ServiceNow, Inc. (NOW) Earnings Call Transcript & Summary

Okay. We're going to get started with what's become one of my favorite annual traditions post-Thanksgiving keynote with Gina Mastantuono; CFO, ServiceNow. Thank you for making time at the Wells Fargo TMT Summit. I'm Michael Turrin, the software analyst here and looking forward to the conversation.

Well, thank you so much, Michael, for having me. And yes, it's quite nice to come to Terranea post-Thanksgiving and the sun finally came out today. It's always nice.

We had a video of it in the background because we can't see the ocean through the doors right now.

So there's a lot to talk about given the time of the year and just the strong position of ServiceNow. But before we get into some of the more specific questions, maybe we can just speak to the most recent earnings report, 3Q, another set of consistent results for ServiceNow. We appreciate it has not been the easiest environment that the company has managed to present this just stable execution pattern for some time. How would you characterize Q3? What are the conversations like coming out of that? And maybe we can use that as a jumping off point?

Yes. Great. Happy to. So Q3, really, really pleased with another quarter of just really, really strong execution across the board, right? We beat top line guide, bottom line guide by a good amount. And a few things that I called out on the earnings call and then I'll just reiterate, despite an uncertain macro that has continued. And I got this question a lot. Did we see a shift in Q3 in the macro? I'd say it wasn't and isn't from an overarching perspective, better or worse. You're still having a lot of scrutiny on spend and ROI is really important, right? And so ServiceNow and the fact that you can get ROI fairly quickly. It's not years, but it's weeks or months has definitely put us in a strong position. It's also a tool that's really a deflationary tool, right? It drives productivity, efficiency and cost savings. So in an environment that we found ourselves in, in the last couple of years, I think that ability to help customers really not only get better, faster and more secure, but actually drive that productivity and savings has been, I think, one of the reasons why we continue to be successful. A few things that we called out that I think are important in the quarter is our gen AI SKUs, right? And so we talked about the fact that only really 3, 4 quarters out, still remains our fastest-growing new product launch ever, which is pretty remarkable. And we talked about 44 deals to date -- or 44 customers to date that have bought over 1 million and that includes 6 customers over 5 million and 10 customers over 1 million, and that is just the gen AI SKUs. And so the conversations about monetization, right? And are you really monetizing gen AI, I think that really answers that question pretty broadly. So really pleased with the progress that we are continuing to see and we're continuing to see realized price uplift of 30%, which is what we had expected in the front. So from that perspective, doing extremely well. On customer workflows had another really strong quarter, up over 50% year-on-year. And so I know we'll talk a little bit more later about front office, but that continues a trend and an opportunity that remains really broad because we are very early days and underpenetrated there. And then last call out, obviously, Q3, big federal quarter, another really strong beat our internal expectations, closing out a federal fiscal year extremely strongly. And I'm sure we'll get into conversations on federal. But as we think about the setup for Q4 and into 2025, another just really strong execution quarter top to bottom.

Yes. We've observed -- I mean ServiceNow has definitely become more of a bellwether for enterprise software spend. You're having high C-level discussions. We've got the observation. Maybe you have two that's -- it's -- I don't want to say it's been a disadvantage, but you report early in the earnings cycle and software investors often aren't sure what's to come. And so you've spoiled us and then we see some subsequent results and everyone kind of looks back and says, "Wow, ServiceNow print was actually really good in the context of what's happening here." I'd just love to get a sense of how you would frame the conversations you're having with customers around their budget plans for next year, how they're approaching, what they're prioritizing and if there's any sense of optimism or if it's still similar to what you would have said a year ago on that point.

