Title

Presentation

AppLovin Corporation beats earnings expectations. Reported EPS is $1.67, expectations were $1.44.

David Hsiao: Welcome to AppLovin’s Earnings Call for the First Quarter ended March 31, 2025. I’m David Hsiao, Head of Investor Relations. Joining me today to discuss our results are Adam Foroughi, our Co-Founder, CEO and Chairperson; and Matt Stumpf, our CFO. Please note our SEC filings to date as well as our financial update and press release discussing our first quarter performance are available at investors.applovin.com. During today’s call, we will be making forward-looking statements including, but not limited to, the future development and reach of our platform, our expected growth opportunities, the result and timing of our proposed sale of our games business, the efficiency of our operations, the expected future financial performance of the company, and other future events.

These statements are based on our current assumptions and beliefs, and we assume no obligation to update them except as required by law. Our actual results may differ materially from the results predicted. We encourage you to review the risk factors in our most recently filed Form 10-K for the year ended December 31, 2024. Additional information may also be found in our quarterly report on Form 10-Q for the fiscal quarter ended March 31, 2025, which will be filed today. We will also be discussing non-GAAP financial measures. These non-GAAP measