Expensify, Inc. (NASDAQ:EXFY) Q4 2024 Earnings Call Transcript

Expensify, Inc. (NASDAQ:EXFY) Q4 2024 Earnings Call Transcript February 27, 2025

Expensify, Inc. beats earnings expectations. Reported EPS is $0.1, expectations were $0.07.

Anuradha Muralidharan: Hi. Welcome to the Q4 2024 and Fiscal Year 2024 Expensify Earnings. Before we get started, we’re going to kick it over to Nikki, who is going to read the legal disclaimers.

Unidentified Company Representative: Please note that all the information presented on today’s call is unaudited. And during the course of this call, management may make forward-looking statements within the meaning of the federal securities laws. These statements are based on management’s current expectations and beliefs and involve risks and uncertainties that could cause actual results to differ materially from those described in forward-looking statements. Forward-looking statements in the earnings release that we issued today, along with the comments on this call, are made only as of today and will not be updated as actual events unfold. Please refer to today’s press release and our filings with the SEC for a detailed discussion of the risks that could cause actual results to differ materially from those expressed or implied in any forward-looking statements made today.

Please also note that on today’s call, management will refer to certain non-GAAP financial measures. While we believe these non-GAAP financial measures provide useful information for investors, the presentation of this information is not intended to be considered in isolation or as a substitute for the financial information presented in accordance with GAAP. Please refer to today’s press release or the investor presentation for a reconciliation of these non-GAAP financial measures to their most comparable GAAP measures.

Anuradha Muralidharan: Great. Thanks, Nikki. All right. Let’s get started by reviewing the Q4 2024 financials. Revenue was $37 million. That’s a 5% increase both quarter-over-quarter and year-over-year, which is great. Let’s the revenue go up. Average paid members were 687,000, which is also up slightly. It’s essentially flat, but last quarter, we were essentially flat and down very slightly. Now we’re slightly up. So we’ll take slightly up over slightly down. And interchange was $5.1 million, which is a 62% increase year-over-year. The card continues to grow at a greater cliff is a bright spot in the company. Operating cash flow was $7.4 million. Free cash flow was $6.3 million. Our net loss was $1.3 million, almost there to get profitability.

Hopefully, we get there soon. Our non-GAAP net income was $8.7 million, and our adjusted EBITDA was $12.4 million. Now let’s talk about fiscal year 2024. Our revenue was $139.2 million. Our average paid members were 686,000 and our interchange was $17.2 million. Our operating cash flow was $23.9 million. Our free cash flow was $23.9 million as well. Those numbers aren’t usually equal. There’s a reconciliation in the appendix that you can take a look at just coincidence, we double checked that we’ve had [indiscernible]. Our net loss was $10.1 million. Our non-GAAP net income was $23.5 million, and the adjusted EBITDA was $39.4 million. Great. Now let’s dive into free cash flow. For Q4, free cash flow was $6.3 million, a 272% increase year-on-year.

Q&A Session

For fiscal year 2024, free cash flow was $23.9 million, a 4,200% increase year-on-year. I know that’s a large percentage increase. We’re just highlighting it to really signal what a one day difference, our free cash flow situation is from where we were in 2023. Now let’s talk about guidance. So last year, we — our initial guidance was free cash flow at $10 million to $12 million. Obviously, we tremendously outperformed that. That is due to a couple of reasons. One, the company performed significantly better in 2024 than ahead in 2023. So that was great. And also, we implemented a lot of efficiency, improvements with AI and other things like that. David’s going to touch on the AI piece in a moment here. So, when we look at 2025, our initial guidance is $16 million to 20 million which is obviously significantly higher than it was last year.

I do want to note that there’s some conservatism baked into this number, because we’re not sure how the macroeconomic environment is going to play out for our customers. So this is a number that we feel good that we can hit even if things don’t go great. But, as we see these kind of policy changes and everything play out and our confidence grows, we’ll update this number accordingly. Now, let’s talk about the Expensify card. We had strong growth. Expensify card grew 11% quarter on quarter to $5.1 million and interchange grew 54% year on year to $17.2 million. Also, very happy to announce that the card program migration went off without a hitch. We are now fully migrated. The migration’s over. We’re very happy about that. It simplifies the accounting story.

All the interchange is going into revenue, where everyone expects it to be. So this won’t be something we need to discuss going forward. Our fiscal year 2024 interchange that was included in revenue was $9.2 million. In Q4, the interchange in revenue was $5 million. And the total interchange for the year was $17.2 million. Now we always talk about, how the latest month went, from a paid user’s perspective. In January, we had 665,000 paid members, which is lower than we saw in Q4, but that’s to be expected. We’ve highlighted in pink on this chart, previous January. So we usually see, some significant seasonality in Q1 and we’re seeing that again this year. Now let’s just talk about some business highlights to round everything off.

