Great, mic's working. All right, well, thanks, everybody, for being in here today. Steven Ender s, part of the software research team here at Citi. With us for our final session of the day, we have the team from Appian, Mark Matheos, CFO, and Sri Anantha on the IR team. So I wanna thank you both for being here.
Great. Thanks, Steve. Thanks for having us.
Yeah, maybe just to start off, maybe talk a little bit about just Appian, what it is that you do, and a little bit of background for those who may be a little bit newer to the story.
Sure.
Yeah, Appian is focused on the process automation market. By that, what we mean is we do everything that's related to building a process, running a process, diagnosing a process, changing a process, so everything related to a process. You know, we largely or predominantly sell to large enterprises that have complex processes or workflow needs. And these companies are trying to make themselves more efficient, provide better customer service, make their processes more agile and, you know, make themselves better. You know, the one thing that's different about Appian versus others is we provide all the capabilities related to process automation, and that includes capabilities related to workflow, RPA, Process Mining, AI, all in one single integrated platform.
We think this is good for the customer, as they're dealing with one code base that makes, you know, help them deploy applications much more faster, quicker.
The demand environment, and what you're seeing out there on the macro. I guess, how would you kinda characterize the impact that you have seen, so far from customers? And how are they thinking about their automation and AI initiatives at this point in time?
Sure, yeah. I, I can take that. You know, demand seems to be pretty resilient and strong. I would, I would characterize it as robust. The product is certainly resonating with, with companies that wanna improve their processes. There is a, a macro component to, how quickly deals get done, and I think that's probably the, the biggest impact from this backdrop of, of macro uncertainty. And so a few quarters ago, we started to see, some deals slipping. We, we weren't quite sure at the time if it was just kind of noise or, or what, but, you know, over time, we've kind of seen it persist, and I, I think it certainly is, as expected, companies that are trying to scrutinize their spend, and get some more approvals in place before they spend any money.
The good thing is we're able to close those deals, we're getting through those approvals, and things are going well, they're just taking a little bit longer. And that's something that we continue to see in the macro. But overall, the actual demand from the business and the product users is really robust, and we're happy with it.
Okay.
The only thing I would add there is this is something that we've contemplated in our guidance. So the positive thing, as Mark said, you know, some deals are getting slipped, but none of those deals are getting canceled or we're losing to competitors. It's just that it's taking, you know, a few weeks longer to close those deals.
Okay. Has there been, I guess, any, like, downsizing or change in the scope of deals as they've come in, either from the ones that maybe are slipping a little bit or from some of the others?
You know, that's a phenomenon. I think those that are in line to approve the deal would like to happen. You know, I think the approvals would go a lot quicker if we started cutting price.
Yeah.
And, you know, we're resisting that urge. We, we really do have a compelling product proposition. We've got an ROI attached to every deal that is pretty compelling, and so we stick to our guns, and, you know, we try to get what, what we're owed, for, for us. And that's why, you know, we're, we're choosing, again, for, for. Again, this is the minority of deals, but for when there is such a phenomenon, we, we choose to let a slip happen and have it closed in a few weeks, rather than start negotiating down a price and just trying to close it to close it.
Sure. Sure. Okay, that makes, that makes sense. You know, I guess we'll talk about the topic of the moment of AI. It feels like, you know, every single person's talking about it at this point. So, I guess to start, maybe talk about, like, what your strategy is today around AI, and what have been maybe the early feedback points from customers when it comes to what you're doing in the market today for AI.
Wanna take that one? Yeah, so, you know, we've been working with AI as part of kinda what Sri talked about. When you look at our overall process approach, we look at all the different actors in a given process. And so we've got different systems we're integrating with, we've got people that are obviously playing a role in the process, and then we've got RPA, if there's an instance where you need a bot. And we have AI capabilities like, you know, email summarization, intelligent document processing, things that historically businesses have found very useful to do things faster and better. And so today, I think we've turned a new leaf, right? There's a lot more excitement that's warranted.
