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spk02: Point Inc. Q1 2024 earnings call. All participants will be in the synonym mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star then one on your telephone keypad. To withdraw your question, please press star then two. Please note, this event is being recorded. I would now like to turn the conference over to your host today, Jamie Arestia, Vice President, Investor Relations. Please go ahead.
spk05: Thank you, operator.
spk10: Good afternoon, and welcome to AvePoint's first quarter 2024 earnings call. With me on the call this afternoon is Dr. T.J. Jang, Chief Executive Officer, and Jim Cassie, Chief Financial Officer. After preliminary remarks, we will open the call for a question and answer session. Please note that this call will include forward-looking statements that involve risks and uncertainties that could cause actual results to differ materially from management's current expectations. We encourage you to review the safe harbor statements contained in our press release for a more complete description. All material in the webcast is the sole property and copyright of AvePoint with all rights reserved. Please note this presentation describes certain non-GAAP measures, including non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating income, and non-GAAP operating margin, which are not measures prepared in accordance with U.S. GAAP. The non-GAAP measures are presented in this presentation as we believe they provide investors with a means of understanding how management evaluates the company's operating performance.
spk09: These non-GAAP measures should not be considered in isolation from as substitutes for or superior to financial measures prepared in accordance with U.S. GAAP. A reconciliation of these measures to the most directly comparable GAAP financial measures is available in our first quarter 2024 earnings press release as well as our updated investor presentation and financial tables, all of which are available on our investor relations website. With that, let me turn the call over to TJ.
spk10: Thank you, Jamie, and thank you to everyone joining us on the call today. Our first quarter was a very strong start to the year as we outperformed our guidance for total revenue and non-GAAP operating margin while delivering strong growth in total and net new ARR. Our performance was again driven by the robust capabilities of our platform, as well as the growing recognition among customers and partners of the need, now more important than ever, to build a strong data foundation. Doing so will empower them to govern their mission-critical information assets, optimize operational costs, boost workplace efficiency, and foster more insightful data-driven decision-making. While these goals have always been top of mind, they're now more critical than ever as organizations around the world seek to leverage generative AI to unlock business value and gain a competitive advantage. It's this dynamic I would like to discuss today with two areas of focus. First, the challenges and obstacles organizations face in adopting AI, primarily due to data security issues that prevent a comprehensive strategy to manage your data estate. And second, the customer demand for AI to improve productivity and the overall employee experience. Along the way, I'll highlight some key customer wins in Q1 that demonstrate how we solve these challenges and close by touching our ongoing investments to innovate in this dynamic business environment. I will then turn over to Jim to discuss our Q1 results and updated financial guidance. So let's jump in. It's no surprise companies everywhere want to incorporate AI into their businesses. I recently had the privilege to keynote the SkillsFuture SG Training and Adult Education Conference in Singapore. In speaking with the many CXOs in attendance, it was clear the ambition to use AI to transform upscaling is palpable. But the elephant in the room is the concern that their data is not ready for AI. These conversations align with the findings in our inaugural AI and Information Management Report, which we published a few weeks ago. Our report surveyed nearly 800 organizations globally and found that 83% plan to increase their AI spending this year, with 60% intending to allocate at least a quarter of their technology budget to AI in the next five years. However, our survey also confirmed a significant delta between these ambitious plans and the reality facing these organizations. Simply put, they're not ready to deploy effective AI strategy because their data estate are not in good order. This is where our confidence platform comes into play. by bolstering organizations' data security postures, providing robust cybersecurity measures, offering comprehensive control and visibility across the digital workplace, and delivering intelligent data insights through automation. By leveraging all our platform has to offer, customers can realize a secure and compliant digital environment that also improves the employee experience. and then build on this foundation with a meaningful AI strategy. But without taking these steps to solidify their data estates, the challenges business face are amplified when incorporating AI, particularly around data security and data governance. According to recent research from Gartner, 72% of organizations believe oversharing and exposing sensitive information is the biggest risk when deploying generative AI applications such as Copilot for Microsoft 365. The AvePoint Confidence Platform can mitigate these risks by helping companies understand the quality of the data AI relies on, controlling permissions, and rapidly setting up proper access controls. In the health and life sciences industry, for example, we worked with a leading US-based medical technology company in the quarter to ensure its data was ready for AI as they prepare to deploy CoPilot for Microsoft 365. With AppOint policies, AppOint cloud governance, and AppOint MyHub, the company is drastically reducing the risk of exposing sensitive information, streamlining their workspace policies, and securing data access so the company's 15,000 employees can utilize CoPilot. Our study also find that before implementing AI, 71% of organizations were concerned about data privacy and security. And 61% were worried about the quality and categorization of their internal data. But despite these concerns, many forge ahead in the flawed belief that their existing information management strategy will suffice. Specifically, our report find nearly half of the organizations lack basic measures, such as archiving and retention policies. And just 29% of organizations use automation. These shortcomings are even more glaring when compared to the size and volume of data our customers need to secure. Driven by the relentless growth of data for many years, more than 40% of the companies today manage at least 500 petabytes of data, and they're seeing that growth accelerate due to AI. Addressing the challenges related to data growth and sprawl has always been a key use case for AppPoint and led to a new customer win in Q1 with a Germany-based real estate firm with over 130,000 tenants and 1,500 employees. The firm turned to AppPoint's secure backup solution to protect its growing data across Microsoft 365, EntraID, Power Platform, and to rapidly identify crucial data sprawl and storage optimization challenges with AppPoint Opus. With these critical AppPoint solutions, the customer can now quickly and intelligently archive its data and enhance its data governance and cyber resilience posture. As noted in our report, we believe the most effective approach for all companies is to establish a robust information management strategy from the outset because organizations with mature information management strategies are one and a half times more likely to realize benefits from AI than those with less mature strategies. For example, let's take a look at the CPG industry, where nearly half of companies are facing challenges collecting and integrating the volume data needed for successful AI adoption. This is largely due to data fragmentation across large number of SKUs, expansive supply chain, and warehousing networks. and complex product categories. In Q1, we expanded our relationship with one of the largest CPG companies in the world to streamline its information management approach with the purchase of AppPoint Opus. Already an existing customer with a number of AppPoint solutions and a growing data estate, Opus will streamline data management policies for their 123,000 users, providing better visibility into data utilization, improve data quality, and lower the risk of breaches. We know a healthy data state is essential to effective AI strategy. And effective AI strategy obviously makes good business sense in creating a more secure organization, reducing cost, and addressing macro challenges. But one additional benefit of effective AI strategy is the improvement of the overall employee experience. For example, Gartner finds AI can drive productivity gains by up to 20%. Why does that matter? Research show that more than 60% of a typical workday is lost to repetitive and mundane tasks that knowledge workers spend 25% of their time searching for information, and they use the average of six to eight apps to complete a single process. If AI can successfully mitigate these employee frustrations, companies can retain talent and reduce turnover, further strengthening the organization. Our best-in-class abilities to solve these problems for many years have established a strong competitive moat, and it's why we continue to innovate and invest in further enhancements for our customers and for the AppPoint team. Our AppPoint AI program aimed at integrating AI into everything we do, continues to progress with internal and external applications of AI. One example is our TiGraph product, where we recently introduced new advanced analytics capabilities for Copilot for Microsoft 365. We're proud to be first to market with this offering to support Copilot, which enables companies to identify areas of high collaboration to better prepare for Copilot readiness. This is just the latest of our AI readiness solutions for organizations to prepare, secure, and optimize data, which collectively will enable them to fully take advantage of AI in the workplace. In closing, successful AI deployments require a strong and healthy data state, which in turn mandates a robust data management strategy. As companies become increasingly aware of this, we have a massive opportunity to drive AI adoption in the years to come. underpinned by our platform technology and our experience solving the most urgent challenges facing organizations around the world. I'm excited for the years ahead, and I want to thank the entire Apple team for their tireless efforts and dedication. Our Q1 results are another strong step forward, and we're laser-focused on continuing execution and capitalizing on the growing demand for our platform. With that, let me turn the call over to Jim.
