Alteryx Inc
F:3AI
| US |
|
Johnson & Johnson
NYSE:JNJ
|
Pharmaceuticals
|
| US |
|
Berkshire Hathaway Inc
NYSE:BRK.A
|
Financial Services
|
| US |
|
Bank of America Corp
NYSE:BAC
|
Banking
|
| US |
|
Mastercard Inc
NYSE:MA
|
Technology
|
| US |
|
UnitedHealth Group Inc
NYSE:UNH
|
Health Care
|
| US |
|
Exxon Mobil Corp
NYSE:XOM
|
Energy
|
| US |
|
Pfizer Inc
NYSE:PFE
|
Pharmaceuticals
|
| US |
|
Palantir Technologies Inc
NYSE:PLTR
|
Technology
|
| US |
|
Nike Inc
NYSE:NKE
|
Textiles, Apparel & Luxury Goods
|
| US |
|
Visa Inc
NYSE:V
|
Technology
|
| CN |
|
Alibaba Group Holding Ltd
NYSE:BABA
|
Retail
|
| US |
|
3M Co
NYSE:MMM
|
Industrial Conglomerates
|
| US |
|
JPMorgan Chase & Co
NYSE:JPM
|
Banking
|
| US |
|
Coca-Cola Co
NYSE:KO
|
Beverages
|
| US |
|
Walmart Inc
NYSE:WMT
|
Retail
|
| US |
|
Verizon Communications Inc
NYSE:VZ
|
Telecommunication
|
If you don’t study any companies, you have the same success buying stocks as you do in a poker game if you bet without looking at your cards.
Utilize notes to systematically review your investment decisions. By reflecting on past outcomes, you can discern effective strategies and identify those that underperformed. This continuous feedback loop enables you to adapt and refine your approach, optimizing for future success.
Each note serves as a learning point, offering insights into your decision-making processes. Over time, you'll accumulate a personalized database of knowledge, enhancing your ability to make informed decisions quickly and effectively.
With a comprehensive record of your investment history at your fingertips, you can compare current opportunities against past experiences. This not only bolsters your confidence but also ensures that each decision is grounded in a well-documented rationale.
Do you really want to delete this note?
This action cannot be undone.
| 52 Week Range |
42.3
45.1
|
| Price Target |
|
We'll email you a reminder when the closing price reaches EUR.
Choose the stock you wish to monitor with a price alert.
|
|
Johnson & Johnson
NYSE:JNJ
|
US |
|
|
Berkshire Hathaway Inc
NYSE:BRK.A
|
US |
|
|
Bank of America Corp
NYSE:BAC
|
US |
|
|
Mastercard Inc
NYSE:MA
|
US |
|
|
UnitedHealth Group Inc
NYSE:UNH
|
US |
|
|
Exxon Mobil Corp
NYSE:XOM
|
US |
|
|
Pfizer Inc
NYSE:PFE
|
US |
|
|
Palantir Technologies Inc
NYSE:PLTR
|
US |
|
|
Nike Inc
NYSE:NKE
|
US |
|
|
Visa Inc
NYSE:V
|
US |
|
|
Alibaba Group Holding Ltd
NYSE:BABA
|
CN |
|
|
3M Co
NYSE:MMM
|
US |
|
|
JPMorgan Chase & Co
NYSE:JPM
|
US |
|
|
Coca-Cola Co
NYSE:KO
|
US |
|
|
Walmart Inc
NYSE:WMT
|
US |
|
|
Verizon Communications Inc
NYSE:VZ
|
US |
This alert will be permanently deleted.
You don't have any saved screeners yet
Greetings, and welcome to the Alteryx Third Quarter 2019 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.
It's 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's third quarter 2019 financial results. With me on the call today are Dean Stoecker, Chairman and Chief Executive Officer and Kevin Rubin, Chief Financial Officer. Additionally, Scott Jones, President and Chief Revenue Officer, will be joining us for the question-and-answer session after prepared remarks.
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 uncertainties. 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 EDGAR system and our Web site, 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 and the Investors section of our website for a reconciliation of these measures to their most direct comparable GAAP financial measures.
With that, I'd like to turn the call over to our Chief Executive Officer, Dean Stoecker. Dean?
Thanks Chris, and thank you everyone joining us today. Alteryx delivered another solid quarter in Q3. On today's call, I will be providing some high level market trends that we believe validate our longer term strategy; these trends are automation, convergence and community. Kevin will then walk through our Q3 performance and our outlook for Q4 and full year 2019.
Before we get started, here are a few highlights. Revenue was $1.3 million, up 65% year-over-year. Non-GAAP operating margins were 21%. And we generated positive cash flow from operations of $7 million. We added 335 net new customers, including 27 of the Global 2000. We now have over 5,600 active customers, including 34% of the Global 2000.
