Appian Corporation (APPN) Earnings Call Transcript & Summary

With me today, I have Mark Matheos, CFO; and Srinivas Anantha, Head of IR. Thanks for being here.

Thank you, Kevin. Thanks.

So I thought maybe just to start off, I think it would be helpful for people, who new to the story, to just give a brief overview of Appian kind of history and kind of the platform capabilities.

Got it. Thanks, Kevin, for having us here. Appian is focused on the process automation market. By that, we mean we do everything related to a process building it, running it, automating it, executing it, diagnosing it, changing it, everything related to a process. This is a large market opportunity and by -- and we conservatively estimate the market size of approximately $60 billion. The one thing that is different from others in the marketplace is we provide all the capabilities related to a process. By that, we include process capabilities related to workflow, robotic process automation, process mining, AI. All in one fully integrated platform. I think this is extremely useful for our customers, as they're dealing with 1 single code. But more importantly, they can deploy new applications and maintain existing applications faster. We predominantly sent to large enterprises that are building complex processes. They're making them -- they want to make themselves more efficient by providing better customer experience. Largely -- lastly, majority of our revenue comes from subscription-based services. When we went public in 2017, our revenue mix was 50% subscription, 50% services. Today, that revenue mix is 75% subscription and 25% services. This is largely driven by our cloud subscription revenue, which has grown at 30% or more since going public.

And I want to get back to the platform capabilities in a bit, but I thought maybe we can start since you mentioned AI. I guess I think Appian has been pretty vocal about kind of their strategy in terms of private versus public AI, so maybe just give us some context around what does that actually mean? Why approach it that way? How is that differentiated from maybe other vendors in the space?

Yes, sure. So I think it's actually pretty self-evident. Any time you look at a corporation's assets, data is the crown jewel of the corporation. So they have really, really important controls and safeguards around data and data protection. And if you're a bank or an insurance company, it's critical that you have your data secured, but also that your proprietary business process is also secured, right? So it's not just your social security numbers and your customer private information that's -- that has to be kept secured, but also how you do business, right? So how an insurance company files a claim through its process. So what Appian is saying, and I think what's kind of being echoed throughout industry, there's a lot more white papers coming out about this, is that you really need to keep all of that within your own domain behind your firewall. It's not enough to like redact certain parts of the information. And so when you're thinking about AI today and large language models, the notion that you're going to send all that information out to the ether and try to get some computational advantage from that is really not well thought out, right? It has to be kind of within the confines of the corporate environment that you're in. So I think CIOs and people in charge of the company's data are going to -- they're not going to react nicely to some proposal that sends the data out, right? So private AI, I think, kind of inherently makes sense. And it's really what our CEO has spoken a lot about. He's written an editorial in the Wall Street Journal about it. And I think what we're doing is using the platform that we've already got to try to incorporate all the awesome power that large language models and AI can give us in that kind of secure environment that's within the balance of a corporate environment or a government environment or whoever our customers may be.

Yes, yes. And what I'd just add, Kevin, to that is it's also the nature of the customers that you're dealing with. These are large multinational corporations that have very strict compliance and security needs. So in that particular context, what these customers are saying is, "Hey, we don't want to share our data with any public domain." So when we are talking about training your algorithms or LLM models, we are talking about doing that in a private setting. So that the data is held by the customer wherever it is and whichever cloud they are hosting. They're not even sharing the data with us and training the models. In fact, I was just meeting yesterday another investor, and he was saying, there was actually a letter sent out to the legal industry where they're saying is, "Hey, you guys are going to build these private LLM models, make sure you own the model and you are training the model." So that is what we are going to enable the customer. We will help the customer build the model, but we will give the model to the customer so that they can train that model with their own data in a private setting.

Yes. And then I guess, it feels like the narrative around GenAI is -- the question that we get often is, who gets displaced, who are the winners and losers. It feels like the narrative is some of the more basic low-code solutions, may be more pressured and so maybe talk a little bit about -- Sri, you talked about kind of the end-to-end process automation platform and kind of the mission-critical workloads that you do. So just from a positioning perspective, what does that mean for a platform like Appian versus maybe some other tools?

