Hello, everyone. Thank you for joining us today, and welcome to the 2022 Alteryx Investor Session. My name is Ryan Goodman. I'm the Head of Investor Relations. Before we begin the presentations, I do have some housekeeping. We will be making forward-looking statements today in the program in regard to our Alteryx's business, financial expectations and other future events. I'd like to refer you to the SEC filings and our safe harbor statement for a description of our business and the risks and other important factors that could cause actual results to differ materially from these forward-looking statements. We have a fantastic lineup today. We'll begin with a company and market update with our Chief Executive Officer, Mark Anderson. As we're taking the utmost care with our COVID policy, Mark's presentation today will be shared on video. Next, Paula Hansen, our President and Chief Revenue Officer, will provide an update on the go-to-market strategy. We have Suresh Vittal, our Chief Product Officer, who will give a product overview and then a discussion on the innovation strategy. We'll wrap up with Kevin Rubin, our Chief Financial Officer, who will provide an update on the financial drivers. After the presentations, there will be a Q&A session with the executive team. For those of you who will be joining us in person here today, we will have a customer panel, an interactive customer panel that will be moderated by our Chief Advocacy Officer and our Co-founder, Olivia Duane Adams. With that, it is my pleasure to welcome our Chief Executive Officer, Mark Anderson. Thank you all for joining us here today. Those of you here in Denver, it's so good to be back in person, and thanks to those of you that are joining us remotely. If you're seeing this on video, unfortunately, I got busted by the COVID police and couldn't make it in person. My name is Mark Anderson, I'm the CEO of Alteryx, and it's my pleasure to offer this audience updates on our strategic roadmap and talk about how Alteryx will win in the data and analytics space. Before I jump in, I'm eager to share that a lot has changed since our last in-person Investor Day three years ago. This is my first Investor Day in person as CEO, and I've imposed a lot of change on the team that I inherited. We have an up-leveled executive bench with well-tenured leaders who bring relevant stage experience, and we've added well over 1,600 exceptional employees across the company, including cloud experts from three acquisitions last year. We're attracting people with, on average, over 15 years of experience, with most coming from billion-dollar or greater companies. We've made exceptional progress as a company, and I'm thrilled at where we are and where we're going. Yes, in many ways, we're still the same Alteryx that our customers have always loved. Our designer platform has never been stronger, and we continue to serve our core customer base with our best-in-class solutions. Under the product leadership of our CPO, Suresh Vittal, we've introduced an end-to-end cloud-based platform of offerings that enables us to empower new personas and a multitude of use cases. Over my 30+ years in IT, I've seen how platforms win. They won in mainframes, operating systems, networking, public cloud and security. We are confident that platforms will win in our very complex marketplace. Under the sales leadership of our President and CRO, Paula Hansen, we've upleveled our go-to-market motion with greater focus on enterprise and global scale. With these strategic initiatives well underway, the company is executing at a high level, as evidenced by our strong finish to last fiscal year, as well as our Q1 results announced earlier this month. I am so proud of what we've accomplished and so excited at the massive opportunity ahead as the need for democratization of data is higher than ever before. Digital transformation has become more urgent than ever in the post-pandemic world. Consistently, enterprise and government leaders from whom I hear tell me it's a number one or number two priority. Companies need to be more nimble and agile to win in their respective markets, and that requires fully embracing data analytics. In order to transform, businesses must upskill their knowledge workers. As such, we are witnessing a massive uptick by businesses to invest in analytic platforms that allow them to harness their vast amounts of data. In fact, a few weeks ago, I had the privilege of meeting with the number two official at the Department of Defense, Deputy Secretary Kathleen Hicks. What I learned from Dr. Hicks was that while DoD is leaning into investments in technology, AI, and analytics, they're keeping humans at the center of their strategy by prioritizing the upskilling and reskilling of their existing workforce. Based on recent data conducted in January of this year by IDC, we know that 88% of organizations face data analytics and technology constraints. 95% of organizations report being challenged by data in creating analytic outcomes, and 90% of organizations use multiple tools in data and analytics activities. No wonder we continue to see companies that are hungry for ways to harness data to make better decisions and improve their competitive advantage. These realities signal that our mission statement is more relevant than ever, to enable every person to transform data into a breakthrough. We know that upwards of 78 million data workers are advanced spreadsheet users, and this number has gone up 15% in just the last two years alone. Folks, we all know that this time on spreadsheets has its challenges. IDC cites that data workers lose 800 hours annually. That's annually. With 78 million data workers, that means that there are more than 60 billion hours wasted on a global scale due to redundant tasks and inefficiencies. Despite the innovations across the stack, ingestion, visualization, AI, ML, significant time is still wasted on manual tasks. What we hear from business and government leaders is that while early in their journey to digitize and become data-centric organizations, they are keen to make the investments. Some struggle with where those investments should go with a host of commercial tools in use. The analytics market is highly fragmented, and companies often find themselves acquiring multiple tools from multiple vendors for a single task. Vendor fatigue is high. In fact, a recent IDC study found that over 50% of those IT leaders polled use over four commercial data or analytic software tools for each activity. In addition, there are added complexities in the form of disparate data types, multiple data lakes, implementation of hybrid stacks across cloud and on-prem with firewalls. As enterprise digitization tailwinds continue to rise, incremental demand for data analytics with new personas amplify that challenge exponentially. These challenges create a massive market opportunity for Alteryx. First, there is the tangible $65 billion spent annually on large, disparate, siloed tools. This spend alone is expected to grow north of $110 billion by 2025 and is ripe for disruption with more modern, comprehensive solutions. Secondly, there are nearly 80 million spreadsheet users that may not even be using analytic tools that are very much in need of data analytics solutions. Finally, new personas are emerging every day as enterprise organizations continue on their digital transformation journeys. As a company, we are exceptionally well-positioned to address this growing TAM with our evolving product portfolio. Number one, we're the well-established leader in data analytics with our flagship designer desktop. Time and again, our customers leverage our solutions to optimize multi-hour, if not multi-day workflows to a matter of minutes. Number two, we're building a unified end-to-end analytics platform, a one-stop shop. Number three, our UI is unrivaled. It's easy to use, low code, no code, and that allows customers to democratize analytics across a broad range of personas. We will meet demand for a platform that brings it all together, both in the cloud and on-prem. As this generational shift towards data literacy evolves, customers will look to accelerate their data analytics journey, and it must apply to a broad range of knowledge workers. I submit that there will be independent companies across this ecosystem that will emerge as platform leaders. Today, you will hear more about how we plan to seize this meteoric opportunity to be one of those winners. Since we connected last May, we've taken bold steps to broaden our platform offering. This includes a doubling down on our innovation efforts led by Suresh's team, implementation of a world-class go-to-market motion led by Paula, and an investment in our people and teams as our customer personas have shifted, so has our talent profile. We're benefiting from a virtuous cycle of high-quality team expansion with employee retention rates at the highest level in well over a year. We also welcomed over 200 employees from Trifacta, whose deep industry skills continue to strengthen our cloud capabilities. On the sales front, we're attracting many well-tenured sales reps with a wealth of experience coming from Fortune 500 and multi-billion dollar software companies. I'm also incredibly pleased with our progress on our CSR efforts, which Paula will share more on shortly. We are uniquely positioned to meet this growing TAM with our trifecta, our strategic sales motion, innovative products and solutions, and our teams. To expand on these elements, our President and CRO, Paula Hansen, will provide all of you with an update on why our customers are increasingly choosing Alteryx. She will offer updates and a roadmap on a refreshed go-to-market strategy that she launched in 2021, which has already enabled us to address enterprise data analytics needs more broadly. This is evidenced by our continued acceleration in ARR from customers contributing greater than $100,000. With a record Q1 in terms of million-dollar ACV deals, more than double year-over-year. She'll also talk about her plan for continued growth across the G2K. On our Q1 earnings call, we noted that nearly half of the Global 2000 is an Alteryx customer. This is hugely beneficial to the company, given their 128% net retention rate. She'll also talk about how she's working with an expanded ecosystem of partners to scale both our go-to-market reach and our customer success efforts, and why cloud matters now, and how we will continue to leverage access to our cloud products. Our Chief Product Officer, Suresh Vittal, will provide this group the ability to see a few demos of the expanded platform, Designer, Auto Insights, and End-to-End. He'll really go a layer deeper on the technology to help you appreciate how differentiated our platform really is. He'll also cover where Alteryx fits into the modern data analytics stack, how cloud streamlines data analytics adoption for our customers, and effectively expands our reach to new personas and new use cases. At Alteryx, we believe it ties back to empowering our customers and changing lives. I'm sharing this outstanding customer quote, which says so much. "We all wonder what we want to do when we grow up. Alteryx not only showed me, but taught me to be what I was meant to be." That's what it's all about, folks, enabling our customers to be what they were meant to be. Thank you so much for allowing me this time to set the stage for today's investor update. I'm so proud of the results that we've achieved over the last year, and I'm extremely grateful to our customers, our partners, and our internal teams for their ongoing vote of confidence. We have a vibrant community of over 300,000 Alteryx zealots who continue to champion our mission. With that, I'll hand it over to our own GTM powerhouse, President and CRO, Paula Hansen. Good afternoon. So excited to be here. Welcome to those of you that are here in the room, and also welcome to those of you who are joining us via the live stream. So many things, so many exciting things to share with you today, and over the course of these next couple of days, which I hope you have the opportunity to spend some time with us during our Inspire event. Well, we've all been through a lot over the last couple of years. The global pandemic has changed the competitive landscape forever. As we talk to customers, we realize, and they realize, that to be able to meet the redefined customer expectations that the pandemic has introduced, to be able to identify how they're going to differentiate within their competitive landscape, they need to do digital transformation. That is what's