Net expansion was 132% as customers continue to invest in Alteryx as their data science and analytics platform of choice across their enterprises. In the quarter, we had 92% growth in the number of expands greater than $250,000. We believe Alteryx is benefitting from a number of trends we expect will enable us to deliver growth for many years to come.
The first is automation. While overall IT spending levels are expected to post only modest growth in 2020, we believe there are emerging categories that will demonstrate outsized growth. One of these categories is automation. We are increasingly hearing from customers the desire to drive more operational efficiencies. And in uncertain times, companies look to do more with less. IDC indicated there will be $2 trillion spent on digital transformation in 2019 alone. And last year, the World Economic Forum found that 29% of all work was formed by machines, and is expected to grow to 42% by the end of 2022.
Additionally, industry analysts have estimated that a significant portion of data science tasks will be automated by 2020. Identifying and preparing data for analysis remains the more time consuming task facing data and analytics users. This leaves much of the data work to the line of business analysts, data scientists or many cases, data engineers and IT. This creates business risk due to a lack of data governance as organizations give more users the ability to access data directly to create analytic content.
By automating both simple and complex analytics tasks with the Alteryx platform, we can significantly increase the productivity for all categories of data workers across the enterprise. As a leader in the analytics market that is agnostic to the shape, size and location of data, as well as agnostic to how it is consumed, we have a unique position in the market. Alteryx Designer enables companies to build workflows to automate data, data science and analytic pipeline, and Alteryx Server orchestrate these pipelines autonomously, yet in scheduled, scaled, secured and governed ways.
This type of advanced analytics process automation is increasingly important, and our messaging is resonating with Chief Data Officers overseeing digital transformation efforts for enterprises around the world. Customer conversations about the first mile of analytics leveraging the social catalogs of Connect, and the onerous last mile of analytics via the model deployment and management of promote, are becoming more common. We believe the addition of our recently announced acquisition of Feature Labs and their expertise in automated feature engineering and auto modeling will also advance our automation capabilities and bring another level of sophistication to the Alteryx platform.
Automation is also increasingly coming into play with our open and expanding ecosystem of partners, another key element of our growth. Conversations around driving digital transformation and automation are at play in organizations of all sizes, and in all theaters around the globe. Partners continue to play a critical role in these conversations, and we intend to expand the number and type of partners we engage with around the world. As a leading standalone end-to-end data science and analytics platform in the market today, we have proven have a unique value proposition for independent software vendors, large systems integrators and global advisory and analytic consultants.
The second trend is convergence of analytic personas. We are starting to see the citizen data scientists who are business professionals with limited or no coding abilities, and professionally trained data scientists that have strong coding abilities converge around a single platform for their analytic work. Next generation technology providers will need to address the requirements of users with a variety of skills, coding abilities and comfort with advanced analytic capabilities, including spatial and predictive analytics, machine learning and auto modeling.
Citizen data scientists are no longer simply creating dashboards and status reports, but are working on higher value outcomes. And data scientists are increasingly looking to automate and streamline data pipelining to enable them to spend more time on building, operationalizing and managing models. Alteryx addresses both of these challenges by up-leveling skills for line of business analytics and automating data flows and streamlining model deployment and management for data scientists, all via a single unified platform experience. This convergence has been accelerating with the emergence of Chief Data Officers and organizations focusing on digital transformation.
While the competitive field is populated with vendors delivering some dimensions of the analytic and data science needs today, they fail to address the automation needs for the entire end-to-end analytic pipelines. We believe the Alteryx platform is uniquely suited to unlock tremendous business value across all analytic personas. We also believe that we are well positioned to win in this market, because of our extreme focus on customer success; winning the hearts and minds of data workers across the globe, while driving enormous value. For example, at Inspire EMEA held in London earlier this month, we have the opportunity to hear from a number of customers who graciously shared their Alteryx success stories.
And [Amro Abdoun], Senior Financial Controller at Siemens AG who is responsible for the Digital Finance Initiative with a focus on automation, was able to productionize his first workflow within two weeks without any formal training, enabling thousands of employees to consume analytic reports powered by Alteryx. [Rafal Olbert], a Data Scientist at UK Retailer Asda, is focused on e-commerce analytics. And when he found Alteryx, it was love at first sight. He said with Alteryx, we have revolutionized the way we connect, work and drive true insights with data. His organization has productionized nearly 200 daily workloads and 10s of analytical applications, democratizing data and embracing the mindset of true self-service analytics.
Another example is a large systems integration effort with Alteryx that saved $1 million in internal costs by monitoring online media. In a third use case, involving product availability, Alteryx helped reduce the unfulfilled rate, one of the biggest challenges in e-commerce by 7%, which resulted in both enhanced customer experience and reduced costs.
The third trend is community. We have long seen analytics as a social experience and now is on full display as Inspire EMEA. The mix of attendees at Inspire truly illustrates the range of our platforms' capabilities. We had attendees from 19 industries, 11 functional areas from 48 countries, prosecuting dozens of use cases and sharing their successes with each other.