Expensify Card. Like I said before, it was a great year, grew 54% producing $17.2 million total interchange, and we fully migrated the card program. Our free cash flow increased year on year by $23.3 million compared to fiscal year 2023. We launched Expensify Travel, which adds fee based and transactional revenue opportunities for the business. We’re very excited about this. Customer enthusiasm has been super high, so we look forward to giving you more updates on that in the future. And last but not least, we reduced all of our debt. We paid our debt down by $22.7 million and we’re now debt free, something we’re very proud of. Now, I’ll pass it over to David.

David Barrett: Great. Thanks. So, as we just saw, Q4 was a great quarter. If every quarter were like that, everyone here would be incredibly happy. But we set out to do is more than just have, sort of just, uptick quarters. We set out to do something really big. So kind of going backwards, if you will, to the start of our IPO and talking about what has happened since then and what’s changed to now. So starting with basically what hasn’t changed. Basically, the opportunity size is still enormous. If we look back to kind of our initial TAM and so forth, so much of it is still untapped and so much of it is still largely the same in terms of competitive dynamics. Viral lead gen is still the most scalable model out there, and we’re the ones that are focused on bottom up adoption.

So the core acquisition model hasn’t changed. Likewise, the payment super app is still a huge hub of data that captures basically the same viral lead gen transaction revenue, subscription revenue, all packaged just in place. That strategy is still a great strategy. So fundamentally, the core tenants of what we set out to do are still in play. The strategy is still a sound strategy. But some things have changed in a very significant way. I’d say AI is finally here. And most interestingly, AI is based upon chat. It’s not called e-mail GPT, it’s called ChatGPT. It’s called that for a reason because the language of AI is English. And the way you communicate on English and computers is primarily through chat. So I know there’s been a lot of questions as to why we’ve been leaning so heavily into chat, basically, what is the chat-based attention for and so forth.

And a lot of people would say it was like, well, I don’t want to replace Slack. I already have a Slack. I don’t need a new Slack. And I would say, it’s not about Slack. It’s not about business chat. It can be. You can definitely use Expensify Chat to collaborate with your colleagues. But the most important thing is doing Expensify Chat to collaborate with concierge. Concierge is our primary sort of AI-first experience built throughout the entire product because I think we’ve learned early on that the UI of the future is a chat-centric UI. What we are building with new Expensify is what everybody is going to look like in 10 years, but we’re bringing it to you now because it’s not just about talking with your colleagues, it’s about basically having the super intelligence built into the app in a simple way you can communicate with it.

So just like ChatGPT, you can talk to concierge in the direct conversation. But unlike ChatGPT, you can also talk about it about data that is unique to you. ChatGPT knows maybe everything about the public world. Concierge knows everything about your private world. And it’s not just basically general conversations about the data you have access to, it’s highly contextual conversations. When you talk with the concierge inside the context of an expense report, for example, you’re talking about that expense report, about that employee. We’re talking about a particular approval flow. So it’s telling you things that are actually unique to that particular report and you respond to it and you say, like maybe I want to approve this, but not that, and can you forward to this person.

Our concierge AI has the context and understanding to actually do this more sophisticated action for you. So I think we’ve seen that ChatGPT can bring a tremendous amount of efficiency across the board, but it’s limited by what it doesn’t know. Concierge just knows more, and we’re bringing it to you in that context. And so when you kind of think about what happens when you take a super intelligent chat and you combine it with super app data, you get Expensify. And it’s a very unique combination because fundamentally, expense management is special because we process all of the company’s payments. We know where every dollar comes into and goes out of the organization, whether it’s expense, card bills, invoice and so forth. That’s a tremendous amount of awareness that our AI has that no one else has.

Likewise, we’re actually in the pockets of every employee, whether it’s not just the finance team, it’s a sales team, it’s a C-suite. Everyone in the company basically is using Expensify, talking to concierge and getting that sort of efficiencies built into the financial experience. Likewise, we physically know where people are through our travel duty care functionality. We know not only where you are right now, but where you’re going to be in the future and when. Similarly, we know how the company is organized. We know not just basically who you are, but we know who your boss is. We know how many entities are in the company, what the departments are, who’s in those teams, who your clients are and so forth. Finally, I would say we have access to basically anything we don’t know, we can reach out to outside organizations and pull it out because Expensify is already tapped into accounting systems, HR systems, CRM, payroll and so forth.

And so expense management is really the nexus of all of the company’s data, and we’re powering that data basically with our super intelligent concierge AI. And so as such, when we kind of think about fundamentally the future, what we set out to do at the IPO. Now I would say Ryan and I were both Midwestern, we’re pretty humble. We don’t like to make big boastful claims, if you will. So the humble goal that I think we set up for the company is total fintech AI to primacy. And now we’ve talked a lot about basically how the entire industry is converging in a number of ways. We said early on that like the industry is going to go towards real-time expense reports, everyone kind of followed. We said a long time ago that the industry is going to move towards sort of product suites and super app designs and everyone is moving that way.

