize and standardize any data, apply any range of simple to complex arithmetic, to algorithmic, to predictive processes and expose the result as a RESTful API, that can immediately be ingested for embedded applications. And so we're seeing a lot of organizations begin to fuel machine learning models, which led to our decision to acquire Yhat for model management. And we're beginning to see organizations deploy more and more applications from Alteryx as a user interface or as an API so that more people can deliver benefits around analytics. And this is exactly what the CDO is after. The CDO is trying to get the networking effect of not just technology and data, but people who are involved in decision-making processes.

Our next question is coming from Michael Turits from Raymond James.

This is Austin Dietz on for Michael. Right, so I think we've had Alteryx Server available on AWS for about a quarter now, so maybe you could tell us what you're seeing in terms of adoption and it's actually accelerating adoption in the Alteryx platform. And secondly, I know Alteryx availability on Azure was announced in June, so perhaps you could tell us what uptake has looked like there as well?

Yes, thanks for asking. It's relatively light. We see activity, we don't see tons of activity. We don't see everything because customers have the ability to take their own license. So we don't have visibility into those particular cases. Many of our customers do stand up Alteryx Server in the cloud, they buy a license from us and they have private services up in either AWS or Azure. As far as the commercial offering, we're starting to see more activity around trial licenses for people who don't necessarily -- and this is one of our reasons for launching on both platforms. We have weighted the hassle of an organization getting IT necessarily involved too early to do trial experiences with Alteryx. And I think this also kind of illustrates the fact that not everyone is moving to the cloud for complex analytics as quickly as some might think. It's going to be an on-prem hybrid cloud world for quite some time. There'll probably be hybrid cloud world in the future. But we're hopeful. We think that we've made it easier for customers to try our products out in both platforms, and we're pretty excited about the possibilities going forward.

Our next question today is coming from Greg McDowell from JMP Securities.

One for Kevin and one for Dean. First, for you, Kevin. This is the third quarter in a row of positive cash flow from operations. I was just hoping you could maybe help us think through the second half cash flow from operations and whether we should be careful in how we sort of model the second half cash flow number.

Yes. Thanks, Greg. So we did -- I did mention in my prepared remarks that we expect to be cash flow positive from operations for the full year. We did conduct our Inspire Conference in June of Q2, and a large part of the cash outlay connected to that conference does come in Q3. So keep that in mind as you're thinking through your model. But nonetheless, we are expecting positive for the year.

That's helpful. And then one for you, Dean. One of my big takeaways from your user conference was just the sheer number of customers using Alteryx in use cases beyond the visualization platform. I think you cited over half of customers using Alteryx for spatial analytics, almost half of customers using Alteryx in predictive analytics use cases. I was just hoping you can maybe take a minute and expand on sort of some initiatives in place that go after, I guess, specifically, the predictive analytics market opportunity, vendors like SPSS and such?

Good question. So I too noticed the big difference in Inspire this year. It felt much more data science-y than in years past. Not only was it much bigger, but there was a more of the data science- feel. And we're beginning to notice our customers consume and build more and more sophisticated analytic models, proof that the data prep and blending prowess that we have is just that on-ramp to the entire continuum of analytics. And so as we allow the citizen data scientists in a code-free environment to build sophisticated statistical and predictive and prescriptive models, we also offer the trained data scientists the ability to do the same thing and to instantly deploy now, with our Yhat acquisition, the ability to deploy models in a very rapid fashion. So we continue to roll out new capabilities on our community that illustrates the use cases for Alteryx, in some cases, for predictive and spatial and cognitive learning. We rolled out 160 use cases in Q2 that illustrate the power of the entire end-to-end process of the platform, not just the data prep and blending capability. And so I think we're beginning to see the early stages of disruption from the analytic platforms of yesteryear, where I think the citizen data scientist is now getting the trained data scientist to think a little bit differently about their skill set, and we're beginning to embrace more and more of the 1 million to 2 million data scientists who also want to be thrilled to solve problems for the business and instantly deploy models with a few clicks, something that's never been done before.

Our next question today is coming from Derrick Wood from Cowen and Company.

I just wanted to follow up on that subject. So just people are wondering what you're seeing competitively in the advanced analytics side of the business. Are you competing head-to-head against SaaS or SPSS very often? Are you displacing them? Or is it really about kind of new use cases, more greenfield and not really much competitive overlap?

We generally don't go in head-to-head competing with nearly anyone. I think that we tend to see point solutions, and you would -- as I probably have indicated before, you would need 4, 5 or 6 different point solutions and then you would have to take out all the friction of movement between those solutions to actually be competitive with the Alteryx platform. That said, we sometimes will run into a rapid miner in a predictive use case or [as we're in] a spatial use case, but there's no real way to just compete there. We tend to do Trojan horse activity, where once they see the power of our platform, they begin to -- and again, this is where CDO is very helpful, the CDO wants everyone on a standard platform, in both a code-free and a code-friendly environment, so they can leverage the networking effect of data technology and, most importantly, the people in the process. So over time, we hope to do much more of the predictive space.

Okay. And then you also mentioned, and I know you've said this before, that IT is becoming more involved in the self-service data analytics decision-making. In light of some of the new metadata capabilities coming out with Connect later this year, are you seeing IT engage more in pipelines? And I guess I'm just trying to get a sense. Do you think this, once it does come out, you get more IT buy-in, that this could be an incremental catalyst for you guys?