Got it. That's a great question. Again, we constantly think about these things. The way I would think about is we have been using AI for a while. We have deployed as a part for some of our solutions, AI. The government acquisition management solution, which is one of the successful solutions that is largely deployed by large federal agencies, we already provide some AI capabilities as a part of the platform. The way we think about AI or GenAI, in general, is it's an additional lever or an accelerant to automation adoption more than anything else. To your point, could there be some low-end solutions that could be displaced, probably. If you're just a code generator, that probably is more relevant. Today, when we talk about Appian platform capabilities, we are talking about building an entire end-to-end processes. And when we include AI as a part of that platform, we think it accelerates the adoption of this platform in these solutions, but more importantly, it enables customers to deploy some of the applications they're planning to build much more quickly. So it's more an efficiency driver rather than we think it's going to be a displacement, probably some low end, but that's not the market we are focused on.

Yes. And just to add to what Sri is saying, we operate in kind of this broad complex mission-critical space. So companies that are faced with supply chain issues -- for example, we've had a story we said about a major manufacturing company who had to face Brexit, and they had to -- all of a sudden -- I mean, they were U.K.-based. And all of a sudden, their whole procurement and supply chain operations ground to a halt because they needed to think about customs forms for every item that was shipped out of the U.K. So we built a solution that streamlined that entire shipping and procurement supply chain. So when that company was sending transmissions to Germany, into Italy, they can just type in the address. They were pulling the jurisdictional forms that were required, would auto-populate them. It completely streamline that procurement for that manufacturing company. They liked it so much that they're expanding into other supply chain apps. So they're running their supply chain in large part on Appian. So it's not one of these, a, build a low-code lightweight tool to get us to do point A to point B. It's a fulsome transformation that companies are doing with Appian.

Yes. And Sri, you made an interesting point on maybe implementation times getting faster, time to value probably getting better. Does that help maybe broaden the addressable market just by kind of having a tool that can get you up and running even quicker?

We think so. It not only brought it to our market opportunity, but more importantly, the time to value, right, especially in an environment like this where customers are looking for solutions that generate quick ROI. We think that certainly helps the case from a return on investment for an investor. But also internally, when we're using the same set of capabilities, we're also improving the productivity of our developers. Keep in mind, we've already seen some level of productivity out of our developers, but we think if this is going to be accelerating so it helps our inherent operating leverage in the business model too.

Yes. And then there's a lot of buzz around GenAI and it feels like there's increase in customer engagement. But do you think -- are you starting to see it kind of in the pipeline? Like is it impacting kind of any of the key kind of growth metrics? Or is it still kind of in the early stages there?

It's definitely early stages. The conversations are happening. I think the energy levels are extremely high. Companies are actually trying to figure out how to best use AI to get what they need done, right? And so they're talking to partners like Appian to try to get a feasible way. They're reading about AI and the capabilities, and they're looking at their actual IT landscape and what they have to get done. And they're using Appian as a sounding board to try to get an actual feasible road map that will help them take advantage of all these new technologies. So I think -- yes, it's early days right now, but the level of energy coming into it is very high, yes.

And then I want to maybe shift gears a bit to just kind of overall demand. I think last quarter, Matt, CEO, he mentioned, I think things are stable or things haven't changed too much from prior quarters. But maybe just add a little bit of context around kind of what you're hearing, what's the appetite for both existing customers and new customers to maybe undergo some of these larger kind of transformations?

Yes, I think in large part, the demand is still pretty strong. It's on the user side and the business side. It's perhaps even stronger than it's been. I think the macro impact is more on the deal lengths and approvals required to get any spend through a company right now. And so that's kind of a little bit of a proverbial rock in the [indiscernible] or whatever. I forgot the expression, but it's kind of a little bit of a slowdown in the actual sales cycle itself, right? So I think we've seen that for 2 or 3 quarters. In the beginning, it wasn't clear if this was just kind of normal noise, but it's been persistent enough that we think it definitely is just overall macro backdrop that's challenging. And we certainly don't see it resolving. We're not in a position to say the light is shining at the end of the tunnel, and we're turning the corner on that front. But again, the product demand and the use cases that are out there that need to be done are still very much present, yes.

