Manhattan Associates, Inc. ($MANH)

All right. Perfect. Thank you, everybody, for joining us here today. My name is Dylan Becker. I'm the research analyst at William Blair that covers Manhattan. We have Eric, Sanjeev and Linda. So we've got a full quorum here from the Manhattan side of the equation. For all of the necessary disclosures, you can find those on williamblair.com. But thank you all for joining us.

And I know that there's varying levels of familiarity, but there was a release earlier this week, Eric, to just maybe just kind of start the conversation, if you could kind of give us a sense, I know you announced a small reduction in force. Just kind of where you're seeing that operationally? What drove that and how we should kind of be thinking about it?

Sure. Yes. We announced a small reduction in force, about 6% globally. And since I joined Manhattan at the beginning of last year, I've talked about investing more in sales and marketing, but not at the expense of lowering margin. So we -- I've always said we needed to find areas in the business where we could reduce cost and invest more in things that would help us accelerate the cloud growth faster. And one of the key areas that we looked at this time, as Linda stepped into her role as CFO, was we have never, as a company, de-supported any product, and we're not changing that. But we do have a number of legacy products that we have a shrinking number of customers running because we have more and more of those customers moving to our cloud products. So this was about resetting the cost primarily around those legacy products. We can continue to support and give those customers the same great support that they've always had on those products, but we saw an opportunity to reduce some of the spend around those.

Fantastic. Okay. Very helpful background. But now if we kind of zoom out and step back, for those that are maybe not as familiar with the biz, right, could you give us a sense of Manhattan kind of the evolution of supply chain software and digitization and kind of what you guys are seeing and the problems that you're solving?

Yes. So Manhattan has been in the supply chain and commerce software business for more than 30 years and started out really doing a lot of supply chain consulting, and that turned into building systems, and then building on-prem systems, and about a dozen years ago, we started working on building the cloud solution. And for the past 10 years, that's really been the key element of our growth as a company, is that cloud business. And that's what continues to drive our growth, and more than 20% year-on-year growth in the cloud business across warehouse management, transportation management, order management, point of sale and supply chain planning. And then most recently, with putting active AI agents into all of those products, that have really accelerated growth again.

Excellent. And we'll definitely get into each of those components. But maybe from an industry perspective as well too, what's happened kind of from the secular shift around rising complexity, maybe a shift in consumer expectations and sentiment that's driving kind of this digitization or modernization from the industry off of maybe what has otherwise historically been termed as legacy systems?

Yes. And I'll let us jump into this as well. But one of the things that we've seen, you look back over the past year and there's been a lot of noise in the market, right? We've had Liberation Day and tariffs that are on and off. We've had wars. We've had the SaaSPocalypse. But what we've seen from our customers and our prospects is that they're kind of not getting too distracted by the headlines and really recognizing that supply chain is mission-critical and it is strategic and it is one of their differentiators. So that's kind of resulted in we continue to set record sales bookings quarters. You kind of look at the last 2 quarters, calendar Q4 and Q1, were probably the noisiest in terms of war and SaaSPocalypse and what's AI going to do to software. And we had our best Q4 ever followed by our best Q1 ever and carried a lot of momentum into Q2. So we're pretty pleased with where we are.

Yes. I mean, I think, Eric, you are most of it. Just in general, since COVID days, supply chain has become a lot more [ known word ] and I think people are kind of asking us more than asking us less.

Sure. And maybe, Sanjeev, for you, right, you've kind of been the architect of the shift to the cloud in some context, right? How you've seen that evolve, kind of the propensity of the buyers' willingness, if you will, to move to more modern systems?