There's more investment around, "Hey, you could do a lot with generative AI and LLMs." And so that AI component of our approach is getting a lot more focus, and we're looking at ways to make kind of a bigger boost out of our apps and the mission criticality of what we do through using some of those technologies. And our flavor of that, when it comes to generative AI and LLMs, is really a Private AI approach. Our CEO has spoken about this. He's written an editorial in the Wall Street Journal. It's really much more inherently.
It makes more and more sense inherently, right, that a company who values its data, which by the way, is pretty much every company, would want that data to be kind of contained in their own ecosystem, in their own domain, on their own servers, if you will. And so they want to own the LLM, and they want to train it, and we're really positioning ourselves to help facilitate that. And kind of this public and open domain really isn't the place for large enterprises, governments, insurance companies, pharmaceuticals, what have you, to test out and design new stuff, right? They need control over that, and data is really, you know, the crown jewels of what they have.
So I guess when it comes to your AI strategy and the product set, what is it that, you know, that you've kind of built out natively yourself? What are you, you know, partnering on for other things, and just how are you thinking about how the ecosystem develops and what your kind of place is in that?
The way I would approach that is two-part, right? You know, I know Matt has talked about this publicly. I think AI is going to be a productivity booster. It's going to, you know, increase the overall market opportunity for us. But AI works well when you combine with humans.
That's our view. So from that perspective, when you look at it as a Private AI, this is one approach that we have taken, where we will build domain-specific LLM models, either on our own or we will partner with customers, and few customers, and build those models, and give those models to our customers. They can train those models using their own data. That's one way. The second aspect of it is, at the same time, we'll also provide open API integrations to some of the public AI models up there. So if a customer chooses to leverage some of the capabilities of the public AI, they can do that, but they will be training their own models on their own.
All we are doing is facilitate customer to help they train those models. Again, this is within the context of that Private AI. When we talk to our customers, clearly there's a lot of excitement about the AI technology, how they can deploy within their IT stack, but it's still early at this point of time. We also plan to have a separate pricing or premium pricing for this AI functionality. That is something we will likely to come out later this year or early next year.
Okay. All right, that makes sense. Maybe switching gears a little bit, just maybe back to the demand environment. I mean, it seems like public sector has been really resilient, has been really strong for y'all. I guess, how is public sector doing, maybe compared to the commercial side of the business? And I guess, what is it that is helping with customer budgets at this point, and where you're seeing strength versus maybe relative weakness?
Sure, yeah. There's a confluence of things happening. Conveniently, you know, the macro impact is a little bit further removed from the public sector. There's just a less of a focus on that.
A little bit more resilient to macro headwinds and concerns. Sure, the sales cycles are a little bit longer, but you know, they end up kind of being less dynamic and subject to kind of what's on the news today, and kind of the ups and downs of the economy. But the other thing is, you know, we have a pretty robust solution in the government space, and it's the Government Acquisition Management suite. And so this is a kind of a prepackaged offering that is really an eye-opener for those involved in procurement in the federal government. And we think it has implications in the state and local government as well. We're definitely investing and looking at that as a next step, if you will.
Mm-hmm.
But there are success stories in 2023, in the GAM space, in the public sector, in the federal level, that really have helped propel us. So those kind of combined things, the insulation from the economic headwinds, and then our resonant application solution that we've built in that space, has really helped the public sector do quite well for us this year.
Okay. I do want to touch more on GAM and I guess the learnings there to maybe drive to other, you know, prepackaged solutions and those opportunities out there. So, I guess, yeah, what have you learned from GAM that maybe could be applied to a different use case, and how should other kind of prepackaged apps built on Appian, you know, look like in the future?
Yeah. So GAM has been, I think our third or fourth solution that we've built. There's definitely a practice to it, right? We're finding the best components of what we know how to build, that we've built before. We're showcasing the power of Appian and the different components of our platform that we've spoken about, and we're putting it all in front of the customer, and saying, "This is what really will solve your pain points in a fulsome manner from an end-to-end process automation perspective.
Mm-hmm.