What I would just add to that is just we have been seeing this for the past 2 quarters, but we have appropriately baked that into our guidance. So we have been dealing with this. This is not like a new phenomenon. The only thing is it's not getting incrementally worse, but the guidance appropriately bakes that into our guidance.

And I think, Mark, you had mentioned maybe healthier contributions from Europe and APAC last quarter. Is that just kind of -- is that just kind of a one-off or like maybe catch up after maybe softness in prior quarters? Maybe talk about some of the regional markets and any changes you've seen there?

Those markets are doing well for us. I think it speaks to the use cases that are emerging in financial services and insurance among other areas. There's definitely some low numbers here. Those are smaller markets for us. Our total international spend revenue is about 30% or so. So we definitely have smaller numbers, the growth rates are better, but it's a consistent and durable growth. And I think we're going to potentially see that stay the course for at least the near term. Maybe in the midterm, we'll see strength in Europe. There's a lot of institutions that could really benefit from Appian. And I think I'll note, maybe a common thread is the regulatory environment there, is a little bit more likely to need systems and structure for business processes. Europe takes -- there's a lot of regulations that come out of Europe all the time, right? And the companies are faced with c***. We've got about 18 months to deal with this regulation. How do we do it? And I think that's a little bit more of a catalyst and you might find in the U.S.

Around kind of sales cycles, budget scrutiny, is there -- are you seeing customers consolidate vendors especially just given the breadth of the Appian platform. Is there an opportunity there to kind of capture more of the share and consolidate?

I think we are seeing that to an extent. It's along the lines of just spend management. Really, it takes multiple forms. They try to reduce vendors they're not using. They try to consolidate vendors where they can. And it's sometimes the fight between the back office procurement folks and the business folks, who really want to use something. So we're actually on the good side of that side because what we build is really not something that's easily replaceable. It's -- our GRR, gross renewal rates, are 98%, 99% in the past few quarters. They've been that way since IPO. We definitely have a sticky set of software. And I think we prevail when we stay the fight. If there's a fight around consolidation, and we feel let's have it -- let's go through it, we usually end up doing pretty well.

So I wanted to ask about just cloud revenue growth. Sri, you mentioned you're factoring in some macro dynamics into the guidance. I think the full year guide is around kind of high 20s growth. So maybe just around kind of how you think about kind of the durability of cloud revenue growth. I think, Mark, you've talked about 30% being a key target for the company. So maybe just to puts and takes there in terms of how you're thinking about how you're investing and what do you think is the right level of growth at this stage of maturity?

When we look at the guidance for the year, at the midpoint, it's 30%. And clearly, in a normal macro environment, we said we should be able to sustain that 30% cloud subscription growth rate. When you look at the key drivers, right, the existing growth coming from existing customers and new customers. Today, roughly 2/3 of the growth comes from existing customers, and about 1/3 -- the rest comes from new customers. Within the existing customers, we clearly think there's a lot of room for expansion within that. We think our penetration within our existing customers today is probably less than 10% of the available spend that's there. And with our platform capabilities broadening, we think there's a lot of upsell opportunities within our existing customer base. That is certainly something we are seeing, even in this kind of environment. I know you talked about Europe. When we look at some of the strong growth coming from Europe, it's also coming from our existing customer base. What we have seen historically is once a customer builds that first application with us, they certainly understand the capabilities, how easy it is used to. They can use the application. The second sale or the third sale comes within a relatively short period of time. With the new customers, right, we are certainly baking in some macro impacts in the current macro environment. Clearly, that's where we are seeing the sales cycle impact. But clearly, given the market size and the broad capabilities of platform, we think there is substantial room for growth. And in a normal macro environment, we should be able to sustain that 30% cloud subscription growth rate.

I mean, you bring up an interesting point. It seems like the larger customers or the $1 million plus -- I mean, the growth rates there are very strong. It seems like the bigger a customer gets, the faster the growth. Is that just a function of they know how to use the platform, it's end to end, you have all these capabilities. And maybe talk a little bit about that how some of the larger customers are really doing -- that cohort is doing really nicely right now.