Carlene Jones, Data Scientist for global pharmaceutical company Novo Nordisk, is one of 350 users who are creating huge amounts of innovations, including working on a wide range of challenges across supply chain, finance, R&D and more. Alteryx made a significant difference in many areas, including automating routine reporting where they were able to take processes requiring four man months to just a few minutes. Additionally, they have improved their notoriously difficult demand forecasting process, building segmentation models that improve the planning process and have plans to continue to innovate across the company with Alteryx. As part of their analytic culture, they've founded an internal Alteryx user group, helping to facilitate continued analytic innovation.
And finally, Brian Millrine, Business Strategy Director for the UK based Brookson Group, indicated that Alteryx is bigger than analytics and bigger than data science. We see Alteryx as a digital transformation platform, underpinning our own digital platform, which provides services to the flexible workforce, including procurement, payroll, accounting and financial services. Alteryx brings intelligence to our customer portals. It drives customer next best action. It automates bookkeeping. It even underpins the delivery of complex tax advice for our customers. With Alteryx, we are not just building workflows that save tens of thousands of pounds, we are building workflows that deliver products that create millions of pounds of shareholder value.
Given the multiple avenues of growth available to us, we expect to continue to invest in our platform and our go-to-market model in order to capitalize on the significant opportunities we face. Here at Alteryx, we believe that humans are only limited by their imagination. I am continually amazed and humbled by the breadth of use cases that our customers leverage Alteryx for each and every day.
With that, let me turn the call over to Kevin to discuss our Q3 financial performance and outlook for Q4 and 2019. Kevin?
Thank you, Dean. Q3 represented another strong quarter with revenue of $103.4 million, an increase of 64% year-over-year and net expansion of 132%. Our revenue upside was due to the following three factors; first, we had another quarter of strong execution; second, product mix was favorable, resulting in the upfront percentage of our revenue being once again at the high end of the range; third, we did see a modest sequential increase in contract duration, driven by some of our larger customers entering into longer term contracts, although, overall duration continues to average two years.
I'd like to briefly remind you of how our revenue is determined under ASC 606. Revenue is determined based on the total amount of bookings in the period, total contract value or TCV. As a reminder, we typically enter into one or three year agreements with our customers. TCV includes the full value of multiyear agreement.
Of our TCV booked in the quarter, we recognize between 35% to 40% of TCV upfront based on product mix. Sales of our designer products skew towards the lower end of the range, while sales of server, connect and promote skew to the higher end. Thus, as we experienced more enterprise wide deployment, that include servers, connects and/or promote, our upfront percentage skews towards the higher end of the range.
We recognize revenue upon the letter of contract signing or contract start date. As we discussed earlier, this year during our Q1 earnings call, this factor is important to keep in mind as we enter Q4, because we have a number of renewal contracts that expire at December 31st and which renew on January 1st. This dynamic results in Q4 TCV bookings that will not translate into revenue until Q1, 2020. Finally, revenue includes the recognition of the readable portion of our bookings.
International revenue was $28.7 million, up 48% year-over-year, as we continue to benefit from the strong global demand for analytics. This validates our continued investment in our global go-to-market and support organizations. In Q3, we added 335 net new customers and now have 5,613 customers, including 683, or 34% of the Global 2000. Notable customers that transacted with Alteryx during the third quarter include Amazon UK Services, Canada Post, Commonwealth Bank of Australia, Ingram Micro, Microsoft, Rakuten Marketing, Workday and Uber Technologies.
Before moving on, I want to remind everyone that unless otherwise stated, I will be discussing non-GAAP results. Please refer to our press release for a full reconciliation of GAAP to non-GAAP results. Our Q3 gross margin was 92% consistent with Q3 2018. Our Q3 operating expenses were $73.4 million compared to $43.2 million in the same period last year. The year-over-year increase in operating expenses was due primarily to additional headcount and other investments in scaling our global operations.
Our Q3 operating income was $22 million or an operating margin of 21%. Net income was $16.4 million or $0.24 per share based on $69.5 million non-GAAP fully diluted weighted average shares outstanding. Our net income assumes a non-GAAP effective tax rate of 20%.
Turning now to the GAAP balance sheet. As of September 30th, we had cash, cash equivalents, short-term and long-term investments of $986.5 million compared with $426.8 million as of the end of Q2 2019. The increasing cash is related to the convertible note offering we successfully completed in August. Finally, we ended the quarter with 1,176 associates, up from 1,076 associates at the end of Q2 2019 and 756 associates at the end of Q3 2018. Our increase in headcount is reflective of the pace of investments we are making and we expect to continue to make to capture the meaningful opportunity we see globally.