And telling me now the whole industry is going to move towards a chat-centric design. We’re already seeing early signs of that and sort of others as well. And I think that’s because fundamentally, everyone’s following the same kind of process, so bring super intelligence into their legacy applications. And it kind of follows maybe three steps, if you will. First is everyone’s going to start with what we call kind of deep AI, and that’s taking all of the minimal judgment repeatable tasks and viewing them as a training basis for the AI itself because when you have any sort of AI, it all comes down to, it’s only as smart as the data you can train it on. Any sort of legacy incumbent player has in our case, 15 years of receipts and human-generated data that no one else has a very, very defensible, unique asset that no one else can have access to.

We use that to train our AI on the nuances of our domain. And in the process, we also happen to create huge cost savings. Now I’ll dig into that a bit more because there was a big part of the Q4 story or really the fiscal year so 24 story. And so we talked about sort of our AI is delivering strong free cash flow gains in a few different ways. Starting first with SmartScan. What we did is we were able to increase the speed in accurate smart scan and dramatically reduce the cost basically taking the system that was previously a combination of OCR, our [indiscernible] human fallback and so forth and largely replaced it with sort of this new LM technology going back to those IPO slots, basically, this we’re talking about SmartScan look like them, is what it looks like now.

Basically, we’ve augmented our OCR technology with new LMs and in the process almost entirely removed human review from the process. And so this is a big deal. Similarly, we’re basically doing the same for concierge. We’ve brought concierge LM technology. And in the process, we have faster chats, more natural chats and most importantly, 80% fewer human interventions kind of going back to those IPO slides. We talk about how our concierge systems have a high favorite AI sort of multitiered system, where the user writes a request, it goes to someone called a first responder who evaluates a series of sort of canned repeatable responses. And if they can’t do it, it goes to a second or smarter and so forth. With our new upgrades in the last year, now the almost entire actually completely replaced the first responder tier and just using not just repeat of responses, but bespoke and very customized responses to the user that have been trained not only in our sort of public health documentation, but are extensive and in historical conversations, all those sort of repeatable conversations and all the expertise that we’ve built up over years, that is a unique proprietary training data set for our AI, there’s one reason why the concierge I is so smart because it understands everything about how the domain of expense management works.

Likewise, this is kind of a smaller one, but it’s an important one. QA is obviously important for any high-quality product. And so we have a bunch of — you can talk to a salesperson, you can talk to your account manager and all this happens over the phone. Now obviously, we’ve been trying to record these calls, QA calls in the best possible way with industry standards. We ran them with sample calls. Some person listens to them feels like a QA check list, things like this. We switched over to a new method where 100% of our calls are transcribed using AI. We will review these calls against best practices using the AI itself, so we can score them all and then actually do proactive coaching. So it’s not just a matter of saying, “Hey, you should pitch the expensive card every time we talk to a customer because it’s easy to say that, but it’s hard to apply that feedback.

If the call is not really about that, it’s hard to figure out how I naturally bring it in a way that’s actually going to work. And so what our AI coaching does is it will take the transcript of how the call actually went. And they’ll say, here specifically, had you said this, this is how you could have brought the conversation in. And so with this proactive coaching best practice scoring and so forth. In the past month alone, we nearly doubled the number of perfect calls, meaning calls that successfully hit every single point that we’re trying to touch on the call into them the right way. That’s a huge increase for a single month, and we’re just getting started. Last but not least on this list is engineering. So now engineering, obviously, an incredibly important part of any SaaS business.

And one aspect that we’re investing in, we’ve been investing in for a while, is trying to use AI to the maximum for cogeneration, automation and testing and so forth. And it’s not just us. You might have noticed that actually open AI selected us as the basis of their most recent coating benchmark, because the way that they train their AI is by creating a new more difficult benchmark than anything else and then evaluate all the different models against it. Now, in order to do that, they need a rich open source ecosystem that has well-defined tasks, that have all the management steps laid out there,, because it’s not just how can you generate the code, but can you understand the requirements, the design docs, can you take the feedback from the company and so forth.

We’re the only company that has an open source repo like this, where we’re actually creating issues at this scale and then paying freelance contributors around the world, so it makes a unique asset for how do we evaluate open source models. And so this is why OpenAI picks the Expensify code base as actually their most important model for how they train the next generation of AI engineers. And I think this is just a sign of kind of the things to come. Across the board, I mean, AI is obviously is here, it’s growing, and we want to make sure that we are on the leading edge of every single part. Now — and I think the reason that we can do that is because our company is special. Now we’ve talked about how the company is an unusual company. We’ve got about 120 people right now.