Yes. The most prolific customers, the ones that our bigger customers are actually expanding in general at a faster rate than our smaller customers. There's definitely a component of familiarity that builds, and then the power that we've been talking about through that sales process is actually made evident. And so they're getting an ROI from the first 3 apps or 2 apps that they've built. And the road map that we initially talked about, maybe we had 10 apps on it. And so they look at that ROI and they say, why not build the rest. There's definitely -- that's where kind of macro and things like that just get pushed aside, right? You've got your ROI, you've got things you need to do, it's working, keep building. The new customer doesn't have that confidence. It's got nothing to do with the product or our capabilities. It's just a new thing, right? So they need to figure out kind of dap their toe in it first and then go into water completely, right? So I think it takes time to get that confidence. I think we do see success once the confidence is attained and that happens through just the building of apps. Some of our larger customers have 30, 40, 50 applications that they've built. And they're actually continuing to build. It's almost endless because if you think about a top 5 commercial bank, the amount of [indiscernible] in the IT department and in the business is off the charts, right? It's not just 40 or 50 that they can build. There's a lot more. And we're just out there to try to get that use case in front of the customers so they can keep buying.

I wanted to shift a little bit maybe back to product. I think, Sri you mentioned it, but end-to-end platform, now you have process mining, you have RPA, workflow automation, maybe just to level set, like how is the platform being used differently now? Or just maybe compare and contrast the way the platform is being utilized today versus maybe 3 years ago?

Today -- when we look at the usage of our customer base, right, today, they're still predominantly using to build workflows applications. We're definitely seeing incremental adoption of RPA and process mining, but we still think it's in early stages today. The key value add that customers get from our platform is building that workflows and applications in a relatively quicker time period, more importantly deploying those in an efficient fashion. When we look at the usage levels from our different cohort of customers, to your point, like some of the larger customers, the usage is still growing at a pretty healthy rate. The early customers are gradually ramping. But once they deploy that first application, we see the adoption of that going much more broadly. The other things that we are seeing is like data fabric, we talked about recently. That's a new capability that we added to platform. That is the #1 feature that's been widely adopted, since introducing 90% of all of our new customers have signed up for data fabric capability. So as we are broadening those capabilities, I think we are seeing wider adoption. But more importantly, we are focused on that long-term -- long tail growth opportunity. So we are taking our time, but we are definitely feeling good about where the usage levels are trending with our customers.

I did want to talk about data fabric because that stat is pretty impressive. And maybe just talk about why is that resonating so well? What does that enable? And are you also seeing that -- because I think that metric is for new customers, but what about existing customers as well?

Yes. So data fabric is a phenomenal feature of Appian. And it is a differentiator for us. When we show it to customers, they love it, they want it. It's usually a game changer. And I think it's actually taken an enhanced -- it's been enhanced further by AI. And I think what it allows us to do in that space is build these large language models a lot faster, a lot more securely, a lot more in line with compliance regulations. So -- but let me step back, I think the biggest part of data fabric is that it's kind of solving all of your data integration issues. And it creates this virtual database in a very easy-to-use environment and allows you to pull information from all sorts of data sources at your company's IT environment. So whatever systems need to be involved, it can pull the data and actually can write back to the source system as well. So a lot of that depends on how does the user experience, right? Is it easy to use? Is it fast? Is there latency? And that's where it shines. It's extremely easy to use. It's very fast. It's low code. And so you're actually able to solve a lot of these data integration pain points that companies have, and further than that, when you're actually thinking about building large language models, what better way to do that than to use Appian data fabric. And again, one of the things about Appian, that is a differentiator, is that we don't really care about where the data sits. We're not big tech. We don't say, you've got to bring all your data within our system, within our cloud. You can actually just pipe into it. And I think our traditional use cases around an orchestration layer where we come in and say we're at a call center and at an insurance company that's acquired dozens of insurance companies in the past 20 years. And all those systems that they acquire, they all work, but they're just kind of clunky and call center reps have to put you on hold when you file a claim to look you up and what system you're in. That's a perfect use case for Appian. And we've done it before where you just built an Appian orchestration layer, all those systems feed into Appian, and the call center reps are just using Appian. And if they need to update the core record, they can do it with Appian. They don't have to ever use the other systems. And so that's much more effective and really much more cost-effective as well than a rip-and-replace scenario, obviously, which could be a complete nightmare. But that's like Chapter 1 of data fabric, right? Nowadays, data fabric can do a lot more, a lot faster. And again, this AI revolution allows us to bring in data within any system or even any like -- if you're talking about papers, right? If you're talking about paper invoices, we can use Appian intelligent document processing to pull in that data. And then that's how you harness the power of a large language model in the private AI space, is getting all the right data in the right spot. And when you're a highly regulated bank or insurance company, you really can't mess around how you do that. You need a highly secure environment like Appian.