going to separate them from the rest of the competitors in their industry. If you want to accelerate top-line revenue growth, if you want to efficiently manage bottom-line costs, the only way to do it is to unlock the potential of your data and turn that into insights. Businesses have realized this more and more over the last couple of years, haven't they? We talk to customers, and they all wanna be data-driven enterprises. They've been trying to be data-driven enterprises for a couple of decades, and yet they haven't realized the vision yet. Because most of them chose to go down a path of investing in technology for a small set of experts, build a data science team, and they'll solve all the problems. Yet, all the problems haven't been solved because the dataset is huge, the landscape is moving so quickly, and more and more people need to participate in the data-driven enterprise. That's the opportunity that we see at Alteryx. That's the long runway of opportunity that we intend to lead, and I'm gonna share with you a little bit about the go-to-market strategy to do just that. The International Institute of Analytics, or the IIA, has developed a five-stage maturity model for analytics maturity. They surveyed thousands of organizations and found that most organizations, those data-driven enterprises, are at a 2.2 on the five-point scale. They're still dealing with localized analytics and reporting. They have this great data science team, but the rest of the organization isn't equipped, isn't up-skilled to participate in the analytics opportunity to become a data-driven enterprise. What's more, studies show that as organizations move up this maturity curve, their business performance improves as well. Higher growth, better profitability, and better shareholder value generation, which all of us in this room care about. Simply put, those companies that invest in analytics are going to win. This, for us at Alteryx, means a great opportunity ahead. Now, as we talk to the leaders of analytics in the enterprise, the customers that are furthest along on the maturity curve, they've taken a new approach. They realize that they need to democratize the analytics capability across a broad base of their employees. That is our mission here at Alteryx. That's why you'll see the theme for the next couple of days is analytics for all. This is our differentiation. This is what we enable for our customers, and this is how we're going to help upskill and solve the world's most complex business problems and close the gap to being a data-driven organization. We simplify our differentiation down to four E's, easy, everything, everywhere, and everyone. Easy is what we've been known for since our inception. We are such an easy-to-use user interface, drag and drop, low-code/no-code platform. We can take virtually any task and turn it into minutes or hours instead of days or weeks. The everything means that we deliver across the entire analytics life cycle, from data to insight to action, across every data source and every data type. Everywhere means that's where our customers are, that's where we need to be. From legacy on-prem databases and applications to modern cloud data warehouses to every type of cloud platform, and most likely, a hybrid version of all of that. We operate in those environments alongside our customers. Every one is the all. Every industry benefits from our technology. Every department in the enterprise has use cases for our technology, and we are here to deliver to all users of all skill sets to participate in that democratization of analytics. It turns out this is resonating in the marketplace with our customer base. This is our Global 2000 customer base today, which we're very proud of and very focused on. What you'll see here is that it is every industry that you can think of, it is every department inside of those industries, and we're enjoying great growth with these customers. As Mark mentioned, we now today have 45% of the Global 2000. That's up 6% from Q1 of 2021. We've confirmed product market fit. We're focused on this particular part of the market. Why? Because it's where the highest TAM is. It's where the most amount of data is swirling around the enterprise, where the complexity exists with organizations that need to continue to differentiate in their industries. They have an appetite for our innovation, and the results show it. We have the highest, higher net expansion in the Global 2000 at 128% versus the 119% net expansion we have across the entire customer base that we serve. Once again, I'll say we have a long runway of opportunity ahead. Now let's shift to what the strategy is that we have to serve this market. It's a three-pillar go-to-market strategy that we put in place at the beginning of 2021. It will continue to be our strategy for 2022, and I would submit to you for the foreseeable future. The three pillars are focusing on the enterprise segment, winning with partners, and investing with customer success. What does this mean? Well, from a go-to-market perspective, the enterprise segment, as I already mentioned, has the TAM. We've built now a diversified, multidimensional strategy to serving this segment with aligned sales plays, marketing plays, and customer success deliverables. We address a wide range of personas across the enterprise, and Suresh and team have built out a wide platform portfolio to marry up to those personas. From a partner perspective, we are very invested in our thriving ecosystem. They will help us to efficiently scale our business to new markets, new logos, and new buying centers inside of our existing customer base. I'll talk a little bit about what we're doing there in a minute. The third part of the strategy, customer success. You can't expect a customer to continue to invest with you if they haven't yet realized the value of the solution that they've started their investments with. The good news for us at Alteryx, our product has a quick time to value, it has a high NPS, it's very, very sticky. When we just apply the right customer success model to that with our customers, we're able to build repeatable processes. We're able to help them mature on the analytics curve, and in so doing, grow our business with them. Now I'll just double-click a little bit on each one of these pillars. In the enterprise space, we built our business over the last two decades, focusing on the lines of business. We would find the business analysts, the knowledge workers, the data workers that were spending 60%-70% of their time with data and very quickly demonstrate our value to them. They would adopt our technology, and it would go viral across the organization. That land-and-expand motion is still very, very relevant and helps us build out demand across multiple departments within the enterprise. More and more, as we talk to customers, they're realizing that they need to have an enterprise platform, that they need to democratize the capability broadly across the enterprise, inclusive of that centralized data science team that might exist over in IT. We've built sales motions to be able to have all of those conversations from the CIO and chief data officer, where the democratization of analytics really resonates through a wide variety of personas. Of course, our Designer and Server products continue to resonate with the business analyst and the heads of line of business departments. We'll continue those conversations. Now with the acquisition of Trifacta, it opens up a whole new persona for my team to talk to, the data engineer in IT and the CIO who are dealing with large datasets on their journey to cloud. With our acquisition of Hyper Anna and our Auto Insights product, that's a whole new persona for us to talk to, the business owner, often the executive team within our customers who are staring at dashboards and still don't have the answers to their most important questions because data is real time. It's living, breathing, and changing, and they wanna be able to get easy understanding and insights of not just what's happening in their business, but why it's happening and what the next action is that they should take. With the release of our Alteryx Machine Learning, we continue to have discussions with our business analysts to get them more into the machine learning opportunity. It gives us a chance to go have conversations with the data science team as well. Now that we have this platform, and we can address multitude of personas, it aligns very, very nicely with our go-to-market strategy. We've also talked a few times during earnings calls and in various meetings that we've had that our enterprise license agreement is our vehicle for growth in the enterprise segment. This resonates with enterprise customers that are familiar with the construct. What they love about it is its predictable pricing. It gives them access to a broader set of our portfolio, and it eases their expansion because we give them burst capacity to be able to move and grow with us, in a more easy way. We're really pleased with the results of our ELA, only really introduced in Q3 of last year. We're pleased with it not just because of the ability to sell them and the outcomes that we've had from a deal size perspective, but we're pleased with what the customers are seeing and what we're seeing after the sale. Now, a couple of quarters post-sale, we're seeing high utilization of our software. We're seeing they are turning on these other products that they now have access to. In a third of the cases, they're already leveraging that burst capacity to expand with us, which means my team has an opportunity to go back to them and move them up to the next tier of the ELA even before their renewal comes. We're really continuing to double down on the ELA, and we'll be announcing in June our cloud ELA to stack on top of our existing ELA because we know this is the right vehicle for our enterprise segment. When you net this whole strategy out, what does it mean? It means that I believe we'll continue to see strong and improving sales productivity, and more importantly, continued ARR growth. Now let's talk about the second pillar of winning with our partners. We've had a thriving ecosystem for a couple of decades, and we continue to invest in this and look at where they can help us to efficiently break into new markets, break into new logos, or help introduce us to new buying centers within our existing customer base. What's new, though, is that we've been really intentional, just like every other part of our go-to-market strategy, to build more discipline into the way that we work with our partners. We relaunched our partner program on April 1st, and the design of this has a couple of aspects to it. One, to recognize not all partners are the same. There are different categories of partners, and the way you drive behavior and incent growth from your partner community has to change with the different types of the partner. We also realized we needed to be much more clear with our partners on our expectations, that they would yield certain benefits from us once they accomplish certain goals that we had for them. We're really excited about the launch of this program, and the feedback has been positive. We have an incredible representation of partners here this week at Inspire. Again, encourage you to have conversations there. I'll just give you a couple of quick examples to maybe clarify the differences of these partners, right? First we have solution providers. These are the partners that help our customers onboard new users, dream up new use cases, implement our technology. You see the names of some of those there, Data Meaning, Capitalize, Keyrus, all have been with us for a couple of decades. Our global system integrators operate at a completely different part of the market and customer. They have C-suite relationships. They're having discussions with customers about big digital transformation objectives. Of course, these are the PwC, KPMG, HCLs of the world. This maps very nicely to our executive conversation of democratizing analytics. We can go in with PwC and talk about tax automation at a very strategic level. We can go in with HCL and talk about supply chain reinvention at a very strategic level. Different conversations, obviously, than the solution providers. We have our technology partners, our ISVs, where Suresh and team have built innovative hooks and integrations into other players in the data landscape to drive value for our customers. Snowflake is a great example. We have the analytic pushdown capability into their cloud data warehouse. We wanna take analytics