Usually, we're holding hands with a partner while we're doing it. So we're talking to the customer in front of, alongside a system integrator who kind of is ready to go and starting to build this solution. And there's a lot more of a speed component to the deal, right? You've got everything ready. You don't need to sit around and decide what the application might look like. And you're really ready to hit the development. And in this case, since the solution, the development is really plugging it in, configuring-
Mm-hmm.
It's not starting over and building something from scratch by any means. And so, the actual deployment is faster too. In these days, speed is a lot, right? It matters a lot to our customers. And I think focusing on getting an app up and running to go live is really a lesson that's learned. We know that customers care about that, and we know we have the capabilities to do that with our platform.
Okay. Is there a way to quantify how much quicker I guess the sales process is? How much quicker the actual implementation deployment is for something like GAM versus compared to when you're selling you know kind of the fuller Appian Platform and kind of more tailoring the use case?
Yeah, the impact is more pronounced on the sales cycle.
Okay.
I think that's the most... I mean, the reason I say that is 'cause usually our development is quick either way.
Yeah.
We have the Appian Guarantee, where we can build a really useful application in eight weeks. So that's pretty good, right? The sales cycle itself is where we see a dramatic improvement. We've got longer sales cycles when we go for a platform sale, upwards of nine -12 months.
Okay.
So that's the thing that gets cut down dramatically. I don't think we have statistics on it, but that we've shared anyway.
Okay.
Yeah.
The only thing I would add there is, you know, with the Appian Platform, right, customers can build anything they want, right? Everything, when we go into a customer, everything is, is pretty unique. They are trying to build something that fits with their unique workflow processes. Whereas in this particular solution, even though they're buying a solution, it comes with a platform. It's not like this is a standalone product, and they're not buying the platform. The only thing here is they know exactly what they're... For example, you take Know Your Customer.
Mm-hmm.
Let's just say that's a solution, right? If I come to Citi, and you say, "Hey, we have this requirement," so you buy the platform, you're building that. I know the use case that's using for, but we think the same use case could be relevant to other financial services institutions. So we build that use case, and now when I go to them, I'm saying: "Guys, this is a use case." So they don't have to guess what they are building. They're readily seeing it, and that's where we think that sales cycle is much more faster. And because the product is already built, deployment is quicker. Yes, there's going to be some element, the customization, but it's a much smaller.
Okay. So, you know, understand GAM, understand the opportunity there. How do you think about, like, what the next use cases that could be prepackaged is? And I guess internally, what is the process look like for that decision to get made and for, you know, engineering, sales, you know, whoever is involved in that, to make that decision?
Well, we think the, you know, the pipeline is one thing. We do have a list of potential solutions that we're working through. However, we're not actually going down the list.
Mm.
At Appian, we really believe in doing something well and thoroughly, and I think the GAM solution right now is a really good opportunity for us. It's only the beginning.
Mm-hmm.
There could be a lot more there, and like I mentioned, the next chapter of that same space and that same solution is the state and local government space. So while it would be kind of interesting to, to switch to another solution, I think we're kind of focused on, you know, that pivot to the SLG space as the next step. And there are differences, right? You, you have a different ecosystem, a different procurement process. There are application changes that need to be made, but we wanna do it right, and we wanna have the product amaze people. So that's... You know, with a company our size, we'd rather focus on this.
Again, the market is huge, and we do see a lot of opportunities, so we're gonna take it one step at a time with those two for the time being.
Okay.
I think we have a senior executive who runs the solutions, and he reports into Matt.
Mm.
So he's tasked with not only identifying what are the next solutions opportunities, but he also works closely with the product strategy and the engineering team to have them built out. You know, we just, I think three months ago, we launched this Connected Underwriting solution that's focused on the insurance industry. So there's going to be a few more solutions that's going to work. We have a senior executive who's exclusively focused on solutions opportunity, so this is like a key priority for Matt and the company.
Okay. All right, that makes sense. I wanna touch on something, Mark, that you said a minute ago. Just large opportunity for everything that you're doing. And when I think about your net retention rate, I think it's held in remarkably well in kind of the mid-teens area. So I guess to ask, how have you seen changes in your customer expansion behavior, and is there a way to think about the differences between, you know, pricing more users, more use cases that is helping support that net retention level?