Yes. So I think if you go back to our journey 10, 12 years back, our biggest strategic decision we made was to invest in a new platform and build it ground-up, compared to everybody else who did a lift-and-shift to the cloud. At that point of time, we kind of decided that we will build everything as API first, headless. And I think as you look into the new AI world, that has played out extremely well for us from that respect. Now the second aspect, if you look through the various things which worked out in our favor well was when we decided to rebuild this thing, functionally, we took a little different approach of building this. So we kind of broke down the traditional type boundaries of WMS, TMS, labor slotting, all of those things. And we looked at it more from a capability perspective, on what is the capability required, and build them as a true micro services architecture, right? So you knew how unified commerce platform, supply chain commerce platform versus a WMS application or a TMS or labor slotting. We still sell them that way, but underlying is a unified platform. The third dimension to that as part of the journey, which kind of really helps, is how we actually build the platform, right? So 2 years back, instead of writing traditional software or enterprise software, we decided to actually write a code generator and not write code directly. This is before AI, this is pre-AI, everything else. And I've shared this data 2 weeks back at our conference, we generate 75% of our code today and have been generating for the last 10 years. We generate about 45 million lines of code every night overall from the codebase. And the reason was not efficiency really when we did this thing. The core driver behind that was how do we keep up as changes come along, right, because we knew that the software will change and the models will change. The biggest thing which I obviously was very sure of is the user interface will completely change because we've seen that happen over the last 30 years, from green screens to mobile UIs, web mobile, the transition has happened over a period of time. So that was kind of one of the drivers when we wrote the generator, saying, okay, we need to be ready for whatever comes next, right? And that has played out pretty well as we get into the AI space. And that I call what is our deterministic spine when we generate, so we can [ bring ] anything else. And that has become a lot easier to kind of plug in AI, the probabilistic spine back into the deterministic spine.

Yes. And it's probably a good going-off point into AI as well too. But how that positions you to kind of balance between those 2, right? There's a lot of rules and configuration and deterministic necessity, if you will, in supply chain, but pairing that with the probabilistic capabilities of some of these models.

Yes. So that's one other difference in approach we kind of took. So in supply chain world, at least our customers will tell us is almost correct is equal to wrong. So we have to be right all the time. And for that, you need to be very deterministic in actions you take, right? If you have to ship 100 somewhere and you ship 101, that can break us up, you cannot kind of really do those things. So when you look at the AI-native companies, they start from the point where you take an LLM, you throw a bunch of stuff at it and it figures out what needs to be done. And that's kind of their starting position. And our starting position always was a very hybrid approach, of you need -- a lot of stuff has to be very deterministic. It doesn't need AI or a probabilistic thing. Now there are certain decision points you need in this workflow where we can throw in an LLM in how it makes decisions. But there are a lot of places where we build outcomes in the past. And those outcomes are as good as anything else, and they have to be used to get a very deterministic answer. So that's been a big difference between our approach versus some of the [ pushes ] you will see being thrown out there. The good news is even if people who kind of threw that approach now are probably aligning with our point of view, is you need to bring in this determinism back into the AI and you cannot throw everything on the probabilistic side of it.

And I think another thing that we've seen in the market over the past several months is, for a long time, you saw companies that were I call it a fear of missing out, right? They were trying to figure out how to use AI. They're creating leaderboards and then we saw the issues of token maxing, right? So now the conversation is how do we make sure we're getting value out of AI and how do we make sure we're not overspending. So we've done a lot of things in our platform to address those things. And you start with our platform, based on the architecture that Sanjeev described is truly AI-native. So we're never talking to our customers about data lakes or data indexing projects or the latency and the security risk that come with all of that. When we're doing AI on our system, we're doing it using the same APIs that a human user would use. So it doesn't introduce any new complexity, any new security threats, et cetera, and it allows a much faster time to value. When we turn on the AI-based agents, they can use them same day. So we're seeing customers get real value in production right away. We've also created a dashboard so they can see that. They can see exactly which agents their teams are using and what value they're getting out of those agents. Again, going back to, am I getting value out of the AI that I'm using? And then finally, these agents are all smart enough to, again, to Sanjeev's point, look at what function should be done by that deterministic backbone of the platform that's based on decades of deep industry knowledge. And where should we be probabilistic? And when we do use probabilistic which LLM should it use, which LLM is most cost effective? So that also addresses the customers' concerns about what value they're getting. And we're not out there trying to help them do token-maxing. We're trying to make sure that they're getting ROI, improving the ROI.