Now turning to our outlook for Q4 and full year 2019. Also, as a reminder, please note that our guidance assumes the following; the average duration of our subscription agreements will be two years consistent with current levels; approximately 35% to 40% of our TCV booked in the quarter with subscriptions start dates in the quarter will be recognized upfront, with the remainder recognize readably over the life of the contract; quarterly revenue seasonality will be consistent with what we experienced in 2018; and, no material changes to the overall macroeconomic conditions.
For Q4 2019, we expect GAAP revenue in the range of $128 million to $131 million, representing year-over-year growth of approximately 44% to 47%. We expect our non-GAAP operating income to be in the range of $26 million to $29 million and non-GAAP net income per diluted share of $0.27 to $0.30. This assumes 71 million non-GAAP weighted average fully diluted shares outstanding, and an effective tax rate of 20%.
For the full year 2019, we are raising our outlook and now expect GAAP revenue in the range of $389 million to $392 million, representing year-over-year growth of 53% to 55%. We expect our non-GAAP operating income to be in the range of $50 million to $53 million, and non-GAAP net income per diluted share of $0.57 to $0.60. This assumes $69.1 million non-GAAP fully diluted weighted average shares outstanding and an effective tax rate of 20%.
And with that, we'll open up the call to questions. Operator?
Thank you. We'll now be conducting a question-and-answer session [Operator Instructions]. Our first question today is coming Tyler Radke from Citi. Your line is now live.
Maybe to start off a question for Dean. It seemed like you talked more of this calla about automation and just around the evolving strategy of Alteryx. I know in the past as you've thought about M&A, the most recent acquisitions have seem to been kind of centered around acquiring assets and building out your citizen and data science capabilities. Just how are you thinking about balancing the investments from the product side and kind of the analytics versus automation capabilities?
Well, I actually think, Tyler, that the two go hand in hand when we talk about these trends of automation and convergence and community, all three are tied to digital transformation and success. And so as the convergence of the trained statisticians who loves to write code converges with the citizen data scientist who doesn’t know how to write code is capable of building models, but needs assistance in building those models. We're seeing the need for more automation within the data science world.
The reason we bought Feature Labs is that they've figured out what no one else has really figured out within the auto modeling space, and that is their focus on automated feature engineering, which is the precursor to actually having any model work and perform for you. So, a very tight analogy to our data prep world for the citizen data scientist to the automated feature engineering or the trained statisticians.
So automation is going to be important, going forward. It's going to affect routine analytics or day-to-day reporting KPIs, and diagnostic use of analytics in dashboards. But the more advanced capabilities around data science outcomes along with automation of those tasks is exceedingly important to us. And it's kind of coming up more and more in deals around the world.
And then maybe a less interesting question from a strategy perspective for you, Kevin. But obviously, there is a lot of metrics to look at this quarter, whether the very high strong revenue growth of 65% or an adjusted billings calculation that actually lower than that and also with this RPO number. How would you just encourage investors to evaluate the underlying growth of the business? And how should we think about the sustainability of that growth rate, going forward? Thank you.
As we've said for several quarters now under 606, given that a meaningful portion of our revenue gets recognized now upfront, I think revenue is a clear indicator of the strength, both in terms of the business as well as in quarter performance. We're obviously very pleased with the over performance of revenue this quarter. And coupled with ultimately our guidance for the future quarter, I think those two in combination are pretty indicative of how we see the underlying momentum in our business. Thanks.
Our next question is coming from Derrick Wood from Cowen and Company. Your line is now live.
I guess, first for Dean. We're hearing more analytics software companies partnering and integrating with cloud data lakes and cloud data warehouse vendors like Snowflake, who's seen a lot of growth. How are you guys positioned around companies like Snowflake? And do you see your users trying to leverage those cloud platforms in their Alteryx workflow?
Yes, and as a matter fact, Derrick, we do. As you know, our design time experience is on-premise and our runtime experience is wherever you choose to put it. We have a fair number of server-based customers who deploy, both in AWS and Azure. Many of them have leveraged Snowflake as their persistence layer of choice. Not all of them. Some have -- it's rare that anyone have a complete set of analytic pipelines that leverage a single data source.
Most of them have many persistence layers, some which resides in cloud vendor of choice, other person are persistence layers reside on-premise. So it's going to be a hybrid cloud on-prem and ultimately, cloud-to-cloud world for quite some time. We actually have a strong relationship with Snowflake. And many of our customers have moved off of other platforms to go to Snowflake, and we're quite supportive of our customers who choose to do so.
And Kevin, going back to the numbers. Obviously, you talked about two factors that pull more revenue upfront, that would be product mix, and then duration. And I think those were both tailwinds for you this quarter. Is there any way to quantify the benefits you reported revenue growth, whether in dollar terms or growth terms, because of these mix shift changes?