spk09: Thanks, TJ, and good afternoon, everyone. Thanks for joining us today. As we review our strong first quarter results today, let me remind you that unless otherwise noted, I'll be referring to non-GAAP metrics. For the first quarter ended March 31st, 2024, total revenues were $74.5 million, up 25% year over year and above the high end of our guidance. Within total revenue, first quarter SAS revenue was $51.3 million and grew 44% year over year. And in Q1, SAS comprised 69% of total revenues compared to 60% a year ago. SAS continues to be our fastest growing revenue segment with 44% year over year growth representing our highest in eight quarters. In addition, our other revenue lines continue to perform in line with our expectations and commentary. Term license and support, as well as maintenance revenue, declined year over year, both in dollars and as a percentage of total revenue. At the same time, services revenues grew 8% year over year, but declined as a percentage of revenue to 14% for Q1. And because services represents our only non-recurring business, 86% of our total Q1 revenues were recurring, our highest ever percentage. Our strong SAS performance is also evident as we look at our results from a regional perspective, where SAS revenue growth was above 40% in every region. In North America, SAS revenues grew 42% year-over-year and represented 77% of total North America revenues, which in turn grew 22% year-over-year. In EMEA, SAS revenues grew 46% year-over-year and represented 81% of total EMEA revenues, which in turn grew 17% year-over-year. And in APAC, SAS revenues grew 47% year-over-year and represented 45% of total APAC revenues, which in turn grew 40% year-over-year. Last quarter, we began disclosing our regional ARR performance as these growth rates provide a better view of the underlying momentum of the business everywhere we operate. We were again pleased with the year-over-year growth we saw in Q1. as North America ARR grew 22 percent, EMEA ARR grew 27 percent, and APEC ARR grew 27 percent. Once again, each region was a strong contributor to our overall performance, with their respective ARR growth rates in line with the total ARR growth we reported on a consolidated basis. Continuing now with total ARR and other key metrics we regularly assess. As of March 31st, 2024, total ARR was $274.5 million, representing year-over-year growth of 23%. As a result, net new ARR in Q1 was $10 million and grew 29% year-over-year. Additionally, we ended the first quarter with 560 customers with ARR of over $100,000. an increase of 20% from the prior year. As of the end of Q1, 51% of total ARR came through the channel compared to 48% a year ago. And for Q1 specifically, 62% of our incremental ARR came through the channel compared to 65% for Q4 of 23 and 56% in Q1 of 2023. As we discussed, the channel contribution to our incremental ARR will fluctuate from quarter to quarter, but we expect the channel contribution to total ARR to continue increasing each quarter. Turning now to our customer retention rates, where we continue to make progress toward our medium-term goals, which, to remind you, are 90% plus for GRR and 110% to 115% for NRR. Adjusted for the impact of FX, our trailing 12-month gross retention rate for the first quarter was 87%, consistent with our performance in 2023. And we are pleased that our FX-adjusted net retention rate for the first quarter was 110% compared to 106% a year ago and to 109% in Q4 of 2023. On a reported basis, Q1 GRR was 86% in line with the 86% we reported in Q4 2023. Q1 NRR was 110% compared to 108% in Q4 of 2023. Turning back to the income statement, gross profit for Q1 was $55.2 million, representing a gross margin of 74.1% compared to 71.5% in Q1 of 2023. The improvement in our gross margin is a result of improved SAS margins as well as our product mix. as we had more SAS revenue and less low-margin services revenue as a percentage of our overall revenue this quarter versus a year ago. Moving down the income statement, operating expenses for Q1 totaled $48.6 million, or 65% of revenue, compared to $42.9 million, or 72% of revenues, a year ago. As a result, Q1 operating income was $6.6 million, or an operating margin of 8.9%. While Q1 non-GAAP operating income was well ahead of our guidance, I would point out that approximately $1.5 million of expenses we had expected for Q1 shifted to Q2 and the second half of the year. And this is reflected in our updated guidance, which I will cover shortly. But even after adjusting for this, Q1 operating income would have come in comfortably above the high end of our guidance as our commitment to profitable growth and our sustained focus on expense management again allowed us to realize more of the substantial embedded leverage in our business. Turning to the balance sheet and cash flow statement, we ended the first quarter with $219.3 million in cash and short-term investments. For the three months ended March 31st, 2024, cash generated from operations was $7.8 million, while free cash flow was $7.3 million. This compared to cash generated from operations of $1.3 million and free cash flow of $1 million in the first quarter of 2023. During the three months ended March 31st, we repurchased 1.8 million shares for a total cost of approximately $13.7 million. I would now like to turn to our financial outlook, where for the full year, we are pleased to raise our expectations for total ARR, total revenue, and non-GAAP operating income. For the second quarter, we expect total revenues of $73.8 million to $75.8 million or approximately 15% yearly year growth at the midpoint. We expect non-GAAP operating income of $3.6 million to $4.6 million. For the full year, we now expect total ARR of $316.8 million to $321.8 million, or approximately 21% year-over-year growth at the midpoint. We now expect total revenues of $314.3 million to $320.3 million, or approximately 17% year-over-year growth at the midpoint. And lastly, we now expect full year non-GAAP operating income of $30 million to $32 million or an operating margin of 9.5 to 10%. And on a rule of 40 basis, which for AvePoint is the sum of our ARR growth and non-GAAP operating margin, our updated guidance reflects a 31 compared to the 29 that we initially guided for the year in February. with each component contributing equally to the increase. In summary, Q1 was a strong start to 2024, and we are excited for another year of continued execution and capitalizing on the substantial long-term opportunity ahead of us. Thanks for joining us today, and with that, we'd be happy to take your questions. Operator?
spk02: Yes, thank you. We will now begin the question and answer session. To ask a question, you may press star then 1 on your telephone keypad. If you're using a speakerphone, please pick up your handset before pressing the keys. If any time any question has been addressed and you would like to withdraw it, please press star then 2. At this time, we will pause momentarily to assemble the roster. And the first question comes from Derek Wood with TD Cowan.
spk12: Great, thanks. Congrats on a strong quarter. CJ, I'll start with you. You talk about the rollout of the co-pilot analytics offering within TiGraph. What was just made available? What's the feedback from customers? And I imagine dollars tied to this will start small, but I'd be curious if marketing this kind of tool could draw incremental interest for some of your core offerings, whether it's cross-selling the base or generating new customers.