There seems to be a general misconception in the market that you can throw AI at it and it will solve every problem no matter what that is. And I think that's far from the truth. People will realize that it needs a structure. And the deterministic spine build provides that core structure. And then you can kind of go to the brain from the AI, which you can mix it up nicely and create a hybrid system, you'll get the best results.

And you guys are already starting to see this, right, so maybe if we start to talk about your agent deployments, the use cases that the customers are kind of using these agents for the ROI kind of case studies that you're seeing from an early example perspective? And then I guess we'll flow to Linda on monetization of those. But yes, I guess, how are customers kind of deploying agents active today?

So I'll kind of start and then you can kind of add to it. So one is, if you look at supply chain in general, it's an industry which is -- which deals with exceptions all the time. Like most of the supply chain professionals kind of on a day-to-day basis, the core of the job is find an exception, figure out how to solve that exception, resolve that issue and then kind of get going. And sometimes those exceptions can take 3, 4, 6, 7 hours to resolve. And by the time you kind of resolve that, the truck which is leaving that day has already missed the shipment. And that's a pretty big cost. And what we see in some of these use cases is the agents are able to help resolve those exceptions as soon as [indiscernible] really happen. And that makes a huge difference, right? So if there's a problem with order not getting allocated. Somebody who's chasing their allocation can take 2, 3 hours. And by the time they figure out that the inventory is sitting in the receiving dock, the truck is already kind of flat and you missed the shipment. If an agent can figure that out, that this didn't get to a cadence, it's sitting there, and it can actually move that inventory from there to put away, you can make that shipment. And that's a big difference we are kind of seeing already in production, right? So we're seeing customers who are increasing their shipments by anywhere from 6% to 30%, which is a huge number in terms of the overall business metric they can achieve through these things. And this is one example, right? And supply chain is full of all the exception management, and that seems to be the biggest core theme we are seeing. There are other things we are kind of doing with it from a user experience perspective, from a productivity perspective and data insights, but that probably, I would say, from an ROI perspective, has been the biggest benefit people are seeing right now.

And maybe, Linda, for you as well too, as you're kind of deploying more agents in the field, how you guys are thinking about kind of the monetization structure? I know we have the 90-day kind of proof of concept, get it in the hands of customers, let them identify the value and then we'll kind of figure out what that ROI kind of ends up, or I guess, our take rate on that ROI. But how are you thinking about monetization as we start to layer in more agents across the network?

Yes. So from a monetization perspective, we're basically going to be pricing this as a percent uplift on their base subscription, and we're using the pilot program as a way to figure out how much do they actually need. For example, if they only want to go out 1 site or a small number of agents at first, they might be able to select a lower tier from a subscription standpoint. And then as they want to roll that out to more sites or they want to develop more agents, then they could choose to go up from there. So we're giving them the flexibility depending on how much they want to use.

And I'm sure that customers are kind of clamoring once they see the value to kind of deploy more agents. But there's probably a little bit of a [indiscernible] readiness problem that they have to solve for, I guess, as we talk about this modernization. I guess maybe the question more so -- yes, I want to address it, but the question is more so like how is the conversation on the topic of AI incentivizing core system modernization for your warehouse management solutions?