What's different about that is it's -- by the way, it's our own patented analytical framework. More importantly, today, there are others that are available where they offer open APIs, right, but they force customers to migrate the data onto their platform. With a data fabric, you don't have to do that. So what is the advantage to customers? Instead of customers building that new API tools or maintaining existing API tools, they don't have to do any of that. It's like a virtual database layer. More importantly, it helps customers to keep the data wherever it is. And it helps customers to integrate the data into this -- into the Appian platform and get real-time updates on what exactly happening with that particular processes. So the advantage is customers don't have to build new APIs or maintain existing APIs.

That's great. And given some of these newer capabilities that are coming out, I think it will be helpful to just talk a little bit about the overall kind of pricing strategy, how are you monetizing some of these newer features? Just maybe talk about seat base versus kind of usage-based pricing and kind of how you think that's evolving?

Sure. So historically, we've priced -- this is going years back, but we still have a lot of our revenue base and our renewals this way, just on a per user per month model. And so we've got a published kind of price list. We've recently -- I shouldn't say recently, it's really been over the past 4 years or so kind of pivoted new business to an application-specific model, where we evaluate the use case, and it actually creates a less friction environment because the customer isn't locked into some per user dollar amount for the long term. Whenever we see anxiety or friction develop around that and we start getting negotiations that are hammering down our per user price, we just say how about we just price you on the app you want to build, and that cuts out the friction. So they'll -- maybe if it's a bank when we build -- I know your customer application for a couple of hundred thousand dollars, and that's palatable, they'll build it in 8 to 10 weeks under the Appian guarantee. It will go live, they love it, and then they'll say, okay, we need a mortgage origination app. That was the next thing we wanted to build. And we say, okay, great. Now you know about our Appian. It works. And we have a little bit of a bigger stance at the negotiating table with them on that. It's better than kind of locking a lower price. But the usage component -- look, we don't have usage-based pricing. It's kind of incorporated in how we evaluate the pricing on an application-specific sale. So will we ever switch to usage maybe, I think subscription seems to be the name of the game at the moment.

Yes. Any questions from the audience?

[indiscernible]

So the question was just on competitive dynamics and kind of how AI is kind of impacting that?

Yes. So I think historically, we've entered into a greenfield opportunity with the incumbent competitor, if you will, is high code or some development in-house that's custom. If it's not that, it's usually Pegasystems is at the bake off because they can build powerful applications as well, although they have an older technology. It takes a lot longer to do that. . The other emerging competitor has been ServiceNow. I think in the past 2 or 3 years, they've kind of gone right at us with the low-code platform. I think a lot of their marketing shows that they mirror a lot of what we're saying. But at the time of a proof of concept, I think it becomes really clear that our power is much, much greater, and that their use cases are really orchestrated around their ITSM environment and neighboring environments that they can do some things in low-code with. But it's not a -- whenever there's a complex use case, like the ones I've talked about, it's really not in ServiceNow's wheelhouse at the moment. I think they are investing and certainly formidable. We don't see much of Microsoft, but occasionally we do. Anything else you want to add to, Sri?

No. I would say the competitive environment, if you just look at for the past few years, it's largely remained the same. Even if I look at within the past 12 months on the margin, we see ServiceNow a bit more compared to what we see in the past. But the type of use cases that we're going after, the type of customer base, I think the competitive set is much more narrower than what tend to be believed out there. There are certainly a lot of noise at the very low end. If you're just a code generator, there's a lot of noise out there or building some lightweight application. There's a lot of noise out there, but that's not a market that we're really focused on.