You know, it's really the additional use cases and more applications, more projects. What we found is actually pretty encouraging, and it's that the prolific Appian user that's built 10 apps or 15 apps, you know, they're a large enterprise or government agency. They are already paying us perhaps seven figures ACV per year. That cohort of customers is actually expanding more impressively-
Hmm
Still than other cohorts. So the more you use it, the more you like it, the more you buy. I think it's a phenomenon that we're encouraging ourselves, and we don't really see, you know, a trailing off of expansion. It's really the more you buy, the more you want it. So, it's probably helped offset some of the difficulty expansion, expanding over in other parts of the economy or in other parts of our cohorts, and we're happy with our resilient NRR. We'd like it to be higher. I know we're focused on getting NRR as high as possible, but we'll take steadiness in this macro.
Okay. So I guess with that point of view, of, you know, the largest customers that you have continue to expand at an outsized rate, how much more opportunity is there for Appian to, you know, get deeper within those accounts and kind of expand the already, you know, large footprint that you have?
I think there's a lot of opportunity. It's not the case that we think we're tapped out by any means on any of these accounts. There are balances you have to strike, right? We are a company that focuses on new logos-
Mm-hmm
And acquiring more customers. We use our partner ecosystem to help with that. So it's certainly easier to expand and, you know, sell more to an existing customer, especially, in this macro environment. But we can't just do that, and be, you know, good stewards of our proposition here. Our product and our market demands more, so we are focused on new logos as well.
Okay.
Maybe you want to add?
Yeah. When you look at the penetration among our large customers, either by IT spend level or the number of applications that they're managing relative to what they have built with Appian, we still think we are only 5% or 10% penetrated, so there's still a big market opportunity. You know, on top of that, you know, we are constantly broadening our platform, adding new features and functionality. We've talked about Data Fabric, you know, in the past few quarters. You know, since it's been launched, it's one of the most widely adopted. The uptake has been 90%+ among our new cloud customers. So we think as we roll out more features, there's the penetration within the existing customers is still pretty big.
Okay. I do wanna touch on Data Fabric, since you bring it up here. I guess, first of all, like, what is it, and what is it that it helps your customers do, and how does it kinda differentiate the Appian Platform?
Yeah, it's a cloud-native data and analytic engine. More importantly, what this enables customer is to keep data where it is and easily integrate into the Appian Platform in a relatively easy fashion. You know, when you look at other, the way other companies, you know, use that is, for example, if you go to any other vendor, they make you write a custom API in order to migrate the data onto their platform.
Yep.
But as with this particular Data Fabric feature, you don't have to do any of that.
Mm.
In fact, it's a patented technology, and we think it not only helps customers, you know, manage their data easily in a highly secure fashion, but also enables them to build new applications much more faster.
Okay. So is it something you're directly monetizing, or is it more about the usage and being able to build faster, and so you monetize it kind of secondarily?
I think it's more about the usage, and I think the monetization is going to come later.
Okay.
Today, it's not like, hey, if they adopt Data Fabric, we're gonna charge them a separate price. We want to drive adoption and usage, and we think the monetization aspect will follow.
Okay.
But we've been really successful at driving adoption. It's very highly adopted amongst our new customers. Over 90% are using it.
Yeah. So I think Matt have talked about it quite a bit, of Data Fabric, helping, you know, helping with the AI strategy and helping kinda differentiate it. So I guess, what is it about Data Fabric that enables that, that Private AI strategy that, that you've talked about?
Well, to create. You know, part of this Private AI strategy hinges on creating your own large language model, right? And to do that, you need to bring in data from all sources. And oftentimes, in a corporate or government large enterprise environment, the data is everywhere. There's disparate systems, there's different entities that you've acquired over the years, and it's a proverbial nightmare, right-
Yeah
... to get all the data.
Yep.
And so with Data Fabric, you can not only just get the data, you can do it securely, you can do it in a way that is controlled, trusted, it's fast, it's performant, it's low code.
Mm-hmm.