Yes. One part of it is AI, that becomes one of the big [ carrots ] for customers who are not in our modern cloud platform. It gives them one more incentive, one more reason to kind of move to the cloud platform. Now we've stacked up the deck all along. I mean cloud platform is far more richer than our own [indiscernible] I think this can tip the scales easily on why they need to move to this thing. Now you kind of mentioned, and I kind of said before. So one part of this, one big difference from our perspective really is when you start with a cloud platform, you're already ready, right? We can start your day 0 when you say I want to turn this on. Any other approach you will see out there, right, starts with, okay, you got this data, I'm going to create this data lake. I'm going to index this. I'm going to put the security, I'm going to figure out how to kind of get you ready. And that could be a 3, 6-month, 1-year project before you even start using it first time in production. And the approach we took from being API, API for us being headless, right? You can throw these agents and start [ using ] them day 1, right? So I think we took the whole AI readiness question completely out of the mix.

Yes. Yes. No, that makes perfect sense.

And in fact, a few weeks ago at our user conference, the largest ever attended conference by customers and by prospects. And we had a number of customers on one of our keynotes that shared their stories of how they're using our AI and they kind of ranged from 1 customer that have been using it for 3 months to 1 that have been using it for only 3 weeks but already finding that value and already justifying the ROI. So I think that's one of the big differentiators that we've got, is we're able to very quickly turn it on, show value and justify the expense.

And a big initiative since you've come on board as well, Eric, we talked about kind of adding sales capacity and leaning into conversions off of the legacy on-prem base, I guess can you kind of just dive into the nuances of where you're adding kind of structured teams, how you think about those investments kind of ramping and cross-selling, I guess?

Yes. So if you think about what we've done over the past quarters from a sales standpoint, we put more structure around I call them the intersections. You think of all of our products and then the deal types across conversions and new logo and renewals, and we've made sure that we've got teams that are dedicated to those intersections so that we're not overlooking anything and not having people too focused on the low-hanging fruit, right? So what that's done is that's created the best pipeline we've ever had in most of those intersections. And we've got -- take as an example, point of sale, we now have people that are career point-of-sale people doing those sales opportunities as opposed to somebody that maybe has spent their whole career in warehouse trying to sell a product that's related. So that's put a whole lot more focus on building that pipeline and continues to drive those high win rates. We've talked about more than 70% win rate across all of those products. You mentioned conversion. Conversion was a big opportunity to create that dedicated team because in the past at Manhattan, we've always taken the approach of they'll convert to the cloud when they're ready. And we decided it was the right time to get more proactive and more consultative with those customers and talk to them about not only the value of what they get on the cloud platform versus what they have today, but as we're introducing AI, that's probably the biggest step-up, right? This is the biggest carrot we've ever seen of what they could have versus what they have. And then the other thing that we're out there proactively talking to them about is they probably have this image in their head that that conversion from the on-prem to the cloud is going to be something big and complex because that's what they're used to over the past many decades when they were converting and upgrading on-prem products, those were big complex, long, expensive projects. It's not that way anymore. So we're committing to fixed time line and fixed price versions that are leveraging AI that we've built to auto-configure. We know exactly what they're running today. We know where they're going. We're seeing 40% decreases in the number of extensions. The extensions that we do have to write, we're riding twice as fast. So just everything we're doing is much, much faster which takes the risk out of them moving to the cloud and allows them to take advantage of the carrot that's out there and all of this new functionality, including the AI.

Yes. And so it's effectively enabling customers to adopt and lean in more aggressively.

Exactly.

I guess on the professional services component, right, as you're moving to a fixed fee, I guess, how should investors interpret that dynamic, right? In one angle, it's conviction and efficiency that you're seeing. On the delivery side, it's reducing risk from the equation. But how do you think about kind of what that unlocks maybe in being able to expand the scope or volume of projects that you're serving as well?

Yes. What that unlocks is the ability to do a much higher volume at a much faster pace, which is driving faster cloud growth. In Q4 of this year, our cloud revenue will surpass services revenue. And once it does, it's going to -- that gap is just going to get bigger and bigger. And as you would expect, our cloud margins are bigger than our services margin. So that's going to create the ability for us to accelerate margin growth even faster. So this is just kind of setting that process off and running. The fact that we are growing services revenue this year just tells you, you can assume that everything we're doing in services, we're doing it faster now than we were doing it a year ago. So when we're growing services revenue, that means we're doing more volume, right? We've got more go-lives, more new customers. 55% of our bookings over the past 5 quarters have been new logo. So we just continue to put more and more new customers into the system.