Yes. Well, a couple of things that I think are a little different today is I'd say a little bit of cautious optimism in the economic environment that we find ourselves in. And so just looking at whoever reports you look at, whether it's IDC or Gartner. And if you believe the numbers or don't believe the numbers actually, the pace of IT spend is expected to double in '25 and software spend growth, they're talking 15%. So even if that number is not accurate per se, it's significantly more than what was actually spent in '24. So that's super positive, I think. The other also surveys that you hear that many, many companies do with CIOs, where they're going to spend and are they going to be increasing the spend, most of them are suggesting increased spend in '25. So that gives me some cautious optimism, especially in the software space. The other thing I'd say is the actual conversations that we're having with customers at the C-suite level very interesting. And they're really focused on how do we take the experimentation phase that we're in with AI and gen AI and move it out of the POC and experimentation phase into real implementation. And what is that going to drive and so that conversation, I think, is very broad-based across industries and across customers. And so that, for us, I think, is an exciting time. And what we're hearing and not dissimilar to how Bill and I think about this is that while the experimentation phase is very focused on productivity efficiencies and cost savings, in an AI-infused economy like we think we're going to be seeing in the next 3, 5, 10 years, the ability for AI to not only generate that productivity and cost savings and efficiency gains, but also redefine business models and drive top line growth. That's where the C-suite is really excited on. And so how can they get some early wins, understand what AI can do and can't do and how to implement that in ways that can drive that efficiency and productivity, get some of those dollars to be reinvested in some of the other, I think, longer-term big ideas way of thinking about how AI is really going to transform the enterprise. And I get when I say that, people like, well, give me an example of that. And 1 of the things I talk about is pharmaceutical industries average clinical trials of 6.6 years. And if AI can help reduce those clinical trials by 10%, 20%, that's billions of dollars in top line, much less cost, so even more leverage falling to the bottom line and thousands of lives saved or patients in better health. And so what creates the 6.6 years, a lot of it is manual work that AI can really help drive efficiencies. It's about patient care, patient concerns, questions, how do we get those patients from dropping out. AI can really help and that's just one example. Think about how manufacturers could automate things in a much more -- in a much more productive way to get cars on the road faster and into the showrooms faster to sell. And so AI, I think, is very early stages on how it's really going to shift the enterprise. And just being part of that in ServiceNow, I think being an early adopter and one of the first to market with actual AI product, I think, puts us in a really good position as we're thinking about where technology spend in the enterprise is going.

That's great. Very encouraging on many fronts. I want to ask one more high level and then I definitely want to get more into the AI discussion. But there's been -- this is a conversation we've been having throughout the week. I think over the past couple of weeks, we've been asking companies how they're thinking about a new administration who seems to be focused on efficiency, first and foremost, right? And so we look at that from a few different ways. There's a world where that could mean when the budgets come down, and it's tougher to get things done or it could mean that vendors who are able to enable efficiencies or productivities could kind of move up the pecking order. I know it's early and I doubt you're too far along, but do you have kind of an initial sketch of different scenarios that you think could happen based on that with what ServiceNow enables.

Yes. I think from our perspective, and I hinted at it, we've been really strong in federal for years. And certainly, post 2020 and post COVID, we've been a platform of choice for many of the governmental agencies as they're looking to digitize and drive productivity and efficiency and so if the mandate is to drive more productivity and efficiency, you would expect that one of the trusted platforms that they've been utilizing and could count on is someone that they're going to come to drive even more efficiency and productivity broader range. So we actually think it's a really large continued opportunity for ServiceNow. And certainly, because of our strong relationships there, that's the attitude, and that's kind of how we're thinking about '25 and beyond. And so there's lots of opportunity within the federal government in this administration. And we talk about the fact that we are really strong in federal, and we've been doing some in state and local and public sector outside the U.S., but we're just scratching the surface there. And everything that we've done for federal is easily replicable, state and local and outside of the U.S. And so the public sector vertical for us is obviously an area where we are selling down on and focusing where we see great opportunity.

Okay. It's another one. I'm sure we'll hit like 5 of these great opportunities that you're going after. In the AI discussion, so this -- obviously, this has probably dominated a lot of the conversations you've been having. Certainly, we've been having as well. Can you help level set a couple of things, just what is available from a generative or AI-related perspective within your product portfolio currently and what was in that has enabled you to kind of reach the forefront of giving us a monetization metric, something in software that investors are asking about, but many companies are saying, it's just going to take some time. You've been, I think, more forthcoming with progress in your point, it's early in the adoption curve, but the science seem quite encouraging.

I think that's exactly right. And so we've been investing in AI for years and years, right? So our Pro SKU, which was our first AI SKU was launched back in 2018, one of the first acquisitions that Bill and I greenlit when we came to ServiceNow in 2020 was a company called Element AI, which brought in over 200 of quite frankly, the greatest minds in AI that's been helping us kind of create that road map and build products with those capabilities in there. So I think certainly, the focus on that has enabled us to really ship products a lot quicker than some, and we just did our Xanadu launch back in September, which was our biggest AI launch ever. We talk about now agentic AI, and we can go into that in, I'm sure, in a few minutes. But at the end of the day, it's all about how do we this incredible platform that we've created that can go across enterprise and at the same time, be able to drive automation and now you build the AI into that platform. And it can do whether it's HR or ITSM or customer service or even creator, that ability to really drive that supercharged AI automation into the platform is what we have launched and continue to update and refine. I'd say the biggest part of the Xanadu launch in September was our agentic AI and I get the question often, lots of folks are talking about agentic AI. And of course, I think it's going to be a big area where AI is going to go in the enterprise. But if you think about the ability for agents to 24/7 to be able to really assess what's going on and to complete tasks end to end with some human oversight, but they can work together in teams and they can be governed in teams and built in teams and use the same types of models, have that ability to go across platform as opposed to fragmented platforms. That drives exponential value and productivity and efficiency gains. And so if we think about how agentic AI is really going to shift the ability of companies to use AI and to drive that supercharged exponential productivity. That's an area where you're hearing a lot about it because that's where many feel we're really going to start to see huge ROI as opposed to good ROI that we're seeing today. Does that make sense?