spk10: Yeah, great question. The Royal Fork iGraph for Office 5 Co-Pilot is the first such solution in the market where we actually help customers zone in onto the high-density collaboration areas and data estate to focus their effort around co-pilot readiness. Around the world, we have seen tremendous activities of companies across the board to actively experiment with Gen-AI and traditional AI capabilities And Microsoft has done a fantastic job in commoditizing and democratizing AI approach, especially offering Copilot to well over 500 million users on MCC5. So a ton of experimentation. We haven't seen massive enterprise-wide deployment yet. So this is why the solution like TyGraph for Copilot from AppPoint that's released just recently this quarter, is the way to zoom in onto the specific areas of collaboration and user groups. So this allows them to, in pilot mode, in essentially POC mode, in small group settings, to really experiment and take advantage of the power of Gen AI. And as we mentioned in our prepared remarks, a very important aspect of making sure that your AI deployment strategy works is to have a very confident and solid trust in your data state. So a lot of that preparation work goes into preparing, making sure that you have the right privilege, right access, right information management, life cycle, life control, as well as removing much of the redundant, out of date, trivial data. And what HighGraph what CodePilot does is actually allow you to not just look at your entire data state, which could well be over 500 petabytes for a lot of customers, zone into the specific areas and user groups that you start with and to get the bigger ROI right away. So it's a very unique product set. And you're right, we see robust pipeline building from all these information management requirements.
spk12: Very interesting. Thanks. And one for Jim, 44% SaaS growth, really impressive. And even if I look at sequential growth, it was double digits. We haven't seen that since I think first half 21. Can you talk about what's driving that inflection in SaaS? Is there been a pickup in on-prem migrations or are there other factors like more cross-selling, new customer generation, et cetera? And then how do we triangulate that strength with your guide in Q2 of, I guess, relatively flat sequential growth on total revenue?
spk09: Yeah. Hi, Derek. Thanks for the question. You know, so maybe the first part of that question, I think we're seeing, you know, actually a couple of different factors, right? We are seeing nice growth from new customers. But specifically in Q1, too, we saw some nice real expansion with our existing customer base, so to touch on your point. And getting to that 110% of NRR, that was a nice driver and also drove some of that SaaS expansion as well. So I think we're seeing it really across the platform. I wouldn't say it's just coming from one particular product or even migration, as you suggested. It's really across the spectrum, which is nice. And again, both new customers and then again, seeing nice growth from the existing customer base, which is nice, that expansion. And then I think when we think about Q2 in terms of, you know, where we ended Q1 and what we're thinking about for Q2, I think we're really pleased with the guidance that we have out there. And in terms of really setting the stage for the full year, you know, raise that we put out, we feel comfortable about that. We went from really revenue forecast about 15% year-over-year growth to 17%. We're increasing the ARR growth from 7% or actually 20% to 21%. So we feel good about the guidance that we put out there. We also, you know, we've talked about this before. We do have this flux between SAS and term and the impact that that has on revenue. We did see in Q1 that there was a significant amount of SAS, and that can fluctuate from quarter to quarter. So we're mindful of that as we think about setting guidance there. specifically for Q2, but even thinking about the full year. So, again, we're excited. We think the guidance that we put out there is good, and we feel very comfortable about achieving that.
spk14: Well done. Thank you.
spk02: Thank you. And the next question comes from Brett Novlock with Cantor Fitzgerald.
spk20: Hi, guys. This is Tommy Shinsky on for Brett. Congrats on another solid quarter. I guess last quarter we talked a little bit about the MSP approach to the SMB sector and how that's kind of shielded you from a lot of the SMB headwinds that the SaaS industry is kind of seeing as we head into 2024. I guess, is there any update to if you're seeing any SMB weakness or maybe even some budget constraints from the MSPs themselves?
spk10: Yeah, that's a great question. So MSP segmentation is our approach to SMB segment. For Microsoft, SMB segment is well over 40% of their total revenue. So for us today, it's just under 20% of our total recurring. It's still the fastest growing segment for us. We see a level of abstraction. So we don't, because what we do is we offer essentially a management platform for these managed service providers to enable their businesses to scale to manage hundreds, if not thousands of Microsoft Cloud tenants behind the scenes. So from that perspective, it's a different layer. And from there, we actually continue to see very strong demand. We do have a very differentiated platform approach in the Microsoft Cloud play with information management. and we continue to see very strong demand from MSPs. Before, it was really focused around data protection, data integration, and control. And now, a very, very hot topic, of course, is Microsoft Copilot Readiness. Policy Insight is the product, and Opus are the products, the hero SKUs now among the MSP community. So yeah, we actually don't see much softness in that segmentation. Perhaps, as I indicated before, it's because we're really targeting and enabling the MSP business to grow. And for us, SMB, the small, medium business segment, is still just 20% are recurring, while the overall market is at least 40% of the total market. So still a tremendous headwind and headroom and a green space for us to grow into. Thank you.
spk19: Awesome. Thanks, and congrats again, guys. Thank you.
spk02: Thank you. And the next question comes from Nahal Chokshi with Northland Capital Markets.
spk08: Thanks, and congrats on the strong quarter, strong raise. Your net new ARR was up 29% for the March quarter. How are you thinking about the net new ARR yearly growth as we move through the remainder of the year here?
spk09: Yeah, so I think our guidance now that we just put out implies 55 million of net new ARR for the year, and that'll be up about 10% over, you know, for the full year, year over year. So I think when you think about it over the course of the year, on the net new, that's kind of how we're expecting the full year to shake out.
spk08: Right. I guess what I'm trying to drive at is that I think that adds up to about 46 million net new ARR for the remainder of three quarters compared to 42 in the comparable year-ago period. So that's up about 10% year over year. and yet you just hit 30%. And so the question here is that what's behind what appears to be a deceleration in the net new ARR that you're expecting?
spk09: Well, I think there's a couple factors. I wouldn't say it's deceleration, but if you think about Q1 last year, Nihal, when we were sitting here, we had a a relatively low Q1 last year. It's definitely the weakest part of last year, and it's definitely a comp that we're comparing against. So we're pleased with the growth at 29%, but it's also coming off a weak Q1 in particular. So again, we're We're pleased with the guidance that we have out there. I wouldn't call it a deceleration. We had strong performance in Q2 through Q4 of last year. And again, I think on that net incremental ARR, we feel good about that. And that gets us to our, you know, annual target of that 21%, which again, for the year, we're focused on achieving that growth rate and feel good about that guidance we have out there.
spk08: Great. Yep. And by the way, I mean, 10%. incremental ARR growth for the remainder of years. Nothing to cry about. That's very good by itself anyhow. TJ, thanks for the customer examples and especially the concrete example around how Opus is helping customers get their data Gen AI ready. Can you give us a sense as to what does the ARPU add as customers look at leveraging AppPoint's the capabilities with respect to getting their data gen AI ready?
spk10: I know that's a great question. As we mentioned earlier, there's still a ton of experimentation happening. I think you probably also hear from other hyperscalers, the expectation for a real revenue evidence monetization will really happen probably in 2025. This year, it's really because a lot of, I was just recently at Microsoft Redmond headquarters around executive debriefing. A lot of the challenge with AI deployment is it's actually a change management. It has to drive from business owners, business C-levels versus just the IT conversation. So still a ton of experimentation and making sure that there's solid, concrete business ROI. before folks are willing to really deploy this enterprise-wide, really deploy a massive amount of budget towards it. So it's experimentation phase. We see a ton of that, and that adds, obviously, to the number of increases of conversations and opportunities in the pipeline. But I would say the real dollar value, we won't see it most likely until next year.
spk13: Great. Thank you.
spk02: Thank you. And the next question comes from Jason Ader with William Blair.
spk06: Yeah, thank you. Good afternoon, guys. I wanted to ask about multi-product, multi-suite customers. I know that you've talked a little bit about that. I don't know if you have specific metrics for us, but maybe you can just talk to any momentum there. And then beyond that, if you could build upon that and just Maybe talk about the relative growth rates of each of your three suites and any color commentary on, you know, what is happening within each of those product suites.