So all of those things enable you to bring in all the data you need, and you could even use, you know, intelligent document processing, which is AI-driven, to get it off of. Let's say you have paper forms that you need to read and incorporate in your LLM. So it's kinda the first step, right? Before you start training and getting the iterative machine learning and the different things you need to do, you need the data, right?
Mm-hmm.
So that's where Data Fabric comes in.
Okay. Last question on AI, and then I guess we'll leave that to Matt here. Monetization, just how are you thinking about it at this point? And kind of what are the, you know, implications for what you know charging for AI will do for Appian?
You know, as I said, you know, AI, we've already been investing in AI for quite some time. In fact, some of the solutions, products that we have already have some AI capabilities. The government acquisition management solution is a prime example of that. So AI is already built in, so customers do pay for it. It's not like we have a separate SKU.
Mm.
It comes as a part of the platform, and so they pay a premium pricing for it. With respect to Gen AI and LLM models down the road, we will have some premium pricing for it. If customers are going to sign up for that AI functionality, there is gonna be a separate premium pricing. What that is, we are yet to determine that. That is something we're probably going to communicate later this year or early next year.
Okay. All right, that makes sense. I guess we'll stay on the product side. I think you have made quite a few acquisitions in the space to build out your automation platform, you know, RPA, Process Mining. Where does the automation portfolio sit today? How is the adoption of kind of those other solutions that you've acquired into the Appian base going? And I guess, finally, you know, how much of a differentiator is that compared to, you know, some of the automation peers that you're competing against?
You know, I think our advantage is that we have the hard stuff down. The hard stuff is the actual workflow, application building. That's our DNA. Where we're actually getting, you know, all these integrations built, all the different actors, like I said earlier, to play together, to actually get stuff done in a company's environment. I think that's our forte. When we have RPA, you know, it's our approach has been different than RPA-led companies, right?
Mm.
Those companies pretty much want to put a bot everywhere they can. We're putting a bot where we absolutely have to. We'd rather build an integration, we'd rather use Data Fabric, but we sometimes we need to put a bot, so we have that asset. The other asset that you mentioned, which is more and more important today, is the Process Mining piece. I say it's important today because we're using it as a way to show the value of the things that we're building in Appian. And you know, Process HQ is our way of framing up that proposition. We're showing all the information that a customer would care about, about what their process was before Appian and kind of how Appian is helping streamline.
And it's a continuous, real-time assessment of how long things are taking to go through the process, how much, you know, time or money you're saving, or whatever unit you'd like to track. That all of that is enabled by Process Mining and getting the plethora of different processes on a piece of paper in front of the customer, or on a screen in front of a customer, to actually show the power of what is being built and how it's running. And it plays into this maintenance piece, too. Like, you need to, it's one thing to build an app and go live, but you have to live and breathe it. You have to go through it every day to make sure it's still doing what you want it to do.
Mm.
That part is facilitated by Process Mining very well.
Okay.
So those assets are kind of the building blocks. You know, there are at this point not too many things that we can't do with Appian.
Mm-hmm.
But we'll certainly look out for, on an opportunistic basis, for anything else that might enhance our technology.
Okay. I remember when you made the Process Mining acquisition. There, I think, was a view that maybe it'd kind of be like a tip of the spear to help kind of bring customers in. I think maybe it shifted towards then being more of, like, an expansion opportunity. So I guess, how are you viewing the monetization potential of Process Mining today? And just, yeah, what's the view of how it changes maybe the go-to-market here?
You know, I don't think our strategy in Process Mining has changed, right? We still said it's going to be part of the platform. So when the platform, you know, is fully integrated, customers should get it. It, it makes sense. The existing customers who have been using Appian Platform for a very long time are likely going to be the first adopters. Again, this is very consistent with what we've said in the past.
Sure.