I did want to touch on go-to-market. I think Appian definitely added a lot more sales capacity, I think, in the back half of last year. So maybe just touch on kind of how things are going in terms of go-to-market in this macro environment? How you think about some of the newer reps ramping and the impact of productivity and maybe layer in kind of -- I think you guys have set some nice kind of EBITDA targets, right? And so how that plays into the bottom line guidance?

Yes. So we made a lot of investments last year. I think we're very happy we did. We've got a really strong go-to-market motion at this point. Certainly, the macro is not ideal, but we're still seeing a healthy ramp. We haven't -- we wouldn't have expected those reps to be productive quite yet. There is a solid 12-month or so ramp-up time. So towards the end of this year, early next year, we'll start to see productivity from them. We certainly have seen pipeline generation and all of the things that are indicating success. But our growth rate, I think, is still the central focus, and we're very happy we have that strong motion on the go-to-market side. The -- to your EBITDA comments, we are moderating our OpEx in general. And I think that's more catered around just what I call growth with scrutiny, identifying areas where maybe in a 0% interest rate environment, you would have allowed sort of some spend to happen. But in this environment, we need to cut some of it back. But it's not, I think, targeted towards anything that's revenue-generating or impacting our growth rate. And so we'll actually continue to invest in those areas as we move forward, especially where we have territories that need more go-to-market muscle. But overall, that moderation in spend will result in us reaching a breakeven point in adjusted EBITDA in 2024 and being adjusted EBITDA positive in 2025. Another question.

On the go-to-market, part of the ramp do you think it's related to -- one of your competitors, they talked about deemphasizing the net new motion and kind of focus more on the installed base. Do you see that as an opportunity kind of take the other side of that? You said that you [indiscernible].

Yes, it's absolutely an opportunity. We aren't doing that in terms of what our competitor is doing and focusing on expansion. It would be easy for us to try to get a few more points of growth from expansion. But I think the strategy for us is to get more customers. We're using our partner ecosystem to help with that. We're enhancing our partner relationships with our most strategic partners, so we can get more new of those. It's critical. We see this as an early innings company with a large opportunity in front of us, including a lot of new customers. And hopefully, we can get those customers up to that 7-figure ARR mark, so they can start expanding on their own and telling us what they want to build. And that's the goal to get as many of those.

And some of that improvement in EBITDA is just coming from us getting more efficient, right? We've talked about our R&D efficiency. We're improving our efficiency. We recently opened our R&D development center in China -- in India. So part of that R&D efficiency is coming from that particular center. Plus we're also going to be more than $500 million in revenue this year. So some of that is just comes with scale rather than we're trying to take away some of the costs from somewhere. So we're still focused on the growth, but we're also trying to get more efficient. .

Yes. I think it's nice to be in this kind of scale right now where we can still grow and kind of naturally create adjusted EBITDA breakeven without having to do any painful cuts.

Yes. And maybe to finish things off, just on this, Mark, you recently introduced some long-term targets so maybe talk about kind of the key levers there. I think you've talked about 20% operating margin. I think -- key to that is also I think 80% to 85% gross margin, so maybe talk about kind of what's the appropriate mix? You guys have talked about services declining, but maybe a little bit more on the key levers that will get you that 20% target.

Yes. Certainly, the mix will continue to shift towards software. Our gross margins are near 90% on the software side. So that's certainly an area for leverage. Sri talked about our Chennai, India, R&D center. It's not some small thing we're doing. It's a massive R&D tech center we're building, and that will help. We're actually finding a really, really good talent there, and kind of very happy we've gone there. So in general, we are looking at sales efficiency as well and making sure our reps are ramping quicker, that they're all productive. Sales enablement is a focus. And then finally, we are at the size now where some of the marketing programs can have some more scale and benefit to us as well. So I think S&M will certainly be looking at improving that over time.

Yes. Great. I think we're out of time, but really appreciate the time. Thank you.

Thanks, Kevin.

Thank you.