spk05: Yeah, so maybe the first part of that question, I think we provide
spk09: you know, the suites and the, you know, kind of multiple products and multiple suites within the customer. I think with that metric we're providing annually. But I will say that, Jason, in terms of what we saw in Q2, we did see some, again, very nice growth from the existing customer base. Most of the upselling that we see or the sales to existing customers is not so much more of the same product, but it is cross-sell motion. So we had a very strong quarter in Q2 in terms of where that landed. In terms of our annual disclosure around products, we've got about 50% of our customers that are on two or more products and about 24% that are four-plus products. And then when we talk about in-suites, it's roughly about 25% of our customers on two-plus suites. That's that annual metric that we're providing. We'll again provide that next year. But again, we saw a nice progression in upsells in Q1, and that led to that NRR of 110, which was, again, a very strong quarter for us.
spk06: And then just the rank order of the growth rates by suite and then color commentary. Maybe I'd love to hear DJ talk to just the kind of dynamics in each of those three suites and, you know, what's going really well.
spk05: Yeah, so...
spk10: Overall, the upsell, we're very pleased with that. We saw a 25% increase in upsell deals in Q1 compared to this time last year. And also deals over $100,000, we saw a 40% increase compared to this time last year. Now, in terms of suites, as I mentioned earlier, it's really the control suite that really focuses on information management. and access control that's the most active. Again, in terms of dollar value though, we are seeing, again, smaller deployments because we do do by subscription and C count, marrying that of Microsoft's license model for their cloud. So because of that, the experimentation across accounts are still focused on smaller focus groups, business leaders to roll out general AI capabilities. So there's definitely that happening, and we do have a set playbook for co-pilot readiness that actually leverages all three suites because people need to prepare, secure, and optimize their data estate. So step one is prepare is to centralize and enhance data integrity, and step two is secure that is identify and also enforce content policies. And the last step, optimize, is to go forward with governance and automation. You have to do both at the input of the AI model as well as the outputs because now almost 10% of data generated are being done by GenAI. So the output also needs to be very much controlled and filtered and moderated because we all know with large language models that you have inherent about 10% hover around that of hallucination that's happening. So because output oftentimes is also used as input to data models to capture and model concept drift as the business environment evolves for large enterprises. So you always have to have that software, governance, and man-in-the-middle type of approach to ensure that this continuous feedback to the model is managed and measured and optimized. So, in fact, it's actually driving all three of our product suites.
spk04: Thanks, guys. Good luck.
spk03: Thank you. And the next question comes from Gabriella Borges with Goldman Sachs.
spk17: Hi, good afternoon. Thank you. TJ, AvePoint has this unique vantage point in two ways. One is the savings that you enable for your customers when they think through things like storage optimization. And the other is the projects that you have visibility into from an AI deployment standpoint. So my question for you is, how is that push towards cost optimization trending in some of your larger customers relative to last year. And the second part of the question is, where is the budget for some of these AI projects coming from? And can AppPoint maybe connect the two pieces where you're enabling savings in one area of the business, but then go towards funding AI projects in another area of the business?
spk10: That's a great question, Gabriella. So we continue to see consolidation. um, uh, plays from customers where they, they like, uh, platform vendors. They like, um, less, uh, singular products and less vendor. Um, and this decreases risks and allow them to focus on the high quality platform providers. So that, um, uh, economics focus and, and, uh, platform approach continues into this year. Um, so we do, as you mentioned, um, give customers significant savings. Um, one of the, uh, important value we provide in the Microsoft cloud ecosystem is to help our customers maximize ROI, uh, return on investment on their existing cloud investments. Um, so we ourselves actually consume about a hundred million dollars for Azure over a three year period, and that's growing very rapidly. And from that kind of economic scale, we're able to drive a further savings for our customers. So storage optimization is just one such savings. The others are also be able to provide consistent data management capabilities across different license type tiers, as well as multi cloud. I can't emphasize enough that today's world, customers are not only on one hyperscalers, in fact, Most enterprise customers, including government agencies, have a mandate to do business continuity reasons. So they actually intentionally have multiple cloud vendors just to ensure that they have business resiliency. And the second part of the question is the budget bucket. It is true, increasingly, the conversations are shifting towards the business budget versus the IT budget. If you only look at pure IT budget, it's very hard to say, hey, I'm going to spend the extra $30 per user per month just on generic capabilities. From an IT infrastructure planning perspective, considering that that's equivalent to what more than most customers pay for entirety of... Office we should have today with teams with office with email with, you know, one terabyte of one drive, etc. Combined. However, when you take it into a business context when you're driving business outcomes. That it's much easier and different conversation. And this is where we're seeing very, very aggressive and active experimentation. across the board to drive that business our eyes. So yes, while the copilot experimentation happening are limited to smaller footprints within the overall user population in companies. But those user population today are all your power, effectively power users among business community, you know, your head of sales, your head of marketing, head of HR, CFOs. So when you have that kind of conversation, it's a very different conversation than just pure IT CIO level conversation. So yes, it is actually a very different budget conversation altogether.
spk17: That makes sense. And then given some of the dynamics we were just walking through and the newer products that Outpoint has in its portfolio, Talk to us about how the go-to-market is evolving both from a cross-sell standpoint and then from a customer education standpoint as well. How do you intersect some of the problems that you're solving with what the customers are planning for 2024? How does that conversation get catalyzed?
spk10: Yeah, that's a great question. So what's really interesting is AppLine has been in the business of information management, data management for the last 20 plus years. It's a very easy conversation with highly regulated industry customers because that just policy and regulations demands it. But now with Gen AI rollout and everyone wants to take advantage of AI capabilities and disruptions to enhance and innovate on our business, the market is educating them very, very quickly the need for a very solid and clean data state. So otherwise it's a, you know, it's a trash in trash out issue because it is not magic, right? So AI models are heavily, heavily rely on your corporate data estates when you do fine tunings on existing large language models to take advantage of these new technology and your existing domain specific industry data. so that your AI capability is not just a summer intern type of knowledge base, but rather 20-year decades worth of industry knowledge in your specific company and domain. So with that, the awareness of data and information management and governance becomes the forefront across all industries. So that's really the sea change that we see before we have to educate customers on the need for data management and governance and security And today, they're actually coming to us to ask for that. And as I mentioned with our playbook around what we call oftentimes work with regional partners and Microsoft regional teams around co-pilot readiness is that three-step process of prepare, secure, and optimize, and continually optimize and monitor your ongoing data usage to train and refine your models that actually brings forth all of our product set and our platform. And that also further highlights the need for a platform. You can no longer just offer point products that's just in one aspect of the information management lifecycle or just only focus on data protection. You have to really consider the entire lifecycle and data management and continuous governance cycle to be successful. So it elevates the importance of our platform even more.
spk18: Very interesting. Thank you.
spk02: Thank you. That concludes our question and answer session. I would like to turn the conference back over to CEO T.J. Zhang for any closing comments.
spk05: Thank you.
spk10: The rate of innovation always swept our sector. It's gaining even more momentum. Powered by the rise of AI, the energy was tangible during my recent visit with fellow Microsoft IGN partners at the Executive Briefing Center in Redmond, as I mentioned earlier. It was an inspiring experience to be part of such a massive technology ecosystem as we embrace the AI transformation wave together. At that point, we're excited by the transformational potential of AI and we're equally aware of the challenges it poses to organizations around the world. We're ready to capture the many opportunities ahead of us and we look forward to a strong 2024. Thank you again for joining us today, and we look forward to speaking with you more this quarter.