to where the data exists and resides and is moving, and this is a great partnership that is unlocking value for both of us with our customers. UiPath and a number of the other RPA bot providers, they go find data in really hard places to find in the enterprise to bring that into our platform to be a part of the analytic opportunity. This is an exciting part of the partner portfolio. Lastly, OEMs, which is probably a little bit of a newer pillar of our partner strategy, but I envision it growing quite rapidly as we go forward. Thomson Reuters is a great example here, where they take their ONESOURCE tax software and wrap it around our Alteryx platform and provide that to their customers for tax automation, unlocking quite a bit of opportunity in the marketplace. We're really pleased with the results of this investment as well as redesign of our partner program. In Q1 this year, we saw significant growth in our partner-attached business as compared to just a year ago, and we're just getting started here. The third pillar is customer success. As I said, you have to partner closely with your customer, make sure they realize the value of any investment they make so that you can ask permission, or rather they come to you and say, "I'm ready to expand. I'm ready to buy new products. I'm ready to grow with you, Alteryx." What we've done here is build methodology into our process to helping our customers through this journey, this analytics journey that they go through, that we've learned about over a couple of decades. We've seen thousands of customers mature up that curve that I talked to y,u about. Now we take those best practices, that guidance, and we provide customer success, repeatable methodologies to our customers, and our partners do as well. This helps them to more easily onboard people onto our platform, adopt our technology, and ultimately expand and grow with us. We've instrumented this team with the technology that helps them really have insight into what's happening in our customer's environment, so we can be that good business partner. We understand how they're utilizing our software. We apply health scores to how they're using our software, so we can benchmark them against best practices, make recommendations, really help facilitate that move of maturity. We have triggers that tell us, "Okay, maybe this customer could be at risk of churn, so let's respond to that." Or triggers that say, "This customer's really moving quickly. The sales team should go in and propose another product or propose an ELA to facilitate faster growth. This repeatability is generating higher net expansion with customers that have customer success and higher renewal rates. To be clear, this is a for-fee capability that our customers pay for. They can either buy it a la carte, or we bundle it into our ELAs as well because that facilitates the adoption. Now what's even more exciting, because this is a human capital investment, and Matthew Stauble here, our Chief Customer Officer runs this organization. These customer success managers and human capital that we've built up over the last year and a half, now we've taken that capability and built it into a digital capability so that we can take this downmarket across the entire customer base that we serve, because we have no intention of building a customer success team large enough to serve all of them, but we want all customers to understand these best practices, to understand how to mature on their analytics journey in a very repeatable way that we know works. We're really excited about this as a pillar of our growth strategy. I feel like nothing really cements this strategy better than sharing a customer story. I thought I'd share with you Phillips 66, who we all know as a global energy leader in the Global 2000. They've been a customer of ours for a number of years and have used our software across a number of different departments, including finance, supply chain, legal, engineering, and operations. Last year, we decided to get far more strategic with this customer, and we decided to be provocative and put a proposal in front of them about how they could more quickly mature on their analytics journey. We partnered up with PwC and married up our strategies and put in front of Phillips 66 a proposal for an ELA as well as customer success that they also agree was the right thing for them to do based on where they were with Alteryx and the transformation that they wanted to drive. The outcome, it's still pretty early days 'cause this is the second half engagement with them, but they've estimated they saved 800 hours of productivity, that they've realized over $100 million in benefits, and there's been some really core use cases that they've seen very quick returns on, whether it's helping them optimize their buyback pricing, reduce spending too much in their operational technology departments, or just driving better efficiencies. We're only getting started with Phillips 66. There's plenty of growth opportunities still there, and yet there's many Phillips 66 customers out in the wild as well. We know that this three-pillar strategy of enterprise, partners, and customer success wins and drives growth. Now I'm gonna shift gears a little bit. I've been talking about the go-to-market strategy, and Suresh is about ready to share with you our product strategy. While we're building those strategies and executing in the market with our customers, we also wanna make sure we're doing it the right way. We have really doubled our focus in ESG, and I thought I'd share with you the initiatives that we have ongoing here. Last year in 2021, we engaged with qb.consulting, which is a woman-founded and woman-led consulting business who focuses in the area of guiding enterprises in their ESG initiatives. Now we have a couple of great initiatives underway to share with you in 2022. We have our first energy and greenhouse gases inventory initiative launched, and that's going to culminate in our inaugural global impact report that we'll be releasing here within the next 12 months. Additionally, last month in April, we opened our global headquarters in Irvine, which I encourage you to come visit if you have an opportunity. It's not only a beautiful facility, but it's also gold-certified LEED. We're very excited about that. Libby, who is here as our Co-founder and Chief Advocacy Officer, leads our Sparked initiative, which many of you are probably familiar with. This is our commitment to developing the next generation of analytics leaders by donating software and curriculum to colleges and universities globally to help them upskill students, so as they move into the workforce, they can be incredibly impactful to their organizations. Just since May, we've donated over 130,000 licenses to 800 colleges and universities across 45 countries. I know Libby and her team are just getting started here, so we can't wait to see the long-term impact that we can have on society and in business here. If you wanna learn more about what we're doing in ESG more broadly, I encourage you to review our recently released proxy statement. With that, I'm now going to ask up to the stage my partner in crime, Suresh Vittal, our Chief Product Officer, who I couldn't be more pleased to work alongside. Our customers expect that our product strategy and our go-to-market strategy are fully aligned. I can tell you right now, we are fully aligned on what we're doing together in support of this opportunity and in support of our customers. I couldn't be more excited about what he and his team are building. The interest is incredibly high with customers as I travel around and talk to them, and I'm thrilled to have the opportunity to invite him onto stage to share with you. Thank you. Hello, and welcome everybody. I'm Suresh Vittal, Chief Product Officer at Alteryx. I truly appreciate all of you being here with us in person and virtually. This is my first time being at an Inspire Investor Day in person, and I'm looking forward to connecting with all of you, or as many of you as I can, after the session's done. It's hard to believe it's been just about over a year since I joined Alteryx, and the transformation of the portfolio has been exhilarating to watch. Let me share with you a little bit about what's going on by the talented product and engineering teams that are working on our product portfolio every single day. We're deploying more products, more capabilities, more features than ever before, driving value for our community of users across the board. On average, we deliver 100 product features every year on top of our solutions, and a lot of these come directly from our informed community of users. If you've been through the Alteryx community, you see them sharing ideas and sharing product use cases, and those kind of emerge into the product over time. As you'll see over the next few days, this community of users, of data enthusiasts, are vocal and they're growing, and we want them to keep growing because our goal is to provide the most powerful solutions that enable people to extract actionable insights out of all of their data and drive breakthroughs. We're only just getting started with our product strategy. Since last year's Investor Day, a lot has changed politically, socially, environmentally, economically for our customers. More and more of our customers, like Alteryx, have tried to figure out ways to work, and adopted new processes. They've adopted hybrid work environments. They think about modernizing their ways in which they share data. And of course, they're creating new analytics automation and new ways in which they share insights across these organizations. What's undeniable with all of this change is that there's this underlying digital transformation that's happening for our customers, and now more than ever, they seek the clarity that only analytics can offer. Every time we talk to our customers, that question becomes clearer. They want to empower more and more users with analytics and with the insights which allows them to make more informed decisions. With these new changes and with companies adopting new processes, we've also seen them struggle to leverage all of this data, all of the diversity of data, all of the diversity of insights, the increase in data literacy inside their organizations. This challenge exacerbates with fragmentation that we see in the data every single day. We see the pull of data moving to the cloud. We see that getting stronger. Enterprises are adopting cloud warehouses or data lakes or data stores, and they're retrieving and working with increasingly large sets of data. It doesn't mean that they want. They also want cloud analytics solutions to go with that. What's clear is that this on-premise data isn't going away. Far from it, actually. In fact, when you look at a recent IDC study on some of the software implementations, over 50% of the data analytics solutions implemented have happened for on-premise data. A lot of the critical analytics and the insights that are happening continue to happen in data across the firewalls, and this will continue for many years to come. With this increase in enterprise digitization, we see a real need to empower every single individual and for organizations to tap into this information in far more meaningful ways than they do today. We hear from our customers they want these insights to happen at much faster speed and a much faster scale than we've seen to date. This means the way the challenges that they're faced with also are changing, right? They are looking at fragmentation of data. With every new enterprise SaaS application they adopt, it creates yet another data silo. They're working with hybrid and cloud environments that really make it complicated for them to integrate this data. They're working with a bevy of tools. New users introduce new tools, new use cases introduce new tools, and they're struggling with this voluminous data piles that these tools are creating. This has become an incredibly complex challenge for our customers to manage across the world, and that's what informs our product strategy. The four themes that I'm about to discuss with you are really aimed at addressing these challenges that our customers see day in, day out. Let's talk about these four themes a little bit and unpack them. Cloud centricity, big data fluency, AI as a strategic advantage, and persona expansion. Let me start a little with cloud centricity. This supports our goal of making it easy for data users to collaborate across personas, across roles, across organization lines. We actually go to where the data