At the same time, we're also putting that capability in front of our partners also, so that they could then talk to new customers out there. So, you know, it's not like, you know, one is more important than the others. Like, you know, it's equally important about everything, but it kind of that initial adoption, we think we will see much quicker adoption by existing customers because they already know how to use the Appian Platform, and they've been using it for a very long time. So from that perspective, I think we've seen some pretty healthy uptake, and we've talked about customer examples who've used Process Mining. Some of these are large, global, multinational customers-
Mm-hmm
who have signed up for the Process Mining capability. So we feel very good about it. And in fact, you know, we still think the Process Mining capability is very relevant, especially in this kind of macro environment, where customers are looking for quick ROI or looking, trying to find process inefficiencies within their IT stack. So Process Mining is a perfect tool for that.
Okay.
The one advantage is it's fully integrated into a platform, so customer doesn't have to, like, write an open API and say, "Oh, I want to integrate with someone else.
Mm-hmm.
It's just dealing with one software over here.
Okay. That makes sense. Maybe switching gears a little bit, I do want to ask about the 8-K that was filed this morning, for the insurance on the lawsuit. I guess a couple questions. I guess one, can you just give some more details about what was actually announced today? And secondarily, what kind of led to the decision to do this?
Sure. Do you want me to give background on the lawsuit or?
Yeah, sure. Let's start there first.
I think, you know, I'll do it briefly. There's a lot of materials out there, but there was a trade secrets misappropriation lawsuit. We won the lawsuit and a $2.08-something billion verdict against our top competitor, Pegasystems. There's an appeal process underway. What we've done is succeeded in getting a Judgment Preservation Insurance policy awarded to us or purchased by us, and that kind of creates a floor or a locked-in value for us at $500 million. So no matter what happens in the appeal process, you know, we feel very confident in that process. We feel confident in our our overall victory, but now we don't have to worry about anything getting overturned, because we have a floor of $500 million.
So the mechanics are simple. If you, you know, if the judge, for some reason, throws it all out and rules that there's a $0 award, we get $500 million from the insurance company. If the judge says the award is $200 million, we would collect $200 million from Pega and get $300 million from the insurance company. So we get trued up to $500 million. If the award is ultimately, let's say, you know, $700 million, the insurance company wouldn't pay us a dime 'cause that judgment was preserved at above $500 million.
Mm-hmm.
We would have to collect from Pega. It's really a win-win at this point for us. We have a new kind of floor, like I said, and we'll fight to get it all, but we know the minimum is $500,000.
Okay. Maybe to follow up on that, you know, I'm sure that there's gonna be appeals pro- or I know they were in appeals process now with that. I guess, what's kind of the, the timeline that you're kind of thinking about today? I guess, you know, I'm sure no matter what happens, there's gonna be another, another level of, of appeals here. Like, at what point does, you know, does this ultimately kind of get, get finalized?
You know, it's hard to put a timeframe, like, but, you know, give and take, it's probably going to take another two-three years. You know, the oral arguments in the appeal process may be likely to be relegated this year.
Mm-hmm.
And the judge needs to rule on it after the oral arguments are done. Depending on the outcome of that, either party can choose to appeal that. So, you know, again, you know, these are all in a moving process, but I think at this juncture, we think it could take another two-three years.
Okay. Okay. That makes sense. Maybe if we go to, you know, the go-to-market a little bit, you know, new CRO, Chris Jones, has been in place for, I think, a little over a year now. What are some of the highlights of what he's put into place to maybe change or evolve the go-to-market? And what are kind of the short strategic priorities today when it comes to the go-to-market function?
Yes, CRO has been there for a little more than a year. We're seeming happy with what he's doing so far. What I think Chris Jones wanted to do was more fine-tune rather than reinvent the way.
Mm-hmm.
So as a part of that, I think he's flattened the organization structure so that there is quick communication between different teams, so that it enables them to make decisions much more quicker. But more importantly, I think what he is aiming to do is drive sales force productivity, number one. Number two, accelerate new logo wins.
Mm-hmm.
If you were to boil it down, those are the two most important things that he's looking to improve upon.
Okay. I know that there's been a big shift for multiple years now to push services more and more to the partners. Like, where does this effort stand today? And maybe how is the channel and the partner opportunity different, you know, now relative to a few years ago?
It's pretty. You know, it's a longer game for us. We've been at this for a while.