And if we’re able to do what we can do with 120 people, any company doing something similar with thousands of people must be doing something catastrophically wrong. And Expensify is able to do this for the team that we have, because we’ve organized in a way where everyone on the core team is trying to focus on innovation, automation and outsourcing. Everyone’s job is to replace themselves some way possible. And we can talk about this in a few different ways. So yes, internally, we can — initially, we scan receipts, we figure how to do it, but we only do that enough and we innovate the process to make the best experience with the customer. Then we’re able to bring in sort of like U.S. agents and international agents to sort of process receipts, scale up the massive basis creating this huge archive repository or CTWs, to train our artificial agents.

And now we can bring them in basically on an equal basis to our historical human agents and dial back the number of human reviews that we need dramatically. And so our Smart Scan Technology is still a hybrid system involving humans, reviewing the AI, AI or in humans and so forth, but more and more, we can lean on the AI to scale up even further. Similarly, when it comes to concierge, we talked about how we started off with the first responders, and we can escalate to second responders. We’ve give this training resource to eliminate the first responders here entirely and no longer basically have a team devoted to sending the best repeatable response for rather using AI to generate a bespoke answered every question and do it quickly in a very low cost.

And also, we’re working with that in the engineering side as well. And that basically, we’ve long had basically this freelance community of thousands of engineers around the world. We’ve augmented that with, what we call expert agencies, truly the best of the best, the people who are developing react native and the technologies that we have are all working with Expensify. And in the process, we’re also creating this huge training data set that we can use to build the best artificial contributors. And so — and obviously, we’re not alone in seeing this opportunity. We’ve already been talking — basically, I talked about how open AI identified us as sort of what are the leaders in this open source opportunity. And so the company is unique, because we’ve got this very core team and everyone on the team is leaning forward towards innovation, automation and outsourcing.

And you might say, well, every company is like that. And I wouldn’t say that’s necessarily true. If you have thousands of people in your company and 500 of them are actually no longer the most effective way to do the job. That’s a huge tension inside the company. And so we don’t have any of that tension. Everyone here is focused on viewing AI, doing outsourcing, doing automation as a way to supercharge their own jobs and not a threat to their jobs. So first, super intelligence and 3 easy steps or deep AI was the key for delivering free cash flow gains. And I think everyone’s kind of start with that. That’s sort of like low-hanging fruit. Then we go to sort of what we call surface AI. And that’s where you take the AI after you trained it on the basics, now it knows enough budget domain to identify opportunities and then reach out to the user with some sort of request and then accept the response.

Now to give an example of how that works. Like one of the features we’re building, we call conversational corrections for basically, imagine you create an expense, $7 for something called subway. Now that’s kind of an ambiguous request. And it’s pretty straightforward and say, “Oh, okay, subway, is that for a sandwich or is it for a train? And does is it categorize as meals or is it categorized as driving transportation? And you can do that and then also you can make it really easy to take those two options. But where the AI becomes valuable is what it allows you to respond to the third option, it’s unexpectedly. And so actually, no, that was a typo, it should be Safeway and it’s for snacks for the office. And the AI has to be smart enough to know what is Safeway, what does that even mean?

How do I interpret this answer because we offered them two choices, and they came up with some third unexpected choice. The AI is there to receive these more sophisticated responses and not just do it the app because it’s a text center guy, it also works over text and email. One unique design of Expensify, everything is designed to reach the user wherever they happen to be. Yes, it works best in the app. But if you don’t want to use the app, if maybe you actually want to talk to us over SMS or just receiving respond to e-mails, that works too. And our chat centric design scales into all these different platforms. It’s a completely different way to think about user interface design away from trying to create a whole bunch of buttons that you’re going to press and more towards us creating conversations with users and allowing them to express to you in natural language what they want done.

The third step here is, we start with deep AI develop base line, starts to sort of show this in more advanced functionality but the real super human results kind of come in the Thursday, try to call it kind of elevated AI. And that’s where AIs are doing things that are really just too big and too fast and the analysis are too complicated to be done by humans and then allowing you to detect this in real time. And then escalate it to you, why you can still do something about it. So it’s not reacting to something after it happened. It’s kind of pre-acting to something before it happens or while it’s in the middle of happening. To kind of get some examples. One feature we’re building into Expensify that we call kind of a virtual CFO. And basically, it should be doing a variety of the things that you would like your CFO to be doing like real-time fraud protections and things like this.

But imagine a conversation of Concierge reaching out to you and say, heads up, Alice’ corporate card is showing some unusually large infrequent purchases but she mentioned over here in social that’s using vacation mall should I block her card to be safe. Now this kind of conversation is something that requires you to be tapped into a lot of conversations in the organization to infer what’s happening about someone. Even if, in this case, Alice didn’t mark herself has gone in the calendar, she said that she’d be gone, and that new information can be discerned basically from the AIs and then connected with the other data that we have to make an opportunity not to prevent fraud that you might have not noticed otherwise. Likewise, sort of most organizations will do some sort of flux analysis at the end of the month, but we don’t have to wait at the end of the month.