And maybe what's the right way of thinking about what that kind of normalized balance looks like between each of those components, between conversions, new logos, expansions, you said kind of 55% from new in the most recent period, but.

Historically, Manhattan has always talked about thirds. About 1/3 of the bookings will be new logo, 1/3 will be, call it, expansion within the cloud customer base and 1/3 will be conversion from on-prem to the cloud. And as I mentioned in the past 5 quarters, we've really been running really fast with new logo and it's been 55% over the past 5 quarters. Our expectations with the focus that we've put on cross-sell, upsell and conversion, that we would like to see get back to thirds, but not because that new logo is coming down. It's because we're driving even faster on conversions and cross-sell. So we see the opportunity there. The other thing you have to think about is last 5 quarters, 55% new logo that's created more cross-sell, upsell opportunity. So there's just more and more opportunity out there for us every quarter.

Yes. And you guys talk a fair bit about the idea of unification, right? Historically, been more oriented on warehouse management, you have additional modules. Maybe Sanjeev and Eric as well too, but that kind of platform simplification from a technology perspective, how customers are buying into that kind of unification vision, if you will?

Yes. So I mean, I think, like I said, when we started the platform, we broke down the boundaries between what is a WMS and what is a TMS. For example, a shipment is a shipment, it can be used in WMS and TMS. So when someone who implements WMS with us, it's already more than half the way there with TMS functionary already in there. So for them to turn on TMS becomes a lot more simpler task. And then we can kind of really articulate the value between them having as a single supply chain system versus having it as a WMS and TMS, right? So when you get an order down, typically, traditionally, a TMS would kind of plan that autoroute without knowing what's there in the warehouse. You do not know what the inventory is, you get a plan, warehouse kicks 10% of that out, and now you got a not optimized truck leaving, right? Versus this being a single system when you can do the planning, you exactly what you have from [indiscernible] perspective, so you can plan accordingly, and chances of you shipping a truck at the right capacity levels are much higher, right? All of those things just pays for itself. So you just take that particular single-use case and that can pay for WMS and TMS together on what you would save on the transportation cost.

Yes. And we're seeing every quarter more and more of the new logo customers are buying multiproducts at one time. And we introduced warehouse management in the cloud a little over 5 years ago, so we're kind of in that natural renewal cycle of that. And when we introduce warehouse in the cloud, we didn't have transportation, that came later. So you've got a big renewal cycle coming where we expect to see a lot of these warehouse customers adding transportation. Because when we -- again, when we look at new logo, about half of the customers that buy warehouse as a new logo now also buy transportation at the same time. So it's a very natural connection. And then we just launched supply chain planning in the cloud about a little over a year ago, and we're seeing that become a more and more common add-on to all of these products. And of course, order management and point of sale go very well together. So we're seeing more and more of that unification story across multiproduct customers.

And I would think that that has favorable kind of economic benefits as well too around kind of stickiness [indiscernible]. I guess maybe from a platform differentiation perspective, right? It's kind of a competition question, I guess, to some extent. But I would assume that not many others can kind of offer that full breadth of platform capability. I guess, just kind of how you think about that as a core differentiator.

Yes. Okay. So a couple of things. So there are companies who would give you the functionality, but the way they deliver the functionality is through 16 systems put together, which makes the whole thing a lot more complex to implement -- integrate because it comes from basic integration. And we've taken the word integration out completely, right? When you kind of take software from us, it is a set of capabilities you take from us you use what you buy. But it's all kind of done without any integration needs, as a core micro services. So that's kind of one big difference from a platform capability. Like Eric mentioned about omni order management and POS customers. Our customers who are using our order management are already using POS. Almost every component require POS, right? To turn that on [indiscernible] is really getting the [indiscernible] and start using the system. So it becomes a lot more simpler for them to move from one product to another product because core of it is already in there.