is today. To accelerate the investment in the cloud, we acquired three companies over the past 12 months, Trifacta, Lore IO, and Hyper Anna, which is now Alteryx Auto Insights. This allowed us to tap into new markets. This allowed us to help new use cases come to life, and this brought new users, which expands our TAM reach. If you think about the big data fluency, more and more our customers are overwhelmed with the amount of data that's coming at them, the variety and velocity of all of this data that's coming at them. This can be overwhelming, especially with the data that's growing in cloud-borne applications. They now need to master cloud warehouses. They need to look at cloud-borne SaaS applications, but they're working in a world of ubiquitous connectivity. Alteryx uniquely gives them the opportunity to work across all of this data. Regardless of the amount of wrangling and algorithms that they need to run to reshape this data and make it ready for analytics, Alteryx is the primary solution they use to drive these transformations. With our third pillar, excuse me, AI as a strategic advantage, we aim to embed intelligence into every decision that happens inside the organization. This happens in a few ways, right? We want everyday tasks that a user does to become easier for them by using data science and AI capabilities, but we also wanna make sure that AI doesn't become a nice to have. It's a must-have as companies compete in today's markets. Finally, for our fourth pillar, persona expansion. This is at the core of how we democratize analytics. Every single persona, whether it's a business analyst, a business owner who's not as skilled at the data, an IT analyst who's focused on the systems, or a data engineer who's building these complex data pipelines. We want to serve all of these users regardless of the skill sets that they have. By doing so, what we think this unlocks is shared learnings and allows employees to do their job better, and which in turn then boosts the company's data wealth and gives people confidence in the results and in some of the insights that are driving decision-making inside the organization. That's a lot of what our SaaS product strategy is focused on. Let's talk a little bit about our product roadmap and some of the recent innovations that we delivered and what's coming next. On Designer and Server, we focused on the user experience with enhancements to the interfaces, making it easier for our users and customers to become more productive from day one on the products. We're focusing on deep cloud-to-desktop integrations as well as broad governance capabilities. You'll see me talk about this a little more later. We reworked the entire server API fabric, and this was an important initiative for us because what it does, it allows the IT teams and organizations, the administrators in organizations to integrate Designer and Server into their enterprise technology stack. On our cloud offerings, we've hit a number of great milestones, including the launch of our cloud products earlier this year. We made deep integrations into Snowflake and Databricks. We've tightened integrations of Auto Insights with Designer and Server. We've introduced new connectivity features across all of our cloud offerings. Looking ahead, we're committed to continue to evolve our platform strategy with tightly woven integrations across all of our products that make it easy for our users to access functionality across these different offerings. Now I'd like to take a few minutes and talk to you about how all of this innovation positions Alteryx in the modern data and analytics stack. Ultimately, it really comes down to users creating insights out of all of this data, and that requires orchestration, it requires automation, and it requires access to these actionable insights. Clearly, data comes in various forms, right? There's spatial data, there's spreadsheets, there's local files, there's data coming from cloud applications as enterprises adopt these cloud strategies, and these continue to be fragmented. When you think about applications like Salesforce or Workday, these are applications that our customers work with every single day. Then cloud storage environments, right? Microsoft OneDrive, Google Drive, Dropbox, and so on. So not only you have the complexity of the data, but you also have complexity of location. The data's all there, and it's largely siloed, but because it lives in various places throughout the organizations, most firms think they need to have this to be centralized. We think this is an opportunity, but this isn't the only way forward. We see companies really expanding their data footprint with cloud storage. Many of our customers use Snowflake or Databricks. They work on AWS Redshift. They work on Azure Data Lake and Microsoft Azure Synapse. You can see this data footprint increasingly getting very complicated. If you imagine one department doing this, imagine what the rest of the departments are doing, right? They're creating replications of this data all over the place. This is a fundamental reason why a lot of the organizations seem to be drowning in data but lacking insights as the ecosystem becomes far more complex and confusing because the data can't be accessed productively for them. While they move to the cloud, and that'll help solve some of the scale problems that they have, it'll help solve some of the data maintenance problems that they have, it doesn't do anything for the data management problems that this complexity and diversity brings. In fact, in a recent study by the Enterprise Strategy Group, 55% of the respondents said that cloud actually makes data integration harder for them, not easier. Now, this influx of data, coupled with kind of a decentralized ecosystem and decentralized storage options, creates a need for IT analysts and a need for data engineers inside the organization. That's just not it. They also need data literate people who are able to work with the data and translate that in insights. In fact, a recent Gartner study shows that the second biggest roadblock for chief data officers is access to data literate people inside the organization. It still doesn't answer the ultimate question people have, right? What are these users doing with this data? How can a company make use of this, all this data productively? How can they create these actionable insights? The challenge these companies have, our customers have, is they're using lots of legacy tools for specific actions, whether it's data prep and blend, whether it's spatial, AI and ML, enriching the data. Each of these tools was built fit for purpose for just one specific task, and inherently don't integrate with other products inside the ecosystem. This makes it hard for the end users. If you step back and take a look at the entire ecosystem, it's incredibly complex, and it continues to remain so. With all of these data living across on-premise and cloud and morphing across multiple data sources, the basket of solutions that customers are using and that they're grappling with to create enterprise value keeps growing. This is exactly where Alteryx comes in and how our product solutions can help. We've got a 15-year track record of low-code and code-friendly solutions, and we're never gonna waver from these strengths. We're gonna continue to evolve, as you'll see from some of our product strategy that I'm gonna share here in a second. We're gonna continue to evolve our product architecture and our platform architecture to reflect some of the changes that our customers are facing. Complex data pipelining, how do you incorporate that? How do you incorporate automation and orchestration into the platform? How do you optimize the analytics experience, so you're starting to create value quickly and permanently? We go to where the data resides, whether it's on the cloud, whether it's on-premise or a combination of both. In parallel, we're constantly fine-tuning how we access the data and how our customers experience the data. We're embedding richer, more intuitive AI capabilities inside of our products with tools like Alteryx Intelligence Suite. It's now incredibly easy for any user, regardless of the skill set that they have and the expertise they have in data, to be able to create a workflow and start to automate analytics inside of Alteryx. With that, let me actually introduce Vishal Soni. He's in our product organization, and he's gonna show you exactly this, how easy it is for a user to create a workflow and start to harness all the data and create insights inside of Designer. Take it away, Vishal. Thank you so much, Suresh. Cheers. Thank you. Yes, thank you all for being here. I'm super excited today to be able to show you the power of Alteryx. We're all gonna play pretend, and we're gonna pretend that we're a retail company. What we're trying to do is to try to understand where we should actually go ahead and open a new store using data. With Alteryx, the nice thing is I can actually go ahead and connect to my data wherever it lives. I can start to prepare my data. I can start to filter it. I can start to transform my data or even tap into things like spatial analytics, machine learning, or even computer vision. We've got all of these 300 different drag-and-drop blocks built out of the box, which allow you to do things like I just mentioned, those ETL tasks, the data prep tasks, and you can actually start to shape the data however you want it. The first thing we're gonna do in our case is we're actually gonna go ahead and connect to some data. To do that, all I need to do is drag and drop. From here, I'm able to actually dive in and connect to data wherever it lives. For example, if I wanted to go ahead and connect into Amazon or Snowflake or Databricks, I just simply click and choose where I want my data to live. In my case, I do have a file, so I'm just gonna go ahead and connect into that. This file contains my customer order data, the shipping data, and transactional information. In order for me to actually start to understand the data, I can actually go ahead and get visualytics given to me directly. What this allows me to do is really uncover all the hidden insights that data has to offer. For example, straight away, I'm able to see if in terms of my shipping method, that most people actually prefer to ship with standard class with just around 60%. From here, I can then go ahead and also check the data's health to make sure that the data's clean. It's how I want it. I'm not missing any data, and I can do this all in a couple of clicks. I can then go in to start doing whatever I want to on my data. I can start adding different filters. I can start changing the way that the data's actually structured. I can even go ahead and output that data or even tap into things like spatial analytics. Here's one I made earlier. Going back to that business problem that we're trying to solve, we're trying to figure out where we should actually go ahead and tap into a new market. Well, I can very easily start to do things like add heat maps directly onto my workflow, again, just by drag and dropping. I can go ahead and choose exactly what I want it to show me. In this case, let's just look at the sales. In seconds, I'm able to click run, and I'll actually be able to see an interactive map showing me exactly where all of my different customers' spending is coming from and also where it's not coming from to really allow me to start to understand where to go ahead and open that new location. From here, I can actually go ahead and just output this back to wherever it needs to go as well. I can choose if I wanted to output it directly back into a BI platform like Tableau or Power BI, if I wanted to put it back into something like Snowflake or Databricks or into a static file as well. Everything that I'm doing is live. We were able to do this all without a single line of code, all using drag and drop in record time. Thank you, Suresh. Thank you, Vishal. You saw how easy that was for a user to be able to do, a retailer creating targeting strategies and targeting decisions on the fly. As you think about our role in the broader analytics stack and our commitment to innovation, particularly focused on the cloud, we've delivered three cloud solutions in the market earlier this year. This expanded portfolio of solutions puts us in a position where we can serve the rising global demand for data analytics, whether it's new personas that we meet with products like Auto Insights and Designer Cloud powered by Trifacta, or it's a whole new set of use cases. This is all part of our