We can basically be doing continuous flux analysis. So you can see what’s happening and you can step in, in real time. So for example, if we say here, hey, I’m during this month’s expenses. Everyone is normal, but I see a big spike in hotel expenses developing but don’t worry, I think it’s for this conference being discussed right here. So basically, saying something is weird, but we think it’s onetime — based upon this information that appears nowhere else in the system but does appear in a chat. Similarly, if we can say things like cash forecasting incredibly difficult, but if we actually are able to bring your income and your expenses and combine that with basically all the data from the organization. We can find things like, hey, based on your invoice has built and historical card spend, it looks like cash might be tight in Q3, so why not pump the brakes in this ad campaign we can discuss in the marketing.

This is the kind of thing where, historically, you’d only know this after they go through the work, make the proposal do some sort of a cash forecast and you realize, actually, sorry, everyone just wasted 1,000 hours at their time because we can’t actually afford this. We can catch these sort of things earlier — earliest that’s what we’re aiming to do by integrating all those data together. And then finally, the same thing for sort of financial management. If we see that you’re building up a cash forward, and we see your intention is behind it, and you’re not going to spend it for a while that creates opportunities to manage that money that might not be visible elsewhere. Fundamentally, we think that AI is a title wave. It’s going to come and it’s going to change absolutely every industry it touches.

It expense management, especially because it is so tapped in to every single part of the organization. So it’s a big change that’s happening. It’s a scary change that’s happening. And the only way – avoid being pulled under is basically to make yourself into a set [ph] that’s what we’re doing with new Expensify. We want to basically view this title wave as an opportunity as an exciting ride that we want everyone here to take with us. So in conclusion, last quarter was great. It’s been a super exciting year. We completed some major investments in deep AI. We’ve really improved our profitability or debt free, which is a huge accomplishment. We transitioned all of our spend away from the — towards the new expense back card, which is so great.

We launched Expensify Travel. I mean now it’s really a complete T&A solution. We’re migrating customers methodically from Classic to new Expensify. And then overall, it was just a great quarter and it’s an exciting year, and I think that 2025 is going to be even more exciting still. So with that, are there any questions?

A – Unidentified Company Representative: Perfect. Can you hear me?

David Barrett: Yes.

Unidentified Company Representative: Okay. Great. Let’s get started with Citi. George and Stephen, I think you’re both on the line.

Q – Steven Enders: Yes. Hi. You got Steven here. Thanks for taking the questions from our end. But I really appreciate the deep dive on the AI side. I just want to get a little bit better understanding for kind of where the capabilities sit today, kind of what’s still on the — what’s still kind of in the pipeline that you’re working on and have everyone engaged on? And I guess secondarily, for these initiatives to work the way you’re thinking like does all of this need to sit within the Expensify app in the chat today? Or can you go out to third-party systems like Slack or other financial systems to integrate all that data view there?

David Barrett: Great questions. And so as for what sort of exists today and what’s coming, I would say the things that we talked about in deep AI already done, basically, the concierge SmartScan and the QAing of calls, that’s all done in practice right now. I mean, obviously, we’re improving in all of these. And so — but I’d say that these are real systems creating real benefit right now. For a lot of kind of the more surface AI stuff in terms of user interactions, I’d say that’s all under active development hasn’t been released yet, but it’s real. It’s coming — as we think more on sort of the future virtual CFO stuff, it’s like prototype, it’s basically — it’s demonstrated, but it’s not kind of like production ready. Everything here, however, is it’s fundamentally real.

Like if there’s stuff exists, we know that it can be done. It hasn’t been launched yet, but it’s coming. And so we don’t have a specific time line for that. The stuff we need to do work really well before it’s worth launching. But this is not vaporware.

Steven Enders: Okay. That makes sense. And then from, I guess, an integration perspective, like does all this adoption need to happen within Expensify itself, like, specifically some of the chat stuff or — and I guess, again, like the third-party system integrations kind of…?

David Barrett: Sure, sure. So one thing we certainly talked about is integrating with other server chat systems, we’re not opposed to that. As was sort of mentioned, one of the advantages of a chat system is that we can kind of meet you where you are. And so right now, we focus on our app, e-mail and SMS, but we certainly talked about what’s a Slack integration as well. One of the challenges, however, is that as we do this, the benefit of the technology is that we can build it in the context of the expense management itself. So for example, with Slack, we can’t show you your expenses inside of Slack, and it’s weird to have a conversation about your expense report outside of your expense report. And so I think there’s some kind of an impedance mismatch for how our data is structured and how a traditional chat application is structured.

But fundamentally, I agree with the thrust of where you’re going and that is we need to meet the customer where they are. And for the right use cases, it would make sense to talk to concierge in different chat systems. The more deep you get into the expense management stuff, the more it just makes sense to be part of the expense management system itself. Is that correct?