If you think about the product mix, we've talked to a reasonable range of 35% to 40%. So as you move across that range, I mean, you can kind of figure out that there's some contribution to product mix and its certainly favorable, but it's not enough in terms of order of magnitude to drive a significant uplift, but it does have an impact.
And then, duration as I've mentioned, there was a modest increase sequentially, but we're still averaging about two years. Both of those two factors certainly contributed to the strong revenue performance. But having said that, it was actually execution that really drove the lion share of the revenue that we put up this quarter.
Our next question is coming from David Griffin with William Blair. Your line is now live.
My first question is a quick follow up for Kevin on billings. First off, just want to say thanks for taking out the disclosure this quarter of the contract assets and give us a good compare. So as we kind of look at the year-on-year growth number here, 38% looks -- certainly looks pretty healthy. But given that it feels like this metric is going to be top of mind for investors on a go forward basis. I did want to ask if there is anything worth calling out from either a timing or seasonality perspective that may have been proven to be growth number this quarter.
So billings are, I mean, essentially an invoicing activity. At the end of the day, they're subject to the timing and the amount they could build in the contract. So to your point, there is seasonality, there is timing. And that can fluctuate quarter-to-quarter. As I mentioned to Tyler's question, we do think that revenue is the most appropriate indicator of the strength and momentum in the business. Billings can move up and down based on contractual arrangement.
And then just a quick follow up for Dean. So I wanted to dig in a little bit more into your experience at Inspire you have earlier this month. I think this was your fourth annual European customer conference, and it certainly sounded like that was well attended. So I was wondering if you could share kind of your key takeaways, maybe the top one or two from your conversations with customers at the event, as well as maybe just talk a little bit about whether you're seeing any key differences between your international and domestic customers in terms of something like adoption of the platform, usage characteristics, or just the general level of analytics maturity?
So let me address the first issue on Inspire Europe. Yes, we've had our fourth conference. We had roughly 2,500 customers, partners and employees in attendance. The biggest takeaway for me was the change in the conversations that we're having with customers. When we had our first Inspire EMEA conference four years ago, the conversations were more about who are you guys, what do you do, features and functions and trying to resolve very specific use cases. Today, the conference was about digital transformation, it was about building cultures where organizations are hoping to get their teams to think about data and asset to drive the business. They're thinking about automation. They understand this convergence of the citizen data scientist and trained statistician.
And most of the meetings that I had were identical to ones we had in Nashville back in June. How do we go from 100 seats to 500 seats, or how do we go from 500 seats to 5,000 seats. There was zero conversation about features and functions. It was about driving a culture of data science and analytics, because everyone realizes the power of automation in the hands of more people to solve more complex business challenges. So that was the first takeaway.
Second takeaway was there if you just noticed the lines at the advanced analytic sessions, it's clear we're striking the cord with both the citizen scientists and the trained PhDs, two of the people I had on stage were actually data scientists who are leveraging Alteryx in really, really interesting ways to drive enormous resolutions to complex problems that they face in the business.
So I think that for me the conversation was consistent with our trends, automation, convergence and community. Community is, it is the conference, it's pretty clear that people show up and they love to chat with each other. We know that the people who are involved in our community expand considerably more than people who are not involved in the community. We see through telemetry, they're advancing their skill sets by leveraging advanced analytic tool sets inside the platform.
The second part of your question was any big differences around the world? Actually, there's almost no difference. There's some cultural differences in certain parts of certain theaters around the world. But this quarter, for example, we landed 27 additional G2Ks, 17 of those were international. And it's the same problem, whether you're a major retailer in Dubai doing hyper local merchandising, or you're an airport in or an airline in Hong Kong, trying to hedge fuel. Everyone has these same issues.
So that part, again, we're really confident that we've touched a nerve with global organizations, which is why we've been reporting on and going after the G2Ks where 9 million of these citizen data scientists hang out and the lion share of the PhDs.
Our next question is coming from Ittai Kidron from Oppenheimer and Company. Your line is now live.
Kevin, starting with you on given that we're trying to focus on the right metrics, net expansion rates in terms of TCV basis, perhaps not the cleanest of or best indicator as well. Is there a way for you to give us perhaps designer seats expansion or paid designer seat expansion per customer? I mean, that will probably be a very good proxy to the true underlying expansion rate from a user standpoint within your customers.
That's an interesting point. I mean, I think if you look at the nature of our expansion, and we've talked about this in the past. We land with a few seats. We expand several times with more kind of blocks of seats. We introduce servers, more seats, servers and maybe other products and then more seats. But at some point, I mean it really is a platform solution that we are deploying across an organization. And so I'm not sure that that would -- it certainly wouldn't send you any different trend than you're seeing in our net expansion of 132%.
And in the end, our largest deployments are really about how do we enable as many individuals within the organization as possible. And net expansion ultimately is providing you the dollar capture, which is something I think we all want you to focus on.