Yes, it does. It's actually really interesting. So you mentioned we're seeing agentic solutions show up in different places. And I think everyone is trying to figure out the best use case, who has kind of priority position to implement those technologies quicker. What would you highlight as ServiceNow's advantages? It seems like the orchestration, the workflow, the things that your core system already enables could map really well to agentic solutions. Is that...?

That's exactly right. And I'll go back to the one platform, right? And so all of the automation that is built into the platform that agentic AI can supercharge the fact that it's all on 1 platform. So whether you have agents in the background, agentic AI in a background working on IT issues or HR employee issues or customer service issues, and many times, they're interrelated. The issues in customer service are not just customer service. They got to go figure out what went wrong, and that could be back in legal. It could be in billing. It could be in the IT organization. So that ability for those agents to work together across the enterprise, cross functions and not siloed. That's where there's real power. And I think a large differentiation for ServiceNow.

I want to just stick with the customer service piece for a moment. What I'm wondering is you've started to highlight this opportunity more as something that we pick up in our conversations as well, the workflow for customer service is quite similar to the workflow for IT service, right? Bill has talked about that as one of the most significant opportunities that he sees in the future for ServiceNow. I'm wondering, is this agentic conversation, the fact that agents seem very well-suited for customer service really use cases, do you think that's opening up take a broader discussion that you can lean into around just repurposing systems or just modernizing whatever is in place with customers.

Yes, I think -- so I'll take agentic separately on that one because while it certainly adds to the opportunity, that's not what's happening, and that's not what's pulling, right? So we have been -- we talked about the fact that our customer workflows cost $1 billion quarters ago, right? So we've seen significant growth, and we have our right to play in that space. And what's been happening is where we've been really successful in kind of the mid back-office piece of customer service, especially in industries where a lot of the customer service issues relate back to IT because digital is the business. Those customers are bringing us to the front office, right? They're saying, you're doing mid and back. Why can't you do this? And let's consolidate everywhere in 1 place. And so think about telco, think about technology, think about manufacturing. Those are where customers are bringing us and asking us to come to the front office. And that's where we have been really focused initially, you add on your question and your conversation about agentic AI, absolutely customer service is a place where agentic AI is going to have a huge impact. And I think it's one of the first areas that's going to be disrupted by agentic AI because of the fact that there's less risk, there's CSAT scores are probably not so high, right? And so it's lower risk for folks to really be taking a chance on this agentic AI to really supercharge these call center operations, attrition is really high, right? And so there's so many reasons why agentic AI can really help drive. And so I think that opens up just another avenue for why, I think, customer service is a huge opportunity for ServiceNow.

Okay. Very helpful. Just, I guess, one more on this topic. The pricing uplift, your ability to capture that within what was expected. There was what felt like a little bit of a misguided bear case at one point that seats would come down and that might impact your ability to monetize and you kind of hit that directly when that conversation first picked up. But since then, you found like tangible proof points around that 30% uplift being kind of the right shape and size. What has enabled that? What are customers telling you that has helped make that the right sort of metric, the right uplift level for the new product?

Yes. I mean at the end of the day, we've always been super focused on selling value to customers, right? We're not just increasing pricing, we're saying, you're going to see this value. Like there's been lots of POCs, and the productivity gains are real. We have examples of customers getting 85% deflection rates, up from where it was at 30%. We have our text to code, 50% of the code generated by AI is being accepted first pass. Like there's real productivity gains and ROI. And when you're giving the bulk of that efficiency gain and productivity to the customer and you're taking a small piece of it, that conversation is not that difficult to have, right? And so we got the same question when we launched the Pro SKUs back in 2018. And by the way, we monetize the exact same way, we thought about pricing in the exact same way. And 5 years out, when people upgrade from Standard to Pro, 5 years out, we're still seeing 25% price uplift, right? And so we felt really confident that the 30% was the right place. And as we're a year out, we're still seeing that level of pricing, and we feel really good about it. But it's all about making sure that you're selling the value and ensuring that customers are getting to value as quickly as possible.