Steven Enders: Yeah, that’s great. I guess that then kind of leads to the next question of if your customers aren’t, I guess, necessarily using the chat functionality to that degree today, what’s kind of the pull to get people to then I guess, drive broader adoption of expensive and use it kind of the way that you’re hoping that we’ll take that on?

David Barrett: Well, first, I would say, I don’t know if I agree to using it this way right now. The process of migrating customers over, and one thing we found is that it’s pretty sticky. When customers migrate over, they typically stay in Expensify. So they like what they find. Now we’re I would say, fundamentally, what we’re doing is just scaling it up for larger companies. We’re scaling it up for more advanced flows and so forth. But it’s a working system that people use and enjoy today. Again, everything is getting better, but it’s already pretty good according to the users who are using it right now. But I also do think that what’s nice about the sort of chat-centric stuff, especially like I would say, some of these virtual CFO functions, I’m super excited for because they start to show how we can pull customers into a chat context by giving them something to talk about.

So, for example, ChatGPT right now, it just sits there idly waiting for you to have a question and then it gives you an amazing answer to that question. But because ChatGPT doesn’t know anything about you fundamentally, it’s just kind of idle. We’re different. We’re basically working for you 24/7. And so as a result, we have a lot of things that we can observe. And I think this creates the opportunity for Concierge to reach out proactively in these different contexts and then pull you into these highly contextual chats, thereby, demonstrating the value of this integrated contextual chat. That’s maybe a lot of words said there. But fundamentally, I’d say, I think that this functionality is a way to demonstrate the value of chat rather than having to sort of imagine what would I do with this chat function.

Did that answer your question at all?

Steven Enders: Yes. No, that’s great context there. So I definitely appreciate that. And, sorry, last question for me. Just on the travel side of it, good to see that’s out there NGA now. But I guess, how are you kind of — what adoption have you seen so far? How are you kind of thinking about what that could look like over 2025?

David Barrett: Yes. So in the initial group, we saw a lot of enthusiasm. We saw a very large increase month-over-month in the travel book. Now that was for a small portion of our customer base. Now that we’ve launched to everyone else, I think it’s — we launched this week. So it’s too soon to be drawing trends, I think, but our account managers have basically been overwhelmed with interest in a million different questions and all that. So I do think that, it’s going to be exciting for Expensify Travel in terms of will it be material to revenue? I think it could be — I think, it will be likely like the card, for some period where it keeps telling its growing. That is small now. That is small now. And it was like, okay, and then eventually that actually, it’s gotten quite large and it moves revenue in a meaningful way, even if subscriptions aren’t necessarily going up. So I think I view the same ID card. Does that help?

Steven Enders: Yeah. No, that’s perfect. So I appreciate you taking the questions from our end and turning back in the queue here.

Operator: Great. Next, Aaron from JMP

Aaron Kimson: Hey. Thanks so much.

David Barrett: Hey Aaron.

Aaron Kimson: Hey guys. So we’ve talked in the past, you’ve discussed trying to get to a new normal by summer 2025. What does the new normal look like in terms of the day-to-day of the business and progress with New Expensify? And does summer 2025 still sound like a reasonable timeframe?

David Barrett: Sure. Great question.

Anuradha Muralidharan: Maybe I’ll take a crack at this. I see what you have to say. I would say new normal means every customer signs into Expensify and sees the new brand. And it goes through basically a New Expensify Centric sales model, all of our — and then we have a sizable contingent of customers, basically talking about New Expensify, because fundamentally, your brand is what your customers tell their friends. But most of our customers today are using our Classic product. And so Classic is still kind of our brand. And so the new normal would be, when we get enough customers over to the new product, that, that becomes our new brand that generates a new word of mouth. And it sort of creates the expectations of when someone comes to Expensify, they’re coming based on a description of this AI-Centric Expense Management application, as opposed to kind of a traditional Travel & Expense Tool.

And so I think that by summer, like now summer is obviously a big deal for us. Obviously, you probably know, we’re sponsoring the Apples F1 movie. It’s going to be a big deal. And so it’s kind of like — I know we did a Super Bowl ad a while ago, but that was 30 seconds. This is two hours of seeing the team expensive name on the giant screen in front of you. The impression on that is so much bigger. And so we expect that that’s going to create a lot of awareness. And we’re going to try to capture that awareness. So all of the first half of this year is building up to make sure that we’re ready to absorb that interest and the second half of the year is really about converting that interest into action.

Aaron Kimson: I agree. Got it. I actually saw the trailer the other day. And I agree, great logo placement for you guys. Second question, on the spectrum potentially of kind of potentially in 2025, so far out in the future, where we see you are in terms of maybe being able to use price as a lever to drive growth when weighing kind of the choppy macro for SMBs versus increased product functionality? What’s been a sticky inflationary environment for a few years now and then not having taken price, I think in, call it, three years, if that’s right?

Anuradha Muralidharan: I think my instinct is we’re going to keep the price where it’s at for the near-term future.

Aaron Kimson: Yeah.