spk02: Thank you. The Outpoint Conference has now concluded. Thank you for attending today's presentation. We now disconnect. Thank you. you Thank you. Bye. Thank you. Bye. Good day and welcome to the Ivey Point Inc. Q1 2024 earnings call. All participants will be in the synonym mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star then one on your telephone keypad. To withdraw your question, please press star then two. Please note, this event is being recorded. Now I'd like to turn the conference over to your host today, Jamie Rustia, Vice President, Investor Relations.
spk03: Please go ahead.
spk05: Thank you, Operator. Good afternoon, and welcome to AvePoint's first quarter 2024 earnings call.
spk10: With me on the call this afternoon is Dr. T.J. Jang, Chief Executive Officer, and Jim Cassie, Chief Financial Officer. After preliminary remarks, we will open the call for a question and answer session. Please note that this call will include forward-looking statements that involve risks and uncertainties that could cause actual results to differ materially from management's current expectations. We encourage you to review the safe harbor statements contained in our press release for a more complete description. All material in the webcast is the sole property and copyright of AvePoint with all rights reserved. Please note this presentation describes certain non-GAAP measures, including non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating income, and non-GAAP operating margin, which are not measures prepared in accordance with U.S. GAAP. The non-GAAP measures are presented in this presentation as we believe they provide investors with a means of understanding how management evaluates the company's operating performance. These non-GAAP measures should not be considered in isolation from, as substitutes for, or superior to, financial measures prepared in accordance with U.S. GAAP.
spk09: A reconciliation of these measures to the most directly comparable GAAP financial measures is available in our first quarter 2024 earnings press release, as well as our updated investor presentation and financial tables, all of which are available on our investor relations website. With that, let me turn the call over to TJ.
spk10: Thank you, Jamie. And thank you to everyone joining us on the call today. Our first quarter was a very strong start to the year as we outperformed our guidance for total revenue and non-GAAP operating margin while delivering strong growth in total and net new ARR. Our performance was again driven by the robust capabilities of our platform. as well as a growing recognition among customers and partners of the need, now more important than ever, to build a strong data foundation. Doing so will empower them to govern their mission-critical information assets, optimize operational costs, boost workplace efficiency, and foster more insightful data-driven decision-making. While these goals have always been top of mind, they're now more critical than ever as organizations around the world seek to leverage generative AI to unlock business value and gain a competitive advantage. It's this dynamic I would like to discuss today with two areas of focus. First, the challenges and obstacles organizations face in adopting AI, primarily due to data security issues that prevent a comprehensive strategy to manage your data estate. And second, the customer demand for AI to improve productivity and the overall employee experience. Along the way, I'll highlight some key customer wins in Q1 that demonstrate how we solve these challenges and close by touching our ongoing investments to innovate in this dynamic business environment. I will then turn over to Jim to discuss our Q1 results and updated financial guidance. So let's jump in. It's no surprise Companies everywhere want to incorporate AI into their businesses. I recently had the privilege to keynote the SkillsFuture SG Training and Adult Education Conference in Singapore. In speaking with the many CXOs in attendance, it was clear the ambition to use AI to transform upscaling is palpable. But the elephant in the room is the concern that their data is not ready for AI. These conversations align with the findings inaugural AI and information management report, which we published a few weeks ago. Our report surveyed nearly 800 organizations globally and find that 83% plan to increase their AI spending this year, with 60% intending to allocate at least a quarter of their technology budget to AI in the next five years. However, our survey also confirmed a significant delta between these ambitious plans and the reality facing these organizations. Simply put, they're not ready to deploy effective AI strategy because their data estate are not in good order. This is where our confidence platform comes into play. By bolstering organizations' data security postures, providing robust cybersecurity measures, offering comprehensive control and visibility across the digital workplace, and delivering intelligent data insights through automation. By leveraging all our platform has to offer, customers can realize a secure and compliant digital environment that also improves the employee experience and then build on this foundation with a meaningful AI strategy. But without taking these steps to solidify their data estates, the challenges business face are amplified when incorporating AI, particularly around data security and data governance. According to recent research from Gartner, 72% of organizations believe oversharing and exposing sensitive information is the biggest risk when deploying generative AI applications, such as Copilot for Microsoft 365. The AppPoint Confidence Platform can mitigate these risks by helping companies understand the quality of the data AI relies on controlling permissions, and rapidly setting up proper access controls. In the health and life sciences industry, for example, we worked with a leading US-based medical technology company in the quarter to ensure its data was ready for AI as they prepared to deploy a co-pilot for Microsoft 365. With AppOint policies, AppOint cloud governance, and AppOint MyHub, the company is drastically reducing the risk of exposing sensitive information, streamlining their workspace policies, and securing data access so the company's 15,000 employees can utilize Copilot. Our study also find that before implementing AI, 71% of organizations were concerned about data privacy and security, and 61% were worried about the quality and categorization of their internal data. But despite these concerns, many forge ahead in the flawed belief that their existing information management strategy will suffice. Specifically, our report find nearly half of the organizations lack basic measures, such as archiving and retention policies. And just 29% of organizations use automation. These shortcomings are even more glaring when compared to the size and volume of data our customers need to secure. Driven by the relentless growth of data for many years, more than 40% of the companies today manage at least 500 petabytes of data, and they're seeing that growth accelerate due to AI. Addressing the challenges related to data growth and sprawl has always been a key use case for AppPoint and led to a new customer win in Q1 with a Germany-based real estate firm with over 130,000 tenants and 1,500 employees. The firm turned to AppPoint's secure backup solution to protect its growing data across Microsoft 365, EntraID, Power Platform, and to rapidly identify crucial data sprawl and storage optimization challenges with AppPoint Opus. With these critical AppPoint solutions, the customer can now quickly and intelligently archive its data and enhance its data governance and cyber resilience posture. As noted in our report, We believe the most effective approach for all companies is to establish a robust information management strategy from the outset. Because organizations with mature information management strategies are one and a half times more likely to realize benefits from AI than those with less mature strategies. For example, Let's take a look at the CPG industry, where nearly half of companies are facing challenges collecting and integrating the volume data needed for successful AI adoption. This is largely due to data fragmentation across large number of SKUs, expansive supply chain and warehousing networks, and complex product categories. In Q1, we expanded our relationship with one of the largest CPG companies in the world to streamline its information management approach with the purchase of AppPoint Opus. Already an existing customer with a number of AppPoint solutions and a growing data estate, Opus will streamline data management policies for their 123,000 users. providing better visibility into data utilization, improve data quality, and lower the risk of breaches. We know a healthy data state is essential to effective AI strategy, and effective AI strategy obviously makes good business sense in creating a more secure organization, reducing cost, and addressing macro challenges. But one additional benefit of effective AI strategy is the improvement of the overall employee experience For example, Gartner finds AI can drive productivity gains by up to 20%. Why does that matter? Research show that more than 60% of a typical workday is lost to repetitive and mundane tasks that knowledge workers spend 25% of their time searching for information, and they use the average of six to eight apps to complete a single process. If AI can successfully mitigate these employee frustrations, companies can retain talent and reduce turnover, further strengthening the organization. Our best-in-class abilities to solve these problems for many years have established a strong competitive moat, and it's why we continue to innovate and invest in further enhancements for our customers and for the AppPoint team. Our AppPoint AI program aimed at integrating AI into everything we do, continues to progress with internal and external applications of AI. One example is our ChaiGraph product, where we recently introduced new advanced analytics capabilities for Copilot for Microsoft 365. We're proud to be first to market with this offering to support Copilot, which enables companies to identify areas of high collaboration to better prepare for Copilot readiness. This is just the latest of our AI readiness solutions for organizations to prepare, secure, and optimize data, which collectively will enable them to fully take advantage of AI in the workplace. In closing, successful AI deployments require strong and healthy data states, which in turn mandates a robust data management strategy. As companies become increasingly aware of this, we have a massive opportunity to drive AI adoption in the years to come. underpinned by our platform technology and our experience solving the most urgent challenges facing organizations around the world. I'm excited for the years ahead, and I want to thank the entire Apple team for their tireless efforts and dedication. Our Q1 results are another strong step forward, and we're laser-focused on continuing execution and capitalizing on the growing demand for our platform. With that, let me turn the call over to Jim.