And is that starting to show up, you kind of hinted at the renewal cycle dynamic, kind of those customers coming up with the initial contract terms, now you have more capability and resources to kind of educate customers of the additional products that you have, but how that's maybe kind of trending from a dynamic kind of customer cross-sell and upsell?

Yes. And again, last year, middle of the year, we put this dedicated renewal team in place. And the reason for that is exactly what you're talking about, is to make sure that a couple of quarters before the renewal comes up, we're having the conversations about what are the natural cross-sells and upsells for that customer, what products should we be adding on to make sure that we take maximum advantage of that renewal cycle. So what we're seeing in our pipeline is the amount of cross-sell, upsell at the time of renewal is significantly going up in the pipeline, not just for -- like Q1 was really our first quarter where we had this team in place, but we're already seeing that pipeline created across deals that are coming up for renewal even in Q3 and Q4.

And the other thing with customers is when they start using one product of ours and get comfortable with it in a couple of years, they become a lot better believers in the overall system and the architecture, which creates the traction for the next set of products. .

Sure. Sure. Maybe Linda, bringing you here as well too. How are you -- we talked about a lot of like the opportunity across all of these different segments and lines of business. And Eric, I think, hinted at the fact that subscription revenue will surpass more than 50% of the overall business mix. How do you think about kind of drawing down against that opportunity? What that can look like from a business perspective as it pertains to the growth profile, the profitability profile, the investments maybe in some of these platforms or products as well too?

Yes. I mean I think just as we think about the metrics of the business and what's important to keep an eye on, historically, our investors have focused on RPO. But I think a very important metric just given our focus on accelerating cloud revenue growth is going to be that ramped ARR metric that we introduced at the beginning of the year. So what that's doing is it's looking at our contracted revenue in 4 years' time. As an example, at the end of 2025, that had grown 23% year-over-year. So that just a showcases again, number one, visibility into our future cloud revenue but also our ability to accelerate growth. So that's definitely our main focus is trying to accelerate that because I think, as Eric mentioned as well, the cloud revenue does have a higher margin than our other items, and that will help us to accelerate or grow our operating margin.

Sure. And is there maybe a way to kind of think about that too, because these are multiyear commit contracts where there's an embedded ramp, we also talked about the fact of kind of delivering faster, getting them online faster, how those kind of like converge, I guess, or thinking about what that convergence looks like between those 2 metrics?

Yes. So when you think about when we sign a contract, that -- the revenue starts to come to us as we deploy, right? When we sign a contract, we agree on a deployment schedule and that revenue is going to ramp based on that schedule. If they get behind, the revenue still ramps. So that is committed revenue. But if we can move them faster, then the revenue grows faster. So I think we see a lot of scenarios where maybe a customer takes a conservative approach just in case they can't move fast enough. But as we can help them move faster, they are very willing to move faster because they get their ROI faster. So we just are really maximizing our opportunity to take advantage of accelerating revenue growth simply by deploying faster. So it doesn't require any new sales. It just means we deploy faster.

Yes. And maybe part of the platform simplification as well too, I know traditionally you've kind of catered to the larger enterprise kind of types of retailers and, I guess, manufacturers there. But what does it mean in unlocking the incremental opportunity to maybe go a little bit more down market and grow kind of the overall pie and your ability to kind of simplify that?