Anuradha Muralidharan: I think when we have all of our — when the platforms are a little more mature than it’s now and we have a broad suite of super hardened products then at that point, I think our price becomes kind of silly low. We won’t really see any backlash from customers on a price increase. But I don’t think we’re there yet. But just to remind you, so the plan is expense management, free corporate card with 1% or 2% cash back, full corporate travel management invoicing, bill pay, chat, hold much AI functionality and also P2P, consumer money transmission for $9 a month. So, that is the goal, and that’s steel, it will cost probably $100. There’s something to have to buy all that individually. So, I think that we are building the conditions where we would have immense pricing power, but we don’t want to put the car in front horse.

David Barrett: Yes. I agree with that. Sort of one thing we talk about internally is this idea of like this kind of a Red Ocean strategy versus the Blue Ocean strategy. Red Ocean is like highly competitive blood and water sermons fighting each other to the death. But there’s a huge opportunity out there that’s largely uncontested. And so I think the way that we go after this large market is really about bringing a tremendous lot of innovation and producing it at an incredibly low price. And so I think that there’s a huge opportunity out there. Our primary method, we expect of making money in the long run is by growing to acquire new customers, not just basically squeezing existing customers hard.

Aaron Kimson: Got it. Thank you.

David Barrett: Thank you.

Operator: All right. Next, we have, I believe, Mark is on the line with us.

Unidentified Analyst: Hi good afternoon. Thank you for taking my question. David, let me start off with you. Could you just walk us through your investment priorities for the coming year?

David Barrett: Investment priorities for the coming years. So, I’d say the most important, as I sort of mentioned before, is lining all of product and marketing and go-to-market basically up for this F1 release in the summer. And so what that means in a more practical basis, a lot of testing, a lot of QA, a lot of just polishing up functionality. Like one thing that we do is when customers come over, we analyze basically their usage of the product itself, we proactively — without waiting for them to report bugs, we find the issues, we fix them, we optimize and so forth. So, a lot of mundane stuff. I mean, it doesn’t sound truly revolutionary, but it’s really important stuff. And so I do think the nice thing about AI functionality is that if you have a platform like ours, which is a chat-centric design, designed to allow you to communicate to an AI as well as the AI communicate to you in every context, it’s actually quite easy to bring in more AI functionality.

We don’t need to create a bunch of like new UI elements and controls and so forth. It’s already pervasive. We’ve done the hard work to build a platform to allow AI functionality to basically engage with you. Now, I would say when we roll in some of this AI functionality, it’s relatively low financial investment because the hard work is done to get the data into the same place to get the UI ready and to get all this in place. It’s — so the bulk of our effort really is on just more mundane testing and migration of existing customers and supporting existing customers and dialed in. But we sprinkle in kind of like the appropriate AI investments along the way. I don’t know that really answer the question because if you have any — if that answers your question for you.

Ryan Schaffer: Does that answer your question, Mark, I can expand if there’s — if it did not.

Unidentified Analyst: No, that’s helpful. And then, Ryan, a question for you. Maybe you can just talk a little bit about how customer churn trended in the quarter?

Ryan Schaffer: So, we did have users go up, which is good, right? We’re not seeing a huge change in churn — obviously, the paper-use users are always kind of volatile. But I think as our new expense a continues to get better. I believe increased the performance of our sales team with Dave talked about kind of our investments there. And we’re — and it’s seen some encouraging signs.

David Barrett: Yeah. I think so. We’ve put a lot of effort into account management, and I think that’s really, had good effects as well. So, fundamentally, I think it’s just a stable trend, I would say.

Unidentified Analyst: Thank you. That’s all for me. Thanks.

Operator: Next up, we have Lake Street Capital. I believe, Max, are you still on the line?

Unidentified Analyst: Yep. I’m still on the line. Thanks for taking my question, guys. Great quarter. Just looking at all these product launches, I mean, with AI then you have expense or the travel product coming online. I mean, if we think about maybe after the Apple deal, in 2025, like what areas do you want to go to next? I mean, what area haven’t you tackled? Maybe that’s in the back of your mind on maybe that’s the next area or space you want to get into.

Ryan Schaffer: I think next I’m not sure if you agree. I think next is, invoice and bill pay. I think next is, so we have invoice and bill pay. We know it is, it can be better. We know what needs to be done, to make it, you know, truly competitive. It’s great for a small business, but, you know, there’s really strong competitors out there. So I think in terms of investment, travel’s in a great place, expenses in a great place. I think it builds invoicing is the next logical one.

David Barrett: So I would agree with that, but also emphasize that I don’t know that there needs to be a big next thing fundamentally. I think the next thing is getting our all of our customers to use what we currently have. And the next thing is really getting people to understand the value and capture the value and use the value that was already being created. Because we think that fundamentally you know, again, AI is hard to talk about because it’s so eye roll inducing because everyone just says whatever they want and they make it up and it makes it sort of like hard to talk about and feel credible. But I’d say because especially because everyone makes the same claims that they’re going to like, we’ve reinvented everything with AI.