Remember, in terms of designer seats, we're still in the 1% penetration rate of even the G2K seats that exist out there. So I think there's a long time before you will see any degradation in seat activity that would support our net expansion numbers.
Well, it's great that you mentioned that. Maybe you can double click on that a little bit, Dean, because not that I want to need to take but you had a great quarter. But you know the number of customer net additions is down quite nicely, actually on a year-over-year basis and your sales force is getting bigger and bigger. So I'm just kind of wondering is the focus shifting more towards expansion activity with your existing base. Should we not assume that customer additions grown year-over-year going forward right or perhaps flatten and/or the main focus is going to be more on expansions?
No, I think we've actually reported in prior quarters that when we started this land and expand model all the way back to Q1 of 2014, it would take us quite some time to understand the S-curves, the expansion capabilities of customers. And we're actually very happy with our net new customer adds, because they're actually the right customers. And you can see that as evidenced by the fact that we hit 132 net expansion numbers once again.
So we're comfortable with it, but I think we have a very healthy dose of both folks focused on landing new accounts in the accounts that have that expansion opportunity and healthy dose of new bag carriers and quota carriers who are prosecuting those expands around the world.
Just to nail that point. We've been talking for the last four or five quarters about the notion that we continue to focus on a better higher quality land. And if you look at over that period of time that we've had that conversation, we've seen consistent net expansion through that period, which I think is validation to the point that we're doing a better job at landing higher quality better logos today than what we may have two years ago.
And we have 66% of the G2K development.
And maybe lastly on the international front, not that 48% is a bad number. But that revenue base over there is clearly much smaller than the U.S. and not growing as fast as the U.S. Is there anything that's handicapping growth? Is there something unique to the international properties one make them grow as fast if not fast then just given your size relative to the U.S.?
No, I actually think that it's just the maturity and when we entered these markets, more than anything else. So we don't go into much detail other than international in general. But all the markets did well. Again, the customer focused on automation, convergence, community, aren't really any different around the world. The teams are newer in some of the markets and that might have an impact on things. But also to say that we actually did quite well in North America.
Thank you. Our next question today is coming from Mike Turits from Raymond James. Your line is now live.
I wondered if you could talk about the data science, AIML space a little bit. Obviously, you've made the Feature Labs acquisition. How is that Promote doing? And how do you see that space strategically? What are the functional areas that you feel like you want to be in and need to be in, and which ones do you not need to be in?
Well, we believe that every functional area is going to have a need for machine learning outcomes. I think it actually plays to our strength of having an end-to-end horizontal platform that can prosecute most any challenge that the business has. I think we reported 19 different industries showing up at Inspire Europe 11 functional areas. And the same platform is used, everything from hedge fuel, to doing predicting patient re-entry into emergency rooms, to helping the fastest UK e-commerce company see success.
And so we believe that everyone has a need for automating complex analytic tasks. A lot of its predicated though on their success, whether or not we're dealing with citizen scientists who need to be assisted in their machine learning work, or their model building work. And we have plans of course to do that at the conference we talked about our assisted modeling effort to help amp up the skills of the scientists of the citizen scientists who can now build models just needs to know what features to include, what model to choose and have a decision off of it. And the scientists are really trying to work on edge cases.
So our acquisition of Feature Labs allows them to leverage Open Source technologies but ideally, at some point in time in the future via a platform like ours, because the Chief Data Officers don't want a whole bunch of platforms, they want one platform to cover off on both personas as they -- I think they're all beginning to realize the convergence that we've been talking about for quite some time is in fact real.
And Kevin, we know where you're going long term in terms of your targets for margins, and it's really too much to talk about '20 at this point. But this has been an acceleration year in OpEx growth. Should we begin to think about next year as more of a leverage year? And if not, if it's more based around investment, what are those investment priorities?
Michael, I think it's a little bit too early to talk about 2020. We haven't introduced any guidance there yet. As you said, I mean, we do have a long-term model out there that we presented to investors back in June, and so that is what it is. But I think it's a bit too early to talk about 2020.
And anything in terms of priority without talking about numbers. Is it more on go-to-market? Is it more on R&D at this point?
Yes, I wouldn't signal there is any fundamental change in priorities. I mean, we continue certainly with the continued strength we've seen this year, from a go-to-market perspective, we continue to have focus on go-to-market and I think second to that would be product.
Thank you. Our next question today is coming from Rishi Jaluria from D.A. Davidson. Your line is now live.
Dean, I wanted to start by asking about the momentum you're seeing on the G2K side. Maybe help us understand, as you've been growing your G2K presence over time. Any color you can provide us in terms of where you're landing in terms of department, or what type of users? And then maybe how the size of the lands has trended overtime? And then I've got a follow-up.