Mm-hmm.
But it's been pretty successful in so far as a good chunk of our new logos are, in fact, influenced by our partner ecosystem. You can see the proof in the pudding with our services revenue being much more slow growth, in some cases, not even growing. Which speaks to the fact that, you know, work is going to the partners, and that is because they've brought us business and new logos. Dovetailing to the earlier question around Chris Jones, our CRO, he's a huge partner guy, and he definitely wants ways to get those partners more involved. There are, you know, strategic partners that, you know, are very involved at Appian, that we wanna even double down on with those relationships.
The ones that we're doing a lot of business with are ones we're looking at to really say, "Okay, let's up this even more," so we can be the vendor of choice for those clients of theirs that are looking to do an automation effort. You know, the AI chapter here is gonna bring in a lot more conversations around that, so we wanna be ready to have 'em.
Okay. And so, I know you mentioned that there's a lot more partner influence in the market today. At what stage are we in terms of partners that are, I guess, pulling you into opportunities rather than, you know, maybe helping fulfill the services angle? Like, is that becoming, I guess, yeah, where does that stand in terms of the go-to-market?
No, I mean, we don't. You know, our success and our efforts in the partner ecosystem and our partner initiative is exactly that, for them to bring us new business. And it's not necessarily, you know, just firms that can do Appian work, so we don't have to do it.
Mm-hmm.
It's really we want their footprint out there, which is huge in the case of, like, you know, KPMG is a strategic partner of ours. It doesn't really get much bigger than them, and Accenture, and then some of the other partners that we have. Those massive workforces that are out there in front of customers are ones we want to tap into. And right now, the majority of our new logos are influenced by those guys.
Okay.
So we want to keep that going and make it even more.
Okay. You made a comment at the recent Analyst Day about wanting to drive a significant increase in rep productivity and continue to increase their efficiencies. I guess, what are the key levers that you can pull to help drive those improvements, and what does it take to, you know, make that significantly higher?
I think some of the initiatives are just basic, you know, blocking and tackling, right? As a part of that, as I said, you know, Chris Jones has already made changes where he has flattened the organization structure. I think one of his conclusions when he was looking at, hey, you know, there are multiple management layers that's delaying the process, and in turn, that's taking longer to close deals.
Mm-hmm.
That, in turn, impacts the sales rep productivity. That's part of number one. He's already done that. Number two, we talked about verticalizing sales force, right? He's already doing that, but also creating, you know, a separate sales force that are focused on the very large customers. You know, we still think there's a ton of opportunity with these bigger customers that are spending. You know, we're trying to say we have customers that are spending $1 million ACV, how to move them to $10 million ACV? What are the things that we need to do different? We are having some dedicated sales force that are exactly focused on those very large customers. The third one is also having a renewal team separately.
Mm.
This way, your existing sales force is not worried about the renewal, because this is basically, "Hey, renewal comes up," just making sure they sign the document, et cetera. So we have a separate renewal team. Even the renewal team takes care of it, the salesperson still gets the credit for it.
Okay.
These are some of the things that we're doing to make, to improve the sales force efficiency.
Okay. So if we tie that, you know, go-to-market and trying to drive efficiencies to, you know, the 30% cloud, you know, sub-growth number that you've talked about, I guess, how does that kinda tie together and how do you-how should we think about the growth equation to get to that 30% level?
So we've talked about when you look at the growth, like 2/3 comes from existing and 1/3 comes from new logos. We think that particular math, the balance is going to remain relatively the same, but more importantly, within the existing customers, as we see a pickup in sales force productivity, there's opportunity for that to be a bit more higher. And over time, you know, again, our ambitions are, you know, at least 30%, but certainly, it's much higher than that.
Sure.
As we see sales productivity improvement, we should see some, you know, movement both within the existing customers as well as the new customers. With respect to the mix of contribution within existing and new, it should remain relatively the same.
Okay. All right, well, I think we're running up against time here. So, Mark, Sri, I wanna thank you both for being here, and, I wanna thank everyone in the room today for being here as well.
Thank you.
Okay. Thanks, Steve.