vision for democratizing analytics. With Designer Cloud powered by Trifacta, we've brought together the best of both worlds. We brought together the user experience that our customers love from Designer Cloud with the secure multi-tenant, multi-region cloud-native platform of Trifacta. With Alteryx Machine Learning, we're giving analysts the opportunity to build predictive models. With Auto Insights, we are creating a whole new set of users of our products, the non-technical business owner or business user who can derive insights with a click of a button and have an automated analyst at the tip of their fingertips. Auto Insights really introduces a unique approach for understanding the data and getting insights out of the data. Whether if you're a business or a non-technical data worker, you just plug in your time series data and Auto Insights does the rest. It starts to use artificial intelligence and machine learning to uncover the business metrics that really matter for your business and surfaces them to the user. In many ways, it goes beyond what the dashboard can actually provide. To show you precisely what this will mean, let's have Vishal kind of just show you the time series data in action and how these insights are generated. Cheers. Thank you so much. Brilliant. With Auto Insights, exactly as Suresh mentioned, we're giving business users the power of AI-powered dashboards to really allow them to unlock all of the different insights in that time series data, and it's done so simply. Without building any code, you business users get an overview of their KPIs. We can go ahead and choose which one of these that we want to actually focus on. For example, let's take a look at some profits. We're, by clicking on Overview, able to actually go ahead and see all the historical views of what's happened. We can see that we're up 6.4% over the previous month, which is great. The natural question that follows this is why? Why did this happen? Well, clicking on what caused this shows you just that. Here we can see all the different top factors that have contributed to our increase in profits. We can even go ahead and drill down into any of these if we wanted to. For example, here, we can see that Delaware did pretty well. It's one of the top contributing factors. By clicking on drill down, we're able to actually go ahead and see all the different key changes that occurred all in context without any code. I just wanna stress that none of these screens have been pre-configured. All we've done is we've taken data, we plugged it in, and everything you're seeing is happening without any custom code or setup. With every refresh, Alteryx is scanning the data and showing you things that you might need to have brought to your attention. With unexpected changes, you're able to actually start to have prompts where any anomalies in your data can be surfaced to you and making understanding them simpler than ever. You can have all of these different types of insights also sent directly to you and shared with members of your team. Typically, creating all these different weekly, monthly, and quarterly reports have been super manual and time-consuming. Not here. You have all of this done for you, so it makes preparing for that 10 A.M. meeting that much simpler and lets you answer the questions you didn't even know you had. Thanks. Back to you, Suresh. Thanks, Vishal. You saw with the Designer demo how easy it is for a non-technical user or a user of any skill sets to be able to automate analytics and create all of this data and these insights. With Auto Insights, you see how a non-technical business user get access to insights that were hidden in the data, and the AI engine starts to uncover all of those insights. It's really exciting to see our products bringing new use cases to life. Our customers require converged experiences, and that's exactly what we set out to do with the recent announcement of the Alteryx Analytics Cloud. We announced it earlier this year, and the Alteryx Analytics Cloud is an end-to-end suite that that integrates Designer Cloud powered by Trifacta, Alteryx Auto Insights, and Alteryx Machine Learning into one single platform. These products work in concert together today, and that integration gets better over time. We are building a converged front-end experience that's role-based and accessible to our users from anywhere across the enterprise. We're firm believers that a platform-based approach is the way forward, and this allows us to scale data and analytics use cases across every user, every line of business, and every department. By pulling all of our analytics capabilities together, we can help our customers truly democratize insights and automate analytics. Let me give you a fairly simplified peek at our cloud architecture. Underpinning all of our cloud platforms that you just saw is our unified platform that is built in the multi-tenant SaaS control plane. Our platform brings together a common set of shared services, whether it's connectors, user management, telemetry, and extensibility, which increasingly becomes critical as our customers and our partners extend our products and extend our solutions to create new innovation. Uniquely, we also offer unrivaled deployment versatility, whether it's multi-tenant SaaS or in the customer's virtual private cloud. They get to decide. This end-to-end platform provides the backbone for our analytics solutions to serve our community's needs across the board. We're seeing our customers engage with Alteryx across a broad set of use cases, really reinforcing this vision that we have for democratizing data analytics for all. For instance, CFOs are leveraging our solutions to build tax and audit automation workflows. CMOs are using our solutions to do build campaigns and do customer targeting. Even CIOs are using our products to do security and network analysis these days. This is just a small sample of the number of use cases that over 300,000 users are doing every single day in our products. Another great example is Stanley Black & Decker, who are here at Inspire. You'll probably hear from them over the next couple of days. They use our products to generate top-line growth and cost savings to the tune of $millions by creating real-time analytics for their sales and accounting teams. Bless you. Interestingly enough, they aren't alone. We have this large community of users that have selected Alteryx as their platform of choice for data analytics. This is precisely why I'm so confident about the bold and transformative steps that we are taking in product engineering to make Alteryx an innovation powerhouse. It's always better for these things for you to see the reality of the Alteryx Analytics Cloud, in live. Why don't I turn it over to Vishal again, where he can show you an end-to-end demonstration of how the analytics platform empowers our customers, to drive insights and breakthroughs and meaningfully enhance the business. Cheers. Thank you so much. We're gonna go through another example today. We're all gonna pretend that we are a retail company, and we've got a bunch of different data. We've got some sales information, we've got customer information, and we've got the different products that we're actually selling. Data comes from a bunch of different places, CRM systems, marketing systems, transactional systems, databases, files, and so on. First, with Designer Cloud powered by Trifacta, data engineers can start to orchestrate and automate all of the different data pipelines that load up your data warehouse or data lake. Here, data engineers can easily start to build out different flows that can take, for example, our customer data from HubSpot, our order data from Oracle, or our product data. Sorry, from Salesforce, and our product data from Oracle to start to combine, structure, and standardize all of these different sources of information to build out a single consistent customer view. In this case, we're gonna take all of this different transaction data, customer data, shipping, and order data, and put it into something like Snowflake or Databricks. We can then step it up. With Plans, you can start to orchestrate and automate your entire different data flows to manage entire data pipelines. All the different steps that we saw in the previous screen can be put together so that we can start to continue loading up all of our different tables, and even send alerts to let people know when the data's ready. The result of this is that we've now got a single consistent customer view of all our different upstream systems, and in this case, we've even sent a Slack notification to the different analysts to let them know that the data's ready. So far then, what we've been able to do is to build out a data pipeline, set up the orchestration, and start to pull data from all the different systems into our data infrastructure. From here, analysts can then go ahead and pick up that data and start to build out their own analytic use cases on top of it. What we've done here is we've connected to that data from Snowflake or Databricks or wherever we've decided to put it. What we've been able to do is start to build out a customer segmentation model so that we can really understand the spending patterns of all of our different customers. We built out this using an RFM model, which essentially looks at the recency of the previous transaction for each customer. We've also looked at the frequency of how often they're purchasing stuff from us, as well as the monetary value of how much they're actually spending within our company. Just by dragging and dropping, we're able to start to transform the data that was provided to us, gain deeper insights about our customers, and segment them based off their spending patterns. We can then output this data directly wherever it needs to go. As you saw earlier, we can output directly to something like Tableau or Snowflake or really anywhere you wanna put it. We could also go ahead and output this to something like Auto Insights just by dragging and dropping to start to give this data to our business users. For this example, let's take things up just a little bit and send it into Alteryx Machine Learning, where we can start to build our code-free models to answer even more business use cases. For example, what is the lifetime value of each of these different customers? I'm gonna jump into Alteryx Machine Learning now. With Alteryx Machine Learning, citizen data scientists can start to build out different machine learning models, which in this case is gonna be to understand the lifetime value of each customer. First, Alteryx is gonna analyze the data's condition to make sure that it's ready for modeling. Next, we'll be able to choose what it is that we actually wanna predict. In our case, we're trying to predict the lifetime value, so we'll look at that sales column. Alteryx is gonna start to show us the different relationships between our columns in these rich, interactive charts. This makes it super simple to start to understand the different relationships between all of our different columns so that we're easily able to see the different patterns in customer spending. Different models are now being trained and analyzed to present us the best one for us to use. We can also see insights about our models as well. For example, we can look at things like feature importance, which tells us just how important each of our different columns are when making that prediction. We can actually start to do simulations and what-if analysis. This can be super valuable if we wanted to understand how a change, for example, in the customer segment from a corporate to a consumer customer, is actually gonna have on the lifetime value of that particular person. We can then allow analysts to go ahead and use this model to be able to go ahead and predict new customer spending values. This can really help us to aid those business decisions. What if we don't know the questions that we want to ask? What if we want Alteryx to take a look at the data and just tell us? Well, that's exactly where Auto Insights comes in. We can load the data in as is. For example, we could take it directly from Designer Cloud powered by Trifacta, and Alteryx is gonna give us these insights, no problem. On the other hand, what we've done here is we've gone ahead and loaded that enriched data that's gone through Designer as well as Alteryx Machine Learning, and this gives the business even further insights, giving us even more detailed analysis on our trends, showing us our customer sales data in a way that's easy to digest. You'll get insights