spk09: Thanks, TJ, and good afternoon, everyone. Thanks for joining us today. As we review our strong first quarter results today, let me remind you that unless otherwise noted, I'll be referring to non-GAAP metrics. For the first quarter ended March 31st, 2024, total revenues were $74.5 million, up 25% year over year and above the high end of our guidance. Within total revenue, first quarter SAS revenue was $51.3 million and grew 44% year over year. And in Q1, SAS comprised 69% of total revenues compared to 60% a year ago. SAS continues to be our fastest growing revenue segment with 44% year over year growth representing our highest in eight quarters. In addition, our other revenue lines continue to perform in line with our expectations and commentary. Term license and support, as well as maintenance revenue, declined year over year, both in dollars and as a percentage of total revenue. At the same time, services revenues grew 8% year over year, but declined as a percentage of revenue to 14% for Q1. And because services represents our only non-recurring business, 86% of our total Q1 revenues were recurring, our highest ever percentage. Our strong SAS performance is also evident as we look at our results from a regional perspective, where SAS revenue growth was above 40% in every region. In North America, SAS revenues grew 42% year-over-year and represented 77% of total North America revenues, which in turn grew 22% year-over-year. In EMEA, SAS revenues grew 46% year-over-year and represented 81% of total EMEA revenues, which in turn grew 17% year-over-year. And in APAC, SAS revenues grew 47% year-over-year and represented 45% of total APAC revenues, which in turn grew 40% year-over-year. Last quarter, we began disclosing our regional ARR performance as these growth rates provide a better view of the underlying momentum of the business everywhere we operate. We were again pleased with the year-over-year growth we saw in Q1. as North America ARR grew 22 percent, EMEA ARR grew 27 percent, and APEC ARR grew 27 percent. Once again, each region was a strong contributor to our overall performance, with their respective ARR growth rates in line with the total ARR growth we reported on a consolidated basis. Continuing now with total ARR and other key metrics we regularly assess. As of March 31st, 2024, total ARR was $274.5 million, representing year-over-year growth of 23%. As a result, net new ARR in Q1 was $10 million and grew 29% year-over-year. Additionally, we ended the first quarter with 560 customers with ARR of over $100,000. an increase of 20% from the prior year. As of the end of Q1, 51% of total ARR came through the channel compared to 48% a year ago. And for Q1 specifically, 62% of our incremental ARR came through the channel compared to 65% for Q4 of 23 and 56% in Q1 of 2023. As we discussed, the channel contribution to our incremental ARR will fluctuate from quarter to quarter, but we expect the channel contribution to total ARR to continue increasing each quarter. Turning now to our customer retention rates, where we continue to make progress toward our medium-term goals, which to remind you are 90% plus for GRR and 110% to 115% for NRR. Adjusted for the impact of FX, our trailing 12-month gross retention rate for the first quarter was 87%, consistent with our performance in 2023. And we are pleased that our FX-adjusted net retention rate for the first quarter was 110% compared to 106% a year ago and to 109% in Q4 of 2023. On a reported basis, Q1 GRR was 86% in line with the 86% we reported in Q4 2023. Q1 NRR was 110% compared to 108% in Q4 of 2023. Turning back to the income statement, gross profit for Q1 was $55.2 million, representing a gross margin of 74.1% compared to 71.5% in Q1 of 2023. The improvement in our gross margin is a result of improved SAS margins as well as our product mix. as we had more SAS revenue and less low-margin services revenue as a percentage of our overall revenue this quarter versus a year ago. Moving down the income statement, operating expenses for Q1 totaled $48.6 million, or 65% of revenue, compared to $42.9 million, or 72% of revenues, a year ago. As a result, Q1 operating income was $6.6 million, or an operating margin of 8.9%. While Q1 non-GAAP operating income was well ahead of our guidance, I would point out that approximately $1.5 million of expenses we had expected for Q1 shifted to Q2 and the second half of the year. And this is reflected in our updated guidance, which I will cover shortly. But even after adjusting for this, Q1 operating income would have come in comfortably above the high end of our guidance as our commitment to profitable growth and our sustained focus on expense management again allowed us to realize more of the substantial embedded leverage in our business. Turning to the balance sheet and cash flow statement, we ended the first quarter with $219.3 million in cash and short-term investments. For the three months ended March 31st, 2024, cash generated from operations was $7.8 million, while free cash flow was $7.3 million. This compared to cash generated from operations of $1.3 million and free cash flow of $1 million in the first quarter of 2023. During the three months ended March 31st, we repurchased 1.8 million shares for a total cost of approximately $13.7 million. I would now like to turn to our financial outlook, where for the full year, we are pleased to raise our expectations for total ARR, total revenue, and non-GAAP operating income. For the second quarter we expect total revenues of 73.8 million to 75.8 million dollars or approximately 15% yearly year growth at the midpoint. We expect non-GAAP operating income of 3.6 million to 4.6 million dollars. For the full year, we now expect total ARR of $316.8 million to $321.8 million, or approximately 21% year-over-year growth at the midpoint. We now expect total revenues of $314.3 million to $320.3 million, or approximately 17% year-over-year growth at the midpoint. And lastly, we now expect full year non-GAAP operating income of $30 million to $32 million or an operating margin of 9.5 to 10%. And on a rule of 40 basis, which for AvePoint is the sum of our ARR growth and non-GAAP operating margin, our updated guidance reflects a 31 compared to the 29 that we initially guided for the year in February. with each component contributing equally to the increase. In summary, Q1 was a strong start to 2024, and we are excited for another year of continued execution and capitalizing on the substantial long-term opportunity ahead of us. Thanks for joining us today, and with that, we would be happy to take your questions. Operator?
spk02: Yes, thank you. We will now begin the question and answer session. To ask a question, you may press star then 1 on your telephone keypad. If you're using a speakerphone, please pick up your handset before pressing the keys. If any time any question has been addressed and you would like to withdraw it, please press star then 2. At this time, we will pause momentarily to assemble the roster. And the first question comes from Derek Wood with TD Cowan.
spk12: Great, thanks. Congrats on a strong quarter. CJ, I'll start with you. You talk about the rollout of the co-pilot analytics offering within TiGraph. What was just made available? What's the feedback from customers? And I imagine dollars tied to this will start small, but I'd be curious if marketing this kind of tool could draw incremental interest for some of your core offerings, whether it's cross-selling the base or generating new customers.