Well, our playbook for landing new accounts really isn't any different, whether it's a commercial account, a mid-market account, an enterprise account or a G2K. Our playbook has worked. We know it works. We continue to refine it every quarter and we leverage Alteryx to understand the metrics of our business. So I guess the first point is we don't see big changes in our land efforts, we approach the markets as pretty much the same way.
The expansions are happening for sure as evidenced, again, by our net expansion number of 132. I think what's happening is that we become a known platform, people have gotten tremendous value. The lands that we're seeing tend to be in, I think, the sweet spot of large global enterprises. A lot of our partnerships tend to work with the C-suites, particularly the Office of Finance. And if you're going to land in any enterprise, the place to probably land is where people understand the ROI of software technologies that they acquire.
And so the CFO's office is a place where we're landing quite often. And I think they're freeing up budget for organizations under their umbrella to spend money on analytics, because they get the benefit.
And then just in terms of verticals. Any color in terms of how sale in public sector did in the quarter. And if there were any other particular verticals that you'd call on have been particularly strong? And I think you pointed out financing was in fact last quarter that you saw. Thanks.
This is Scott. So last year, we started a healthcare vertical and we've been very pleased with the results so far. And we've continued to expand our public sector vertical, both in the UK and in the U.S., and we're quite pleased with the direction of the business in that segment as well. When you talk about buying centers, as Dean just mentioned, offices of the CFO has been really strong. But quite frankly, we're seeing use cases apply throughout all buying centers within organizations.
I think the other follow up to Dean's comment around landing in Global 2000s is, we're engaged more often with CDOs in Global 2000s. And the conversation, even if the land is more strategic, which sets both us and our customers for more strategic expand, which is obviously key to the way our model works.
Thank you. Our next question is coming from Jack Andrews from Needham and Company. Your line is now live.
I want to ask I guess a two part question on the partnership side. Could you give an update in terms of any partnerships, for example, like Thomson Reuters that might be impacting your results in the near term? And then the follow up would be just how do we think about more broadly the potential demand generation from these partnerships. Should we think of it as a similar cadence of land and expand? Or do you think that the development of these partnerships may have a different impact on your business?
Well, remember, we have three kinds of partners in general terms. We have resellers that I think we've reported before roughly 20% of our revenues coming from resellers around the world. In total, we have about 300 partners of various definitions. We have strategic tech alliances, folks like the Snowflake's and the Tableau's, and the Microsoft's of the world. And while they're great partnerships, it's more in market co-selling with customers that are jointly looking for products.
The area where there is the most influence, it tends to be the global analyst consultant and the big six accounting firms. They're actually helping carry a lot of the messaging to the C-suite, both CDOs, CFOs, CEOs, who are acutely aware of the necessity to have a digital transformation effort. And so their global expanse has been very helpful in helping us land many of the G2Ks. So we're going to continue to leverage these strong partnerships, where there is no margin shift, going forward.
Just to talk about the Thomson Reuters' partnerships; relatively new still; we do see pipeline building; they're very excited; and there is a number of joint events that either have been held or will be held going forward. And so we're pretty excited about all of our partners who also have gone through digital transformation of their own. Most of these folks are customers first and then take us to market, because they provide services that we don't.
Thank you [Operator Instructions]. Our next question is coming Taz Koujalgi from Guggenheim Partners. Your line is now live.
Kevin, you said that the contract duration went up slightly I guess for bookings. But can you comment on what the plan was for invoicing duration? Have you saw any change in the inversing duration in Q3 versus Q3 of last year?
We always book one year in advance -- invoice one year in advance, excuse me.
Thank you. Our next question is coming from Steve Koenig from Wedbush Securities. Your line is now live.
So I'm wondering about machine learning here and the market for machine learning. And as we look at it and talk to industry participants in the space, we hear that -- we hear about people moving from SAS or SPSS to the Python in our world. We also hear about several vendors competing based on auto in our system now and including Alteryx breaking new ground here. And lastly, we were hearing more and more from some of the innovators here in the space, including you guys, about the challenge of getting models into production and how this helping customers deploy those models will increasingly become the high ground in the platform competition. So I'm wondering, can you compare and contrast maybe the importance of those functionalities in kind of the new Python in our world versus the old SAS world, and what's changing as data volumes grow?
Well, I think the data volumes aside and where the data volumes reside I think it's perhaps a different kind of a question. But in terms of the players in the space, it's a very crowded space, because everyone I think sees that machine learning is going to eat the world. We just believe that it won't until you amplify the human in the mix. And that's why this convergence between the citizen scientists who doesn't know how to write R in Python, at least not much, needs to be working on the same platform as the trained statisticians who love to write R in Python. And so we see a collaborative effort between these two personas.
And until you have a platform like ours, there's going to be a disparate mix of tools and technologies that enterprises will have to use if they're going to actually seek out the $10 trillion to $15 trillion of value that's locked up in data wherever that data might be locked up in. So our belief is that that R in Python clearly have a play but not just for the scientists. We want to be able to share automated feature engineering sets with the citizen scientists, so they can actually get the outcomes sooner.