automatically generated on your time series data, and you don't need to be a data expert to digest the analytics from it. We can get deeper insights by clicking on that overview. For example, how the transaction count has been over the last month. We can also go ahead and dive in to see exactly what caused it. This is super crucial in understanding the why. We can drill down into the different segments that's actually affected the change to really start to understand how each of these have contributed to our KPIs, as well as dive deeper into any unexpected changes. Alteryx is scanning the data with every refresh, giving you those long-term trends, and ultimately giving you trust in the numbers and helping you answer the business questions you might not even know you had. This is Alteryx, and it truly is analytics for all. Cheers. Thank you, Suresh. Thank you, Vishal. Those three demos really brought our value proposition home. It's a great view of the expanding platform of solutions that work together and create this cohesive experience. I talked to you about Alteryx's role in the modern data stack, how we're helping our customers across on-premise and cloud datasets. I talked to you about the Alteryx Analytics Cloud and how we're bringing an integrated cloud product platform together with a single unified user experience that's role-based. Vishal showed you the demos that you'll start to see this product strategy come together, and this is all kind of product and data working together in real time. I'd like to highlight next some of the announcements that we're making at our Inspire conference. Firstly, we're announcing expanded technology partnerships with Snowflake, with Databricks, with Google. We've entirely refactored our Databricks connectors to make it easy for our customers to connect with cloud Delta Lakes and to read and write into those Delta Lakes, but we've also given them the opportunity to use Databricks SQL and to work with their cloud fetch capabilities. We've made massive improvements to our Snowflake bulk loading capabilities and to BigQuery access and so much more. These updated integrations that we've made with our cloud partners allows our customers to really leverage this native push down capabilities that makes it easy for them to extract insights out of these massive data sets. You'll also hear us announce several platform enhancements and an even better user experience. We've updated the Designer interface, made it easier for the analyst to get more productive and to improve the capabilities of the analyst as they work with Designer. We've shown new integrations. We're announcing new integrations between Auto Insights and Designer. You actually saw that integration at work when Vishal was demonstrating the product, where you could drag and drop Auto Insights inside the Designer palette. In Alteryx Machine Learning, we've added enhancements to our time series modeling capabilities. We've introduced a whole new metric store that allows any user inside the organization to define a common set of operational metrics that they can then share and distribute with their partners inside the business. Last but not the least, we're announcing a whole new set of governance capabilities. Our teams have been hard at work updating our cryptographic libraries and our communications to release a FIPS compliant version of Designer and Server. A FIPS compliant version is critically important for, and is key for us to unlock new TAM with federal markets in the public sector. I strongly encourage all of you to explore the Alteryx platform over the next couple of days. Talk to our customers, there's many of them here, talk to our partners, and even spend time with product engineering teams, so you can get deeper into our products and understand them better. You'll soon start to understand why I'm so confident about the bold steps we've taken in product engineering to keep Alteryx's place as an innovation powerhouse. Thank you for supporting us, and thank you for being part of the ride. I appreciate getting a chance to meet all of you after the session. Let me invite Kevin Rubin, our CFO, to the stage next. Thank you, Suresh, and thank you to Mark and Paula, who we also heard from today. It's great to be back with all of you in person and those of you on the live stream. Thank you for joining us. I've been at Alteryx for six years now, and the excitement and momentum within the business throughout the entire organization has never been greater. Mark began this afternoon talking about our vision of democratizing analytics and the massive TAM in front of us. Paula then shared a refresh go-to-market strategy, including our large enterprise focus. Suresh just walked through our expanded product offering that now includes our cloud-based data analytics platform. Global demand for digital transformation and analytics is ramping to new levels. When we consider all that we heard today, our ability to meet this staggering demand has never been stronger. Let me now tie all of this back to the financial model and how we believe we are differentiated and positioned as a leader for many years ahead. From a financial model perspective, it really all distills down to growth and profitability. Robust, durable ARR growth coupled with disciplined investments is a recipe for long-term shareholder value. Given the size of the market as well as our robust net expansion, we are focused on growth today. We have several incremental tailwinds underlying this growth that I'd like to highlight. As Mark mentioned earlier, the market opportunity is massive. Today, we operate in a $65 billion TAM, and according to IDC, that's gonna grow to over $110 billion by 2025. This TAM consists largely of legacy, disparate, BI, data prep, and analytic tools. That means Alteryx is about 1% penetrated into a very large market opportunity that is long overdue for modernization. In addition, enterprise digitalization is driving an influx and a further fragmentation of data throughout the organizations. This further expands the market by generating incremental demand for data and analytics within new types of organizations, new personas, and new use cases. Alteryx's low-code, no-code approach to data analytics is well aligned to help enterprise customers empower their employees to leverage the data available to them and extract actionable insights. We are seeing this consistent expansion in our average ARR per customer with acceleration in recent quarters as enterprises expand their use throughout the organizations. We are also seeing this traction with ELAs that Paula described a little earlier. ELAs remove friction to new adoption, they seed a natural path to incremental ARR in subsequent quarters, and they provide us a high level of visibility into net expansion going forward. Our cloud strategy is to enable enterprises through a single easy-to-use centralized solution, unlocking new personas and new use cases. We believe this strategy secures Alteryx as a key enabler across the ecosystem for years ahead, especially as the data stack evolves. As you just heard from Suresh, our platform includes Designer Cloud powered by Trifacta, Alteryx Auto Insights, and Alteryx ML. We are committed to our customers and will continue to evolve this platform to meet their needs. We were a pioneer in analytic automation, and we view the cloud as our opportunity to further extend this leadership. Having the right platform for customers is only part of the story. You also need to have a go-to-market strategy to bring the solution to the customers, and that's where Paula's impact on the business has been so transformational. This begins with building out an enterprise-focused direct sales team, where we had a record level of hiring in the first quarter. With our enhanced go-to-market now in place, along with our expanded product platform of cloud-based solutions, we can better engage with customers and prospects at the executive level. This top-down approach creates opportunities for broader enterprise use of our solution across the organization. As we mentioned earlier, we are seeing this early success in our greater than $100,000 ARR customers growing nearly 40% year-over-year in Q1. Finally, we view partners as being key to efficiently scaling our go-to-market reach in meeting this rising demand. Contributions from partners have been a tailwind to ARR growth in recent quarters, and we believe helps us efficiently and quickly scale our reach to companies of all size. Again, our ecosystem partners include technology partners, global system integrators, solution providers and OEM partners. Today, partners represent about 1/3 of our business, and we expect will continue to be a growth driver in the future. We've experienced consistent ARR growth for multiple years now. This has largely been due to the robust underlying analytics demand and our market leadership. The incremental growth drivers, a large TAM, expanded product portfolio, incremental cloud capabilities, new personas, an enterprise go-to-market motion, and investments in our partner program give us confidence in the year ahead. I've also included our historical growth in ARR, revenue and billings to show two dynamics. First, billings and ARR are closely aligned, reinforcing that ARR tracks the fundamentals of our operating model very closely. Second, while there can be some variations year to year in revenue growth rates compared to ARR due to ASC 606, revenue ultimately follows the path of ARR. We manage our business on ARR today, which we believe is the purest metric and most reflective of the state of the business. Growth is on a solid trajectory with multiple drivers in place that we expect will bear fruits for many years. With that in mind, it's equally important to consider the underlying earnings power of our current model. We are committed to investing in our business, but within a framework that we believe puts us on a path to durable profitability. Let's take a few minutes and talk about the operating model. We are continuing to target gross margins in the 80%-85% range. This reflects incremental cloud-driven revenue plus strategic investments in customer success, a key area of focus as we continue to gain traction with large enterprise customers. We are targeting optimizations across the entire operating business, but which I'll focus on in a little bit moment. We see the most meaningful opportunity in sales and marketing over time. We are deliberately investing in enterprise sales, global scale and brand to capitalize on what we believe is a once-in-a-generation opportunity. We expect this will ultimately equate to a profitability of 20%-25% with free cash flow in 20%-25%. With the framework in place, let's explore the levers we have to bridge from our operating margins that we have today and where we see them going forward. Keep in mind, this slide is not drawn to scale. Many of the strategic initiatives driving growth will also unlock incremental margin expansion over time. First, we expect our enterprise-focused sales motion to fuel rapidly growing enterprise base of business. We are already seeing this strategic focus bear fruits. As we mentioned, we have 45% of the Global 2000 now as Alteryx customers, and that's up six points year-over-year. Given the higher upsell and lower churn of this customer segment, this gives us a much stronger net expansion rate. As mentioned, our overall expansion rate for the company is 119%, but it's a much stronger 128% within the Global 2000. This equates to a higher relative lifetime value and a more efficient customer acquisition cost, which is positive for long-term margins over time. Second, we are scaling our go-to-market reach through partners. Empowering our global system integrators and solution providers to sell the Alteryx platform can efficiently scale our ability to meet the rising demand both domestically and internationally. Our partners also provide scale to our customer success efforts, and this means we can expand our incremental ARR more efficiently through partners. Third, we recently expanded the platform to include cloud-based solutions to address the needs of new use cases and new personas. We are already seeing favorable ARR per customer trends and see potential additional tailwinds ahead as customers can more broadly expand corporate-wide with our new platform. We continue to see opportunities to scale the business and unlock operational efficiencies of scale across all of our operating expense line items. To be clear, today we are dialed for growth. We have significant momentum