No, we believe it is. We don't see any huge increment -- incremental gains to revenue in the short term. We'll be rolling out Connect in Q3. We're pretty excited about it. We've been in co-innovation processes with about a dozen customers for the last couple of months. IT is awoken to the notion that self-service of data analytics is real. The CDOs are bridging the gap between IT and the line of business, so that has a huge influence. And then what the reality is, is as we begin to empower all of these analysts and all of these Ph. D.s to easily blend in data and prepare a new model and then easily deploy it, then the analytic journey has to start off with being able to find the right assets for that journey, and there's nobody in the organization that does not want that to happen. So I think it's the inflection of buying from IT, the influence from the CDO. And of course, the users love it because it connects not just the data and the assets and the reports and the visualizations they need for their journey, but it connects them to the people who can tell them about those assets and what they might have to do to those assets as they begin their analyst journey. So we're very excited about the rollout of Connect.

Our next question today is coming from Bhavan Suri from William Blair & Company.

Guys, can you hear me okay?

Yes, perfect.

Just a couple of questions for me. I guess, first, just on the customer adds, 258 was really solid here. Is that really still being driven by data prep as the on-ramp, Dean, as you were saying? Or is actually the advanced analytics becoming a part of the initial purchase? Because typically, the initial purchase has been data prep and then adds have gotten to use it and dropped sort of the random walk and things like that until they've realize the power of the advance analytics platform. But I guess, I'm just asking, initially, are you seeing the advance analytics platform become more important to the initial buyer, vis-à-vis just data prep?

Great question. I think that our sellers and our marketers are telling the end-to-end story earlier. The reality is nobody does data prep for data prep's sake. A lot of customers do come to us, and many of the new customers that we obtained this last quarter, as in most quarters, they just want to solve the problem at hand, which is preparing 4 or 5 disparate data sets together. But they're always intent on delivering some analytic outcome, whether it's descriptive, all the way to cognitive. And so by better telling that story to a more aware audience, with influence being now driven more by IT and by CDOs, I think you're right, we're beginning to see people embracing the higher-order advanced capabilities earlier in the process. And I think that's been part of why we saw such a shift in the excitement around predictive at the conference.

Yes. Yes. I guess just to follow up, and I may have a couple more, but just to follow up on that train of thought for a second. Obviously, a lot of buzz about AI machine learning. Does that actually help you guys yet, or is that still at a level deeper, where people are still sort of doing core machine learning-type development or AI? Or is that sort of broad-based trend, getting people to understand that I can build a model and alter it, share it and actually use that for a -- almost a self-learning analytical environment, maybe not for a system, but certainly, for a set of data to help business outcomes? Or am I sort of -- are we still early on that sort adoption phase, if you get what I'm saying?

Yes, I do. I think it's still early, and I think that's not going to be driven by the citizen data scientists as much. Those folks are going to be doing the day-to-day blocking and tackling around analytics for the enterprise. But we are seeing the citizen data scientist do a lot more around predictive modeling, everything from linear regression to [key meetings], testing, to forced modeling. The Ph. D.s, the statisticians who are trained, we do see them doing more advanced models, exposing RESTful services. And again, the benefit of the Yhat acquisition, which we'll have some announcements on in the not-too-distant future there as well, the -- whoever is building the model with that respect, because we make it easy for anyone to build the model, but whoever does build the model can instantly deploy it and scale it with a couple of clicks to the Yhat infrastructure, so that you can easily embed models for other mobile and web-based applications.

Yes, you sort of preempted my next question, so I would let it go. I was going to say, so with the acquisition, when do you see that coming? But I'll wait until the announcement. I guess one quick last one from me. Someone I think on the call had mentioned about adoption in Europe, and one of the things we've seen with European customers that adopted open source typically faster than North American customers, whether it's Linux, whether it's R. Now given your tie to R, that to me feels like a tailwind for growth in Europe. As you guys go to the market with the story and the integration around R, is that something you're starting to see help pick up awareness and traction out there too?

Well, to a certain extent, I see that. I think it's almost table stakes at this point. I mean, R is clearly the leader. And maybe in some countries, kind of a horse race between Python and R, which is why we're beginning to march down the path of Python and Scala support in the future. I think that open source has changed the world quite a bit, not just for us, but most of the vendors. There's almost all of the vendors out are somehow embracing the R environment. The difference for us is that we've made it so that you can ingest any R package, put a user interface around it. You can encrypt it as many of our customers do. They'll test R models, not just leverage the prepackaged R models. They'll build their own R models, encrypt them and then share those models with everyday analysts who need to be able to get better insights on more sophistication without actually having to build the models themselves. And then, of course, with the Yhat, the ability to expose those models for -- as a RESTful service so that we can get to the API economy.

We've reached the end of our question-and-answer session. Let's turn the floor back over to Mr. Stoecker for any further closing comments.

Sure. Thank you. Before we end the call, I just want to thank everyone for joining us today, and we look forward to speaking with you in quarters in the future.

I also want to thank all of our employees and partners for their efforts in getting us to success with this last quarter. And of course, a big shout out to our customers for their ongoing commitment to both Alteryx the company and Alteryx the platform. Thank you very much, and have a great day.

Thank you. That does conclude today's teleconference. You may disconnect your lines at this time and have a wonderful day. We thank you for your participation today.