We also believe that not all models have to be deployed. But we want to make sure that the models that the scientist do create that do need to get deployed have an easy path to deploy them. It is a very noisy crowded space and I think you're going to see -- we see great technologies out there today, but they only cover off on a sliver of the activity that enterprises actually need. And unless you're part of an end-to-end platform like ours, you probably go to the wayside.
Thank you. Our next question is coming from Chris Merwin from Goldman Sachs. Your line is now live.
I guess, maybe keeping on this theme. Have you seen any shift in budgets from customers who are traditionally have been spending on analytics more for the IT department shifting that budget towards self service, or just more a function of actually growing the TAM by expanding the number of citizen data scientists? Just curious what you're hearing from customers and CIOs in particular? Thanks.
Well, that's a good question. We've long said that the audience for self service data science and analytics was going to be won by us in the line of business it's a $15 billion space. The winner of that space will be the natural beneficiary of the $28 billion share shift of all that technology that has historically sat in IT. We are beginning to see that shift.
It's important though that we're focused on the G2K and having CDOs or proxies for CDOs in the mix, because they are the ones who are going to drive that shift from systems of record deep in IT to systems of engagement out in the line of business. But we are beginning to see the early stages of that.
Thank you. Our next question is coming from Brad Sills from Bank of America Merrill Lynch. Your line is now live.
I wanted to ask about Connect and Promote, how did those two trend during the quarter, any traction there?
Well, the conversations we're having around the end caps has definitely accelerated as a direct result of the continued debt expansion numbers that we see. What happens in these large global enterprises, they -- I think Kevin mentioned earlier, we land with a couple of seats. They buy a bunch more. If a CDO is in the mix, they buy hundreds more or thousands more. And they're beginning to recognize the need to harvest the assets that are being produced by these analysts now.
So we do have a number of implementations on very, very large complex data sets around the world. The conversations are happening more and more, people who have Promote are acknowledging that we've reduced the time it takes to actually deploy machine learning algorithms for operational systems. So we're actually pretty excited about where the conversations have led. And I think over the long haul, you'll see them being -- become a critical part of our platform.
Thank you. Our next question is coming from Mark Murphy from JPMorgan. Your line is now live.
I noticed that contract assets grew by about $12 million sequentially. Presumably that flows into revenue. I guess, I'm curious how much of that was the anticipated or anticipatable? And then as well the kind of one question in two parts, the RPO growth 13% sequentially, I'm just -- I guess I'm wondering if you look at that as a decent proxy for the backlog trend, or -- was that somehow impacted by the duration changes? I think you said the duration increased, but it's still two years. And I'm just wondering if you can put a finer point on that.
The contract asset is and in the same token that the deferred revenue. I mean, those two are purely a function of timing of contract bookings, revenue recognition and invoicing. So those can fluctuate period-to-period as a result. With respect to the RPO, we do disclose the full remaining obligation. So that is in effect the backlog that we have going forward.
Thank you. Our next question is coming from Yun Kim from Rosenblatt Security. Your line is now live.
Can you just talk about trends around large deals, especially those above 250k, and any seven figure deals? For instance, how much of your 250k plus deals and million dollar plus deals represent your total revenue mix and how that has been trending? Any color around that will be helpful. And then also maybe how your go-to-market and sales process is changing, or your large deal activities increasing and we need to focus on the G2K? Thanks.
Well, let me just comment that we did have 92% growth in those large expands or 250. We don't talk about their contribution to overall revenue, but we call this out for a reason. The large organizations that we're dealing with, particularly but not exclusively in the G2K are recognizing that we have become an enterprise standard in their enterprises. And many of these customers are going from tens of seats to thousands of seats in their build out of our platform.
I'll let Scott talk about the sales notions around it. Again, I don't think we have much difference in what we've been doing. I think we've just been doing it better in every theater around the world.
Yes, thanks Steve. Yes, no real change to our playbooks. We continue to run the land and expand motion with our customers. And as Dean noted, I think we're executing really well across the board across all of our regions, and across the size of the companies that we're working with. So we haven't had to retool the sales team, or really adjust our playbooks in any way.
Thank you. We've reached the end of our question-and-answer session. I'd like to turn the floor back over to management for any further or closing comments.
Thank you. Before closing the call, let me take the opportunity to thank our customers for their continued business. Here at Alteryx, customer trust defines the integrity of our business, and we thank you for trusting us with helping you drive value in your business. I also want to thank the more than 300 partners and more than 1,100 Associates around the world helping to ensure our customers key success with our platform. Thanks again to everyone for joining us today. We look forward to updating you on our progress next quarter. Take care.
Thank you. That does conclude today's teleconference. You may disconnect your line at this time, and have a wonderful day. We thank you for your participation today.