behind us, a massive opportunity ahead of us, and we strongly believe that driving responsible investments for growth today will maximize long-term shareholder value. Over time, as we scale our business and capitalize on these margin levers, we are confident in our ability to deliver against the long-term target margins. With that, let me wrap up a quick summary of the day. We remain very positive about the data and analytic market dynamics as well as our positioning in this market. The TAM opportunity is massive at $65 billion, and with users largely leveraging legacy disparate tools, the market is ripe for modernization. Enterprise digitalization is expanding market demand to new personas, and our commitment to democratizing analytics uniquely positions us to meet that demand. We are seeing this both with our flagship Designer and Server solutions, and we are reinforcing our leadership position with an expanded cloud-based solution. Finally, we have an aligned go-to-market motion to efficiently and rapidly scale our market reach to capitalize on this global once-in-a-lifetime opportunity. With that, I'd like to welcome Paula and Suresh up to the stage to join me for some Q&A. I'm also excited to share that we have Mark joining us virtually. Please feel welcome to direct any questions on strategy and vision his way. Before we begin the Hello there, everyone. It's Mark Anderson here. I just wanted to thank you all again so much for joining us today. I hope you enjoyed the presentations by myself and our leadership team. I really wish I was able to be there in person, but really excited to participate with this Q&A session virtually. With that, let's open up the floor for the first question. Last slide, please. You're gonna run the mics. We're good? Yeah. Hey, everybody. Good afternoon. I'm Michael Turits from KeyBanc. Thanks to the whole team and great to see you all. It's fantastic demonstration of the breadth and usability and capabilities of the platform. Suresh, I just wanted to ask you a little bit about the evolution from the current platform to where it's going with the Trifacta integration. Maybe approach it from two sides, both from the back-end side and from the UI side. Just if you'd map it out for us, where we are, where the different pieces will fit together, and what some of the roadmaps will be for that. Yeah. Thank you for the question. As you saw, we continue to invest in Designer and Server. There's a massive opportunity for our customers there that are empowered data analysts and teams that wanna build and manage complex workflows, on-premise, and we continue to support that. Our product roadmap is super rich and robust on that front. On the Designer Cloud powered by Trifacta, Alteryx Auto Insights and Alteryx Machine Learning that comprises our Alteryx Analytics Cloud, we're making significant investments there, and the investments there are directed in a couple of areas. You'll start to see the user experience that our customers are super familiar with, the low-code, code-friendly building blocks, the access to our engines, AMP and E1, the access to and the ability to build workflows. You'll start to see that show up inside the Designer Cloud powered by Trifacta product as early as this summer. Because we embrace a cloud-native platform, and we deploy code almost every single week, we've started to roll these capabilities out inside the cloud product. You'll start to see the user experience show up first and foremost. I talked to you, I kinda gave you a simplified look at the cloud platform. It's multi-tenant SaaS in the control plane, but it's easy enough for our customers to deploy the data plane wherever they choose to, whether it's AWS or Azure or frankly on-premise, if that's what they wanna do. What Trifacta acquisition gave us was that accelerated cloud platform, which makes it easier for us to kind of make this multi-tenant cloud capability available to our customers. Step one, you'll start to see us bring the user experience of Designer Cloud. You'll start to see the Designer low-code tools show up, and the engines show up, and the ability to create workflows as early as this summer, as I said. What you'll start to see is the, as customers adopt these products, you'll have clearly the estate on the on-premise world where customers are running on desktop and server, and you'll have our customers expanding using our cloud solutions, being able to access through a browser, being able to access for a variety of use cases that are increasingly aimed at the casual user and aimed at business analysts seeking to bring AI and ML skills to bear. Over time, what you'll start to see is the ability to run these workflows in either on-premise or in the cloud, right? That's the evolution of the product roadmap and the product strategy. Thank you. Kamil Mielczarek from William Blair. I have one for Mark. So you've been in investment mode. You've done a great job refocusing on the enterprise and building a cloud product, and it's helpful to see the steps that Kevin laid out on profitability long term. But given the macro overhang, how do you think about potentially readjusting the growth and profitability in a more severe macro environment? I know you joined mid-pandemic, but given you were on the board, how does your experience and knowledge of changes made in response to the pandemic inform that decision, and what would you do differently versus early 2020? Well, hi, Kamil Mielczarek, and thank you so much for the question. Yeah, you know, I think we're always adapting and iterating to what's going on based on what we hear from our customers, what we hear from our partners, what we're seeing in the markets, macro in particular. As I think we talked about on the last earnings call, what we do for our customers, I think, really matters. Oftentimes we're brought in to help them drive more profitability or help them streamline efficiencies in their supply chain. You know, just last week I was talking to a large U.S. based tool manufacturer, and these guys have generated hundreds of millions of dollars worth of savings and margin recapture with us. Their priority going forward, recognizing that they see the inflationary impact, they see a potential recession down the road, is to double down and invest more with Alteryx because they know they're gonna get a really good return. I think it sort of dovetails with what I hear from customers. Whether it's cybersecurity or digital or functional transformation, these are the two priorities that I hear from almost every investor, excuse me, every customer, whether it's enterprise or government, very consistently. You know, I think what I've learned in the last couple of years is, you know, keep your ear to the ground and adapt. I think, you know, this isn't, this won't be my first recession if, in fact, we do go through it. I learned deeply from the banking crisis in 2008 as well as a mid-level manager of the dot-com bust in 2001. You know, we've got tools and capabilities to really hear and see things as they're happening. We're prolific users of Alteryx ourselves and you know gonna continue to you know keep our ear to the ground. That's helpful. If I could just quickly follow up, one for Suresh. As you look across your cloud portfolio, the updates are very helpful. There's so many changes going on. If you look out three to five years, what will be most different about the cloud product versus today? When you look across the various initiatives, what are you most excited about? I'm excited about the opportunity to drive an integrated end-to-end analytics platform. Once you have this platform capability, you can roll out new innovation faster. Frankly, our customers and our partners can build innovation faster. You saw me throw up that slide on the use cases across the office of finance, office of marketing, supply chain, HR, and so on, and that was just a fraction of the use cases our customers use. Now, if we give them the opportunity to bring users on board, and you saw Vishal's demo, a business user kind of using Auto Insights and getting insights out of that goes beyond what a dashboard can provide, frankly. Or a business analyst kind of building and validating predictive models. That ability to give all of them the opportunity to drive value out of analytics through a single platform, a single interface, and be able to do that quickly with the time to value keeps decelerating. I think that's the most exciting part of what cloud brings for us. Thanks, again. Thanks a lot, Kamil Mielczarek. Thank you for taking the question. Sanjit Singh, Morgan Stanley. Really appreciate getting to see everyone for the first time in two years. Thank you for the content on the presentation, was very informative. I wanted to talk a little bit on some comments that Paula made. I think she talked about the competitive environment, the pandemic sort of structurally changed that. When I looked at some of the demos, I wanted to get a sense of whether Alteryx was going after the last mile problem when you talk about sort of driving to more automated insights. We had came from this world where you guys were solving the data wrangling problem, and then the BI tool, the data visualization tool would create a dashboard. Mm-hmm. Is that world essentially ending, and are you guys going after the replacing the dashboard with more automated insights? Is that the opportunity what's gonna drive a lot of growth if this platform story really begins to execute? Yeah. Thank you for the question. There's still plenty of opportunity in the early miles, if you will, to use your analogy. You know, we are still just scratching the surface, right? When we look at the 1% market share that we have and the number of data workers that are out there, the common conversations that we have with customers that they just can't keep at the pace that the business requires to be able to address and make decisions and solve the problems that they have. You know, they've worked tirelessly to try and get the data in one place. It's not in one place. It's still very distributed. They've worked tirelessly to try and see if this, you know, highly skilled expert, centralized data science team could solve the problems. They're not able to retain those people because those people wanna work on the really complex problems. They don't wanna solve all the problems for the entire enterprise. Without fail, every customer that I talk to is recognizing that it's absolutely about empowering a broader base of employees across the enterprise. There's still lots of growth opportunity there. In terms of the, you know, the dashboard piece, we have great partnerships with dashboard providers, so we're not really intending to go square into that space. I think frankly, there's tired of the dashboard environment right now, to be honest with you. That's why Auto Insights is so compelling for our customers because these static dashboards might answer your first question about what's happening, but it doesn't answer the next question and the next question and the next question, and they certainly aren't nearly as dynamic and able to deal with time series data in the way that the business is running. I have been blown away by the appetite for the Auto Insights conversation at the executive level with our customers in trying to do that storytelling of your business from your data. What's happening? What are you gonna do next? Why is it happening? I do think that's gonna be a significant growth effort for us as well. For my follow-up, Kevin, thank you for laying out an updated financial framework. When I look at where we are today, which is sort of negative 30, negative 40 operating margin, and then this path to 20%-25%, in terms of thinking about kind of interim milestones, in terms of let's talk about maybe operating profitability, this year is definitely an investment year. Is that something we can expect in calendar year 2023? If not calendar 2023, when can we expect you guys to achieve that sort of interim milestone of getting back to operating profitability on the path to the 20%-25%? Thank you. Yeah. Thank you for the question. You know, going back to the beginning of the year, on our Q4 call and, you know, when we had given guidance, you know, we were really clear that the operating margins of the business this year were being largely impacted by the acquisition of Trifacta. But for that, we would be operating break-even, and that was kinda how we were making our intentional investment decisions. As you saw in Q1, we actually performed better on the operating margin line, and we're