How should we think about just where you are from a seasonal perspective with where Pro Plus is from a product and conversational perspective, meaning we're in December, you're a very seasonally heavy business. Is that -- like how much is that a potential catalyst? How much is that a part of the conversation with customers? And does it, in some ways, can elongate deal conversations? Or is it, hey, some of the AI capabilities, actually, that's what we're looking for, so it can kind of catalyze that discussion.

I would say the AI conversations don't tend to elongate things. It is a catalyst for opening up conversations with customers who might not be in a renewal period, right? And so from that perspective, I think it's certainly a catalyst and all favorable. Again, it's the fastest-growing new product launch that we've ever seen and 100% most conversations with customers, there's a conversation about AI and how they are thinking about their AI strategy, right, and making sure that they are thinking very far ahead so that they're not left behind in what most understanding is going to be a very different AI-infused enterprise.

One other discussion point that's come up for us more frequently and perhaps for you as well is Raptor. You made some changes to the underlying technology, can you speak to the value proposition of Raptor and then also, if there's a way to couple that with what we're hearing quite often from enterprise software vendors is there's a little bit of an obstacle in terms of data, right, meaning data can often be tough to surface, not as well-organized as is ideal for use of generative applications. Is that an area where ServiceNow can also play a role? Or how are you kind of working through that obstacle?

Yes. I love that you get these two questions in one. I know. So I'll start with the first one. So the RaptorDB, really excited about it. So basically, our older technology, MariaDB, we evolved that into what we're calling RaptorDB, which is Postgres plus Swarm64 technology, an acquisition that we made a year and a bit ago. That basically is a better, faster, stronger database. And so all of our customers will, over time, be migrated from the MariaDB over to RaptorDB. And it's a very easy migration happens overnight. We've had no issues. That's just a basic RaptorDB. Then we have a supercharged version of RaptorDB that basically increases the performance by over 12x and then analytics performance and reporting over 27x. So that's like the supercharge what we call RaptorDB Plus, and that is an upsell SKU. And if you think about, to your point on the second question, really thinking about automation platform in an AI-enabled world. That ability to process and perform 12x faster and have inquiries and queries 27x faster is a really compelling value proposition for our customers. And so that's super exciting. On the data specific question, right? And so if you think about the opportunity for ServiceNow, we have been really successful sitting on top of the application sprawl that has happened, right? And so we integrate seamlessly with all the applications, we can hide the complexity, and we can pull the information and drive action from it across the enterprise, whether it's in IT, HR, customer service, legal, finance, really across the enterprise and hide the complexity and drive action. We can do the same thing with data. So what's happened with data? Data sprawl, data is everywhere. We need the data, but how do we use the data, how do we use it to make great decisions. How do we manage the data, govern the data, we can sit on top. And so this is what we talked about in our last earnings call, Workflow Data Fabric, which is a bundled combination of obviously the RaptorDB Plus database, [indiscernible] connectors, right, that connects into the different databases. Our zero-copy technology partnerships that we made with the likes of Databricks and Snowflakes as well as IntegrationHub in a couple of other products. If we put that all together, the vision is to be able to let the data sit wherever you want it to sit. So customers don't have to change their data strategy. If they're using Snowflake, if they're using Databricks, if they're using ServiceNow, they can leave the data where it is, but ServiceNow can pull it and action all of that data across the enterprise, whether it's customer data, whether it's employee data, whether it's IT data, whether it's weather data and your manufacturing plant in a hurricane area. And so think about the ability to streamline the data sprawl as we have been so successful in streamlining the applications for all? And that's what we're calling Workflow Data Fabric.

It just -- it seems like you continue to find ways that the platform can extend its position. Can you talk about that in the context of M&A, right? Like many software companies when they get to the scale, have had to look to M&A to get into an adjacent category to kind of accelerate something that may take a longer period of time. You seem like you've been able to innovate, tuck certain technologies in and continue. What makes that the right framework? And how are you finding success at this scale still using that type of framework?

Yes. So I want to be clear. We haven't utilized M&A to kind of like drive revenues. We haven't bought revenues. But we have done a ton of M&A on kind of smaller tuck-in technology type of acquisitions, talent acquisitions. We just talked about two, Element AI, Swarm64. And so that ability to kind of build incredible innovation, while at the same time, bringing in technology innovation from an M&A perspective, you'll continue to see us do those types of tuck-in M&As, but we've always also said that we wouldn't be doing our jobs if we weren't looking outside of just that. It's not something that we have to do to hit our targets. We have -- we've just talked about a ton of opportunity in front of us. But at the same time, there's so much opportunity out there as we think about where AI is going and just where the industry is going, we wouldn't be doing our jobs if we're not looking. Our focus always on any type of M&A is, does it drive customer value, does 1 plus 1 equal more than 2 and how does it help customer value because that's the only thing that's going to drive shareholder value, right? And so the hurdle rates for ServiceNow are really high. So our strategy has not changed at all, so yes.