Yes. So we've always talked about we're focused on Tier 1 and Tier 2. And that Tier 1 and Tier 2 make up about 80% of the spend in the market. However, I think when you get to the lower areas of Tier 2, maybe we're not in all of those deals. Maybe there are some customers in that space that think, oh, Manhattan has been the leader for -- in the Magic Quadrant for 18 years, but they're big and complex. Because we're known for solving the biggest, most challenging deals. But what we want to do is make sure that we can scale down very easily. And that part of that focus on speed and simplicity is if we can take time and dollars out of deployment, that takes down the total cost of ownership. So that allows us to expand that addressable market and go deeper into the Tier 2. So that's been a focus for us. And I think in the second half, we'll have more announcements and put more clarity of how we're going to get even more focused on expanding that addressable market.

Sure. Maybe one other component too, but what role -- I know this has been an area of emphasis as well that you've kind of been building, but what role do partners play in kind of the educational component, obviously, the delivery component of getting kind of the software and some of these additional modules to any of the customers?

Yes. So we've had a good set of partners for a long time, including technology partners and services partners. But when it comes to services partners, we hadn't always had the best relationship with all of them. So about a year ago, we changed our partner model and committed to them of what -- number one, what we expect of them. And bottom line, we're expecting them to create pipeline and bring us deals and not just follow us around and look for services opportunity. And when we do that, we made commitments to them about how we will help them win the deal and win that services. So we're seeing a lot of partners really lean in and create new pipeline. In fact, we had 1 partner that just announced a program that they're putting in place. Our big user conference in the U.S. is called Momentum, and we follow that up with user conferences in EMEA and APAC that we call Exchange. So as a lead-up to EMEA Exchange, they're doing a 6-city tour where they're inviting prospects that are currently customers of our competitors coming up on renewal cycles, to educate them on Manhattan Active and ultimately get a bigger audience of prospects at Exchange, ready to make purchasing decisions by Exchange. So we've got a whole new focus from our partner ecosystem on creating that pipeline. And a lot of our partners have relationships with kind of that Tier 2 type of customer, right? So we're seeing new deals that we wouldn't have otherwise seen.

I know we're kind of coming up on time here, but maybe one other way to kind of exit the conversation, we've talked a lot about different factors that are driving kind of momentum and enthusiasm in the business. Maybe one for each of you, maybe from kind of an industry perspective or a technological perspective and from a financial perspective, but everything that we've kind of discussed today, what excites you most? Or what are you kind of most enthused about kind of the opportunity ahead for Manhattan as we think about kind of this compounding financial profile of the business?

Yes, maybe I'll take the industry perspective. I think it's quite exciting to see. I mentioned it earlier, best Q4 we've ever had from a sales perspective, the best Q1 we've ever had from a sales perspective during some times where there's a lot of turmoil in the market, I think it just really shows that customers understand that supply chain is mission-critical and they are investing in this. And when they look at this, I mentioned 70% win rates, nobody has invested like we have. Nobody else has the platform that we have. So when they look at this market, they're overwhelmingly coming to Manhattan.

Yes. So I'll go from a technology perspective. When you think about enterprise software, right, and you think about 4 years, 5 years from now on what will differentiate enterprise software from each other, I define it simply as it will be measured in terms of its IQ, the autonomous part and how much it can automate and bring intelligence, and its EQ, which is really the contextual intelligence and software adapting to users versus users adapting to software. So I think that's kind of my measure of how do you see software -- enterprise software. How do you measure software 5 years from now. So what is exciting for me really is all the work we have done over the last 10 years, building the deterministic spine, is bringing the AI into it, the probabilistic part of it and delivering that intelligent software of the future.

Yes. And I think on the financial side, what's the most exciting is, obviously, our goal, like we've said, is to accelerate our cloud revenue growth. What's exciting is that we have multiple ways that we can do that, right? We have a lot of good programs that we've put in place between product specialists on the sales side, our new focus on renewals and conversions in the specialist programs for those, as well as obviously having top products, new exciting features we're adding. So yes, we're excited that we're moving ahead.

Fantastic. Thank you all for the conversation. Appreciate it. And we will carry on the conversation, for those interested, upstairs here. I believe it's in the Richardson room in the next 5, 10 minutes.