actually allowing some of that, or a majority of that, to kind of flow through to the full year while still being very selective in where we invest in the business for growth. I would just go back to, you know, what you've heard from all of us. This is a really large opportunity, and we really have an opportunity now to take advantage of kind of our leadership. You know, at 1% penetrated into a $65 billion TAM, we do think making very disciplined and intentional decisions around where to invest to really kind of grow for scale is an appropriate decision. As for when we kinda get there, unfortunately, you know, we don't guide out before this year, but I'd like you to take away the power of the model that I kinda walked through. Thank you. Joel Fishbein from Truist. I guess two for you, Kevin. One, you put up ARR per customer and how nicely it's grown. Can you maybe both you and Paula give us some insight on where do you think that number can grow to or go to? Paula, along those same lines, you talked about penetration inside your install base. You have, you know, 45% of the Fortune 500, I believe you said. How are you driving new use cases inside the enterprise? Like, are there any specific examples you can give us with regard to that? Where do you think that ARR per customer could go? Thanks. Yeah. There's still lots of opportunity inside the existing customer base, and we've built the go-to-market to be able to support that. That's why it's so important to have the customer success element of the three-part enterprise strategy that I shared with you because that team, those methodologies, the practices that they've built are for identifying new use cases, right? Maybe we're in a customer, and we're in the finance department today doing dozens of different use cases, but we can go over to the marketing organization and take a look at how they're building targeted campaigns, how they're handling lead routing and so forth, and Alteryx has use cases there. What's really common for us is to work with the customer to build a center of excellence, center of enablement, so they can drive in their own way, leveraging their culture and their operating model, a scale out across the enterprise to bring on more users to the Alteryx platform. We give them the tools to do that. We show them the training, we show them the enablement, we show them how to run hackathons to identify new use cases. We help them with the practice to build up the enablement and the excellence center. This is the repeatability stuff that I was talking about that we've seen working, you know, for customers that have gone from 10 users to thousands of users over a period of time, and now we know how to shrink that down and say, "Here's the playbook for you to be able to do that. We'll help you with it, our partners will help you with it, or you can do it, you know, for yourself." That's the way that we help them increase their analytic maturity and there's a lot of growth opportunity for us in that. Yeah, I would echo the same. I mean, if you just look at the amount of, you know, transformation and changes we've made in our business and the improvement we've seen in that metric just over the last five quarters, imagine how that changes over time as we're, you know, really kind of leaning into this momentum and, you know, seeing continued success with ELAs and customer success and really growing that Global 2000 footprint. I think there's a lot of opportunity going forward. Can that $83K be over $100K in a period of time per customer? Is that the goal or? We will see. Drive it up. Thank you. Brent Bracelin with Piper Sandler. Great to see a lot of familiar faces here in person. Yes. Not on Zoom. My question may be two, if I could, but I wanted to start with Paula. Obviously, it sounds like ELA is very early, but sounds like very encouraging success. What is driving the success? I'd love to drill down into that because on one hand it sounds like a dedicated customer success team is helping kind of accelerate use cases. I would kind of not call Alteryx a low-cost product. I wonder how much pricing, as you think about like an ELA and being able to reduce friction around pricing, is also contributing to some of the success there? Just any more tidbits you can give us on why ELAs are having success would be helpful, and then one quick follow-up for Kevin. Absolutely, to connect it back maybe to the prior conversation, right? I think reducing that friction for them to bring on more people onto the platform more quickly without having to raise a PO every time, you know, this department wants to get licenses or that department wants to get licenses. The burst capacity that we provide them in year one of the ELA makes that easy for them to do. That's why we're not surprised to see that already a third of the customers in a pretty short period of time have already pushed into that and you know, far into that capacity. We can go back and say, "Okay, clearly we need to move up." You know, reducing the friction, helping them with the governance of license administration, right? These are things that can get in the way of customers moving at the speed that they want to move. So the ELA absolutely helps with that. It helps them test out other capabilities that, you know, Server, Intelligence Suite. These may not be products that they have yet started playing around with, but those are built into the ELA, so now they have the licenses to be able to do that, and they can start turning those on and seeing how that affects their business. On the discounting side, we were intelligent about what we built into the ELA, right? To be able to say, you know, "Here's a cost efficient and predictable way for you to, you know, gain access to Alteryx innovation. On that ELA pricing, we saw Tableau go through a similar transition to more of a role-based pricing model that really helped reduce friction. In those ELA structures, is it structured more like a role-based pricing where there's different things, or is it more volume pricing benefits and discounts on volume? Volume and product breadth, which you could, by relation, say that it's sort of accessing more personas, particularly when we talk about our cloud products, right? Because the cloud products open up the persona base widely. We haven't designed it with role-based categories. It's volume and breadth of the portfolio. Helpful color there. Just Mark, quick follow-up for you on the phone here. You haven't been shy over the last two years talking about your appetite for M&A. I would love to get a current read on the appetite, just given the changes in the market conditions that have soured. I know there's an aversion between public valuations and privates still, but to the extent that that changes, and it sounds like with some of the layoffs that we're hearing in the Valley, that is changing. What is the current appetite on further M&A? Thanks. Yeah, thanks for the question, Brent, and sorry I'm not there in person to see your smile and face. You know, I think for M&A, last year we were very intentional around, you know, 3 specific targets that each served a very important need, whether it was an acqui-hire, whether it was getting some technology like Auto Insights, as Paula said, that's very much aligned with what we do, getting that team on board. Or whether it was Trifacta, you know, getting 200 cloud-first, you know, engineers, marketers, salespeople to come and join us and become our re-platforming option, if you will. You know, I think we're gonna continue to cautiously look at potential targets. I do see private company valuations going way down, as you inferred. You know, we're always going to be thoughtful about how we execute these things and make sure that we're, you know, doing the right thing relative to long-term profitability models that we're very much committed to. That said, I'll tell you, there is such vendor fatigue out there in the marketplace right now. As I said in my opening keynote, you know, there's too many vendors and they all sound like they do basically the same thing, and nobody really does. I think our thesis is that there needs to be independent companies that build proper platforms that consolidate much of this, and that's what we're gonna do in the long run. My view and what we've talked about as an executive team, Brent, is in times like this, what we might face in the next year, high-quality teams really shine and high-quality technology really sets itself apart from mediocre technology. We feel really good about, you know, who we are and where we are now, and we'll continue to, you know, cautiously look at potential targets. I think we have time for one more question. Hey, Paula. Hey, Kevin, Suresh. Thanks for taking the time today. Also Mark, virtually. Ashish Bhandari from Ashler Capital. It's great to hear that you're now gonna be going to market with cloud ELAs. I guess, could you frame for us what changes around your go-to-market approach through a cloud-specific ELA? Is kind of the advantage basically that your customers are wanting to consume more of your cloud SKUs, and so this is a quicker procurement process that should drive kind of faster sales cycles and bigger deal sizes, or is there kind of more to that? Then I had a quick follow-up. Yeah. Thank you for the question. Right now, as we're talking with customers, they all wanna hear about the cloud strategy and analytics cloud. They're at varying degrees of places on their own cloud journey, and they wanna know that all the innovation and the user experience and the outcomes that we've delivered with our on-prem portfolio is gonna continue to exist in our cloud portfolio. We're having conversations with every customer today about analytics cloud, and it's definitely gonna be a big theme this week. The cloud ELA is something that can stack on top of our existing ELA, that they get access to both the cloud and the on-prem solutions in the same construct. There might be others that are net new logos for us, that they wanna start first with us on cloud because that's, you know, where they're focusing their investments, and they could easily get started with the cloud ELA as well. It's meant to drive adoption. It's meant to give them access to all three cloud products to drive that, you know, persona experience, and we're so excited to launch it. I can't wait. It's designed for different companies based on where they are in the journey, right? Clearly, not everybody is on the extreme of the cloud journey. There's so many of them just feeling it out and trying to understand the hybrid cloud model, the on-premise model. They're shuttling between warehouse vendors, they're shuttling between cloud vendors. Just understanding our product strategy and roadmap and having the flexibility the cloud ELA gives them, I think really helps them try out these products and start working with them. That makes sense. Just my quick follow-up. It feels like your Global 2000 focus is really paying off. You've reduced the friction for them to expand through your ELAs. I guess how should we be thinking about that higher rate of large enterprise expansion as an ARR growth driver in the back half, especially given your cohort of kind of three-year renewals that are coming up this year? Thanks. Yeah. We have a great opportunity this year with the renewals that are coming up. You know, I mentioned that we not only enjoy higher net expansion in the Global 2000, but we also on average see better renewal rates with them. The faster and larger companies grow with us, the better renewal rates as well. There's a lot of positive interdependencies there. We certainly intend to focus our energy now and in the future to making sure at the time of renewal that we not only renew, but we have the expansion opportunity. History has shown us that we have great expansion opportunity with our renewal base because of their satisfaction and utilization. Between the customer success focus as well as what our partners do for us, we have the whole go-to-market pointed in a big way to that opportunity. All right. Well, I wanna thank you guys all for joining us today. We sincerely appreciate you taking the time in your day to learn more about Alteryx, and I hope that you found all of the presentations informative and insightful. For those of you that are in the room, we're gonna be taking a brief break, and then we're gonna be hosting a customer panel hosted or moderated by our Co-founder and Chief Advocacy Officer, Olivia Duane Adams. Thank you again. It was really our pleasure to be able to present to you today. Thank you.