spk10: Yeah, great question. The rollout for TIGRAPH for Office 365 Co-Pilot is the first such solution in the market where we actually help customers zone in onto the high density collaboration areas and data estate to focus their effort around co-pilot readiness. Around the world, we have seen tremendous activities of companies across the board to actively experiment with Gen-AI and traditional AI capabilities And Microsoft has done a fantastic job in commoditizing and democratizing AI approach, especially offering Copilot to well over 500 million users on MCC5. So a ton of experimentation. We haven't seen massive enterprise-wide deployment yet. So this is why the solution like TyGraph for Copilot from AppPoint that's released just recently this quarter, is the way to zoom in onto the specific areas of collaboration and user groups. So this allows them to, in pilot mode, in essentially POC mode, in small group settings, to really experiment and take advantage of the power of Gen AI. And as we mentioned in our prepared remarks, a very important aspect of making sure that your AI deployment strategy works is to have a very confident and solid trust in your data state. So a lot of that preparation work goes into preparing, making sure that you have the right privilege, right access, right information management, life cycle, life control, as well as removing much of the redundant, out-of-date, trivial data. And what HighGraph what CodePilot does is actually allow you to not just look at your entire data state, which will be over 500 petabytes for a lot of customers, zone into the specific areas and user groups that you start with and to get the bigger ROI right away. So it's a very unique product set. And you're right, we see robust pipeline building from all these information management requirements.
spk12: Very interesting. Thanks. And one for Jim, 44% SaaS growth, really impressive. And even if I look at sequential growth, it was double digits. We haven't seen that since I think first half 21. Can you talk about what's driving that inflection in SaaS? Is there been a pickup in on-prem migrations or are there other factors like more cross-selling, new customer generation, et cetera? And then how do we triangulate that strength with your guide in Q2 of, I guess, relatively flat sequential growth on total revenue?
spk09: Yeah. Hi, Derek. Thanks for the question. You know, so maybe the first part of that question, I think we're seeing, you know, actually a couple of different factors, right? We are seeing nice growth from new customers. But specifically in Q1, too, we saw some nice real expansion with our existing customer base, so to touch on your point. And getting to that 110% of NRR, that was a nice driver and also drove some of that SaaS expansion as well. So I think we're seeing it really across the platform. I wouldn't say it's just coming from one particular product or even migration, as you suggested. It's really across the spectrum, which is nice. And again, both new customers and then again, seeing nice growth from the existing customer base, which is nice, that expansion. And then I think when we think about Q2 in terms of, you know, where we ended Q1 and what we're thinking about for Q2, I think we're really pleased with the guidance that we have out there. And in terms of really setting the stage for the full year, you know, raise that we put out, we feel comfortable about that. We went from really revenue forecast of about 15% year-over-year growth to 17%. We're increasing the ARR growth from 7% or actually 20% to 21%. So we feel good about the guidance that we put out there. We also, you know, we've talked about this before. We do have this flux between SAS and term and the impact that that has on revenue. We did see in Q1 that there was a significant amount of SAS And that can fluctuate from quarter to quarter, so we're mindful of that as we think about setting guidance specifically for Q2, but even thinking about the full year. So, again, we're excited. We think the guidance that we put out there is good, and we feel very comfortable about achieving that.
spk14: Well done. Thank you.
spk02: Thank you. And the next question comes from Brent Novolog with Cantor Fitzgerald.
spk20: Hi guys, this is Tommy Shinsky on for Brett. Congrats on another solid quarter. I guess last quarter we talked a little bit about the MSP approach to the SMB sector and how that's kind of shielded you from a lot of the SMB headwinds that the SaaS industry is kind of seeing as we head into 2024. I guess, is there any update to if you're seeing any SMB weakness or, you know, maybe even some budget constraints from the MSPs themselves?
spk10: Yeah, that's a great question. So MSP segmentation is our approach to SMB segment. For Microsoft, SMB segment is well over 40% of their total revenue. So for us today, it's just under 20% of our total recurring. It's still the fastest growing segment for us. We see a level of abstraction, so because what we do is we offer essentially a management platform for these managed service providers to enable their businesses to scale to manage hundreds if not thousands of Microsoft Cloud tenants behind the scenes. So from that perspective, it's a different layer. And from there, we actually continue to see very strong demand We do have a very differentiated platform approach in the Microsoft Cloud play with information management. And we continue to see very strong demand from MSPs. Before it was really focused around data protection, data integration, and control. And now a very, very hot topic, of course, is Microsoft Copilot Readiness. Policy Insight is the product, and Opus are the products, the hero skills now among the MSP community. So, yeah, we actually don't see much softness in that segmentation. Perhaps, as I indicated before, it's because we're really targeting and enabling the MSP business to grow. And for us, SMB, the small, medium business segment, is still just 20% are recurring, while the overall market is at least 40% of the total market. So still tremendous headwind and headroom and a green space for us to grow into. Thank you.
spk19: Awesome. Thanks, and congrats again, guys. Thank you.
spk02: Thank you. And the next question comes from Nahal Chokshi with Northland Capital Markets.
spk08: Thanks, and congrats on the strong quarter, strong raise. Your net new ARR was up 29% for the March quarter. How are you thinking about the net new ARR, your growth as we move through the remainder of the year here?
spk09: Yeah, so I think our guidance now that we just put out implies 55 million of net new ARR for the year, and that will be up about 10% for the full year, year over year. So I think when you think about it over the course of the year on the net new, that's kind of how we're expecting the full year to shake out.
spk08: Right. I guess what I'm trying to drive at is that I think that adds up to about 46 million net new ARR for the remainder of three quarters. compared to 42 in the comparable year-ago period. So that's up about 10% year-over-year, and yet you just hit 30%. And so the question here is that what's behind what appears to be a deceleration in the net new ARR that you're expecting?
spk09: Well, I think there's a couple factors. I wouldn't say it's deceleration, but if you think about Q1 last year, Nihal, when we were sitting here, we had a relatively low Q1 last year. It's definitely the weakest part of last year, and it's definitely a comp that we're comparing against, so we're pleased with the growth at 29%, but it's also coming off a weak Q1 in particular. So again, we're We're pleased with the guidance that we have out there. I wouldn't call it a deceleration. We had strong performance in Q2 through Q4 of last year. And again, I think on that net incremental ARR, we feel good about that. And that gets us to our, you know, annual target of that 21%, which again, for the year, we're focused on achieving that growth rate and feel good about that guidance we have out there.
spk08: Great. Yep. And by the way, I mean, 10%. incremental ARR growth for the remainder of years. Nothing to cry about. That's very good by itself anyhow. TJ, thanks for the customer examples and especially the concrete example around how Opus is helping customers get their data Gen AI ready. Can you give us a sense as to what does the ARPU add as customers look at leveraging AppPoint's the capabilities with respect to getting their data gen AI ready?
spk10: I know. That's a great question. As we mentioned earlier, there's still a ton of experimentation happening. I think you probably also hear from other hyperscalers the expectation for a real revenue evidence monetization will really happen probably in 2025. This year, it's really because a lot of, I was just recently at Microsoft Redmond headquarters around executive debriefing. A lot of the challenge with AI deployment is it's actually a change management. It has to drive from business owners, business C-levels versus just the IT conversation. So still a ton of experimentation and making sure that there's solid concrete business ROI before folks are willing to really deploy this enterprise-wide, really deploy a massive amount of budget towards it. So it's experimentation phase. We see a ton of that, and that adds obviously to the number of increases of conversations and opportunities in the pipeline. But I would say the real dollar value, we won't see it most likely until next year.
spk13: Great. Thank you.
spk02: Thank you. And the next question comes from Jason Ader with William Blair.
spk06: Yeah, thank you. Good afternoon, guys. I wanted to ask about multi-product, multi-suite customers. I know that you've talked a little bit about that. I don't know if you have specific metrics for us, but maybe you can just talk to any momentum there. And then beyond that, if you could build upon that and just Maybe talk about the relative growth rates of each of your three suites and any color commentary on, you know, what is happening within each of those product suites.