It's a good answer. Any initial impressions you can give us around Amit. I know that ServiceNow, obviously, you have a deep team. We've always been impressed whenever someone is presented to us from the outside, but there's been a very tight culture of talent. I mean it seems to us it's been a competitive culture for a long time, but in the right way. What are the attributes that you've gathered around Amit thus far? And how would you kind of present his profile for investors who are just trying to figure out where that fit with the innovation layer.

Yes. Yes. So I'm so excited that Amit is with us. So he has literally, from day 1, been driving that value. And so it was really important for Bill and the entire exec team that whoever filled that role really was a culture fit as well as having all the expertise, right? And so he is, and Bill says this, he's an engineer's engineer, deep breadth of knowledge and experience and then his experience at Google Cloud, thinking about how AI is going to drive and integrate the data strategy is just fantastic. And so he's been spending, as you would imagine, tons of time with the team and he inherited a very strong bench, which is great. And the culture, he's hungry and humble, that is like the ethos of ServiceNow's culture, and he exhibits it like he effuses it. And so he comes in, and he doesn't think he's better than anyone and else, he wants to learn, he wants to know. And he came to ServiceNow for a reason. He loved the product. He loved what we were doing. And he's just been -- even though it's only been a short amount of time, I'm just super excited. The team really enjoys working with him, and he's just -- he gets it, and he's just a great add.

That's great. Yes. I mean most of our conversation is focused on growth, and it makes sense because you have all of these incremental growth opportunities. But ServiceNow has also always had a very balanced financial model and you've been able to deliver margin expansion. What is enabling that still? And I'm wondering if in any way, there are internal gains you're seeing from either things like the shift of the Raptor architecture or internal efforts around AI that give you, I don't know if it's more optimism because you already have good margin, a better sense of what can enable margin expansion.

Yes. I think, first of all, there's inherent leverage in our model, right, because we are this one platform. So the innovation that we build is platform-wide, right? And so there's inherent leverage in the R&D that we have been able to continue to reinvest. While accreting margin at the same time, we have not stopped investing. And so there's inherent margin leverage there. There's inherent margin leverage on the go-to-market side. You've seen we have pretty strong best-in-class sales efficiency metrics as well. And certainly, AI internally helps that. We are -- we talk about Now on Now, which is our customer 0. We're customer 0 for almost every single product that we have. And so the productivity and efficiency gains that we get every single year from implementing the new products we have used to reinvest and AI is no different. I've talked externally already that just the use cases internally that we've launched on our gen AI SKUs are upwards of $15 million of annualized savings that we've been able to reinvest into the business. And that is like year 1, right? And so we remain really disciplined in driving both top line growth and bottom line. But at the same time, growth is our #1 priority. And so if there's an opportunity that we see to supercharge growth and reinvest dollars, we're always going to choose that, while at the same time, making sure that we are maintaining best-in-class margins and obviously accreting to the guides that we provide.

That's great. So you're definitely right. We're not going to make it through all of the questions, it's time for one more. And so I want to turn it over to you for kind of closing thoughts and framing both the importance of the rest of the year for ServiceNow. And then the signals you're watching that will inform your priorities -- prioritization, willingness to spend in '25 and beyond. Investors are much more focused on, I think, 2025 at this point. So maybe help frame the out-year and just where the big points of focus are?

Yes. I mean I think I talked about the big points of focus, right? Gen AI, front office, federal, international growth is another area where we're underpenetrated and have a ton of opportunity. I think what's really important is and we get this question, I got this question from investors a lot the last few days. You know what tends to happen is you overestimate what can be done in the year and underestimate what can be done in 5 and 10. And I just think that we have, while we absolutely have been super focused on strategically where AI is going to take the enterprise, and we will remain focused there. The expectations of what can happen in a year versus what can happen in 5 and 10, I think, are really important. And so we have been very focused on investing in those growth opportunities. We've pulled forward some headcount from '25 into '24 because we see those opportunities. But at the same time, while we're monetizing, I think most people think we're monetizing better than most. It is early days. And I just want -- what I want folks to really understand is that ServiceNow is so well positioned for what's to come in an AI-infused enterprise, and we will continue to invest to ensure we stay on that forefront, but let's not overestimate what can be done in a short amount of time and not underestimate what can be done in the midterm.

No. That's perfect. Great note to close on, Gina. Really appreciate you making time.

Thanks so much, Michael. Appreciate being here. Thank you. Thank you.