And then you look at their product and it looks exactly the same. Like every product, all of our competitors look the same and they all claim that they’re like the most AI centric thing in the world. We look quite different, and there’s a reason for that. We look different because, we were actually building a different kind of AI centric environment. What we see here, the user experience that we’re making, it might seem radical now in the same sense that ChatGPT seemed like a radical user experience when it first came out. But this is the future of user experience, and everyone’s going to be copying this in ten years or however long it takes them to catch up. And so I think that really the main investment is yes. Bill payment and invoice.

Absolutely. We need to dial that in. But really, it just comes down to we just need to we’ve built out this broad product. We need to really consolidate it, get all of our customers on it, and just keep investing and improving that.

Unidentified Analyst: Great. And I’m guessing the there’s a price tag that comes with that Apple ad. But I mean, in theory, should we see any dramatic changes, I guess, to the non GAAP operating expense structure throughout 2025?

Ryan Schaffer: Yes. So, great question, Max. I’ve touched on this in the past, but it’s good to kind of go back over. So movie accounting by GAAP is kind of interesting. You recognize — you do not recognize any of the expense, until the movie comes out. Because like if the movie doesn’t come out, then what do you do? So we, the money spent for the movie has, that’s already reflected in our free cash flow. That money’s already gone, but we have not recognized it in our sales and marketing expenses yet. So, what you can expect is a large increase on the expense level. But I want to be clear that money has been spent already. So it’s kind of one of the situations where reality and gap kind of, look a little different.

Unidentified Analyst: Yes. Understandably, yes, I was just wondering if there was any other reason to see CapEx…

David Barrett: We’re also discussion on marketing around movie. We’re not just going to the movie seen ourselves there. So in addition to what we’ve paid for the movie, there’s kind of additional go-to-market there as well.

Unidentified Analyst: All right. Again, thanks for taking my question.

Unidentified Company Representative: All right. FT Partners, Matthew, are you still there?

Matthew O’Neill: Yes. Hi. Good afternoon to all. Thanks for taking the questions. A lot of the questions asked and answered. Maybe just quickly, good to see the debt pay down and the reload of the share repurchase authorization. Maybe you can just outline sort of your capital allocation plans as a result above and beyond maybe stock-based comp and so forth?

David Barrett: Yes. So a big debate internally and then also just in general is, we’ve gone from not having much free cash flow at all to having a lot all of a sudden, which is great. And to what extent should that be put towards buybacks first debt, we obviously decided to focus on debt which to be clear. We’re paying a lot interest. Interest rates went up. So we have more free cash flow as a result of paying down the debt. And I think our first priority is obviously, let’s invest in sales and marketing to the extent that we need to. And we’ve done that, and we still think we’re going to have a sizable amount of free cash flow after that. And I think that we’re also hiring. So — but beyond that, we think buybacks are great.

We’ve done buybacks throughout the years when we were private. We were doing by tax which is — what’s the kind of strange for a private company, but we’ve a long history doing buybacks deliverer’s dilution. So nothing to announce right now, but we like buybacks.

Matthew O’Neill: Understood. That makes a lot of sense. And I think philosophically, a lot of what you guys are doing probably you answers this question, but just to kind of cement it as you get a lot of unit cost improvements through automation, AI, right, like the smart scan, 80% for escalations, et cetera. And so as far as the willingness to kind of drive more sales and marketing budget into customer acquisition, things like through the movie and otherwise, is that — we think about that right that as the sort of operating leverage in the model improves, it makes more sense to sort of push into paid user growth efforts going forward?

David Barrett: Absolutely. I mean we’ll see how the movie goes. Yes, I mean — I agree with you that when you have more cash, you can put more towards sales and marketing for sure.

Ryan Schaffer: Yes. I mean we’ve never been shy about taking big swings when we see a big opportunity. But I think that we run a very efficient shop, and because their free cash flow didn’t come from nowhere. They came from efficiencies and discipline. And so I think we take big swings and we see the opportunity, and we’re not afraid to you in the future.

David Barrett: But we also get in — I guess, it’s not our culture to spend — just to spend we need to feel good about it. It’s not like –you always use it or lose it, we better spend that they’re on to reduce our budget. That’s not part of our portfolio. So the dollars we spend, we feel good about. And if we don’t feel good about it, we pull it back as quick as we can.

Ryan Schaffer: Yes.

Matthew O’Neill: Great. Thank you both. That’s all for me.

David Barrett: Great

Unidentified Company Representative: That was everyone.

David Barrett: All right. Thank you, everyone. No questions about the Card migration first time in since IPO, so happy that we got that migration done. Thank you all for the time, and we’ll see you next quarter. Thank you very much.

Ryan Schaffer: Thanks everyone.