spk05: Yeah, so maybe the first part of that question, I think we provide
spk09: you know, the suites and the, you know, kind of multiple products and multiple suites within the customer. I think with that metric we're providing annually. But I will say that, Jason, in terms of what we saw in Q2, we did see some, again, very nice growth from the existing customer base. Most of the upselling that we see or the sales to existing customers is not so much more of the same product, but it is cross-sell motion. So we had a very strong quarter in Q2 in terms of where that landed. In terms of our annual disclosure around products, we've got about 50% of our customers that are on two or more products and about 24% that are four-plus products. And then when we talk about end suites, it's roughly about 25% of our customers on two-plus suites. That's that annual metric that we're providing. We'll again provide that next year. But again, we saw a nice progression in upsells in Q1, and that led to that NRR of 110, which was, again, a very strong quarter for us.
spk06: And then just the rank order of the growth rates by suite and then color commentary. Maybe I'd love to hear DJ talk to just the kind of dynamics in each of those three suites and, you know, what's going really well.
spk05: Yeah, so...
spk10: Overall, the upsell, we're very pleased with that. We saw a 25% increase in upsell deals in Q1 compared to this time last year. And also deals over $100,000, we saw a 40% increase compared to this time last year. Now, in terms of suites, as I mentioned earlier, it's really the control suite that really focuses on information management. and access control that's the most active. Again, in terms of dollar value though, we are seeing, again, smaller deployments because we do do by subscription and C count, marrying that of Microsoft's license model for their cloud. So because of that, the experimentation across accounts are still focused on smaller focus groups, business leaders to roll out general AI capabilities. So there's definitely that happening. And we do have a set playbook for co-pilot readiness that actually leverages all three suites because people need to prepare, secure, and optimize their data estate. So step one is prepare is to centralize and enhance data integrity. And step two is secure that is identify and also enforce content policies. And the last step, optimize, is to go forward with governance and automation. You have to do both at the input of the AI model as well as the outputs because now almost 10% of data generated are being done by Gen AI. So the output also needs to be very much controlled and filtered and moderated because we all know with large language models that you have inherent about 10% hover around that of hallucination that's happening. So because output oftentimes is also used as input to data models to capture and model concept drift as the business environment evolves for large enterprises. So you always have to have that essentially software, governance, and man-in-the-middle type of approach to ensure that this continuous feedback to the model is managed and measured and optimized. So, in fact, it's actually driving all three of our product suites.
spk04: Thanks, guys. Good luck.
spk03: Thank you. And the next question comes from Gabriella Borges with Goldman Sachs.
spk17: Hi, good afternoon. Thank you. TJ, AvePoint has this unique vantage point in two ways. One is the savings that you enable for your customers when they think through things like storage optimization. And the other is the projects that you have visibility into from an AI deployment standpoint. So my question for you is, how is that push towards cost optimization trending in some of your larger customers relative to last year. And the second part of the question is, where is the budget for some of these AI projects coming from? And can AppPoint maybe connect the two pieces where you're enabling savings in one area of the business, but then go towards funding AI projects in another area of the business?
spk10: That's a great question, Gabriella. So we continue to see consolidation. um, uh, place from customers where they, they like, uh, platform vendors. They like, um, less, uh, singular products and less vendor. Um, and this decreases risks and allow them to focus on the high quality platform providers. So that, um, uh, economics focus and, and, uh, platform approach continues into this year. Um, so we do, as you mentioned, um, give customers significant savings. Um, one of the, uh, important value we provide in the Microsoft cloud ecosystem is to help our customers maximize ROI, uh, return on investment on their existing cloud investments. Um, so we ourselves actually consume about a hundred million dollars of Azure over a three year period, and that's growing very rapidly. And from that kind of economic scale, we're able to drive a further savings for our customers. So storage optimization is just one such savings. The others are also be able to provide consistent data management capabilities across different license type tiers, as well as multi-cloud. I can't emphasize enough that today's world, customers are not only on one hyperscalers. In fact, Most enterprise customers, including government agencies, have a mandate to do business continuity reasons. So they actually intentionally have multiple cloud vendors just to ensure that they have business resiliency. And the second part of the question is the budget bucket. It is true, increasingly, the conversations are shifting towards the business budget versus the IT budget. If you only look at pure IT budget, it's very hard to say, hey, I'm going to spend the extra $30 per user per month just on generic capabilities. From an IT infrastructure planning perspective, considering that that's equivalent to what more than most customers pay for entirety of... office we should have today with teams, with office, with email, with one terabyte, one drive, et cetera, combined. However, when you take it into a business context, when you're driving business outcomes, that is a much easier and different conversation. And this is where we're seeing very, very aggressive and active experimentation across the board to drive that business our eyes. So yes, while the copilot experimentation happening are limited to smaller footprints within the overall user population in companies. But those user population today are all your power, effectively power users among business community, you know, your head of sales, your head of marketing, head of HR, CFOs. So when you have that kind of conversation, it's a very different conversation than just pure IT CIO level conversation. So yes, it is actually a very different budget conversation altogether.
spk17: That makes sense. And then given some of the dynamics we were just walking through, and the newer products that Airpoint has in its portfolio, Talk to us about how the go-to-market is evolving both from a cross-sell standpoint and then from a customer education standpoint as well. How do you intersect some of the problems that you're solving with what the customers are planning for 2024? How does that conversation get catalyzed?
spk10: Yeah, that's a great question. So what's really interesting is AppLine has been in the business of information management, data management for the last 20 plus years. It's a very easy conversation with highly regulated industry customers because that just policy and regulations demands it. But now with Gen AI rollout and everyone wants to take advantage of AI capabilities and disruptions to enhance and innovate on our business, the market is educating them very, very quickly the need for a very solid and clean data estate. So otherwise it's a, you know, it's a trash in trash out issue because it is not magic, right? So AI models are heavily, heavily rely on your corporate data estates when you do fine tunings on existing large language models to take advantage of these new technology and your existing domain specific industry data. so that your AI capability is not just a summer intern type of knowledge base, but rather 20-year decades worth of industry knowledge in your specific company and domain. So with that, the awareness of data and information management and governance becomes the forefront across all industries. So that's really the sea change that we see before we have to educate customers on the need for data management and governance and security And today, they're actually coming to us to ask for that. And as I mentioned with our playbook around what we call oftentimes work with regional partners and Microsoft regional teams around co-pilot readiness is that three-step process of prepare, secure, and optimize, and continually optimize and monitor your ongoing data usage to train and refine your models. that actually brings forth all of our product set and our platform. And that also further highlights the need for a platform. You can no longer just offer point products that's just in one aspect of the information management lifecycle or just only focus on data protection. You have to really consider the entire lifecycle and data management and continuous governance cycle to be successful. So it elevates the importance of our platform even more.
spk18: Very interesting. Thank you.
spk02: Thank you. That concludes our question and answer session. I would like to turn the conference back over to CEO T.J. Zhang for any closing comments.
spk05: Thank you.
spk10: The rate of innovation always switched in our sector. It's gaining even more momentum. Powered by the rise of AI, the energy was tangible during my recent visit with fellow Microsoft IGN partners at the Executive Briefing Center in Redmond, as I mentioned earlier. It was an inspiring experience to be part of such a massive technology ecosystem as we embrace the AI transformation wave together. At that point, we're excited by the transformational potential of AI and we're equally aware of the challenges it poses to organizations around the world. We're ready to capture the many opportunities ahead of us and we look forward to a strong 2024. Thank you again for joining us today, and we look forward to speaking with you more this quarter.
spk02: Thank you. The UpPoint conference has now concluded. Thank you for attending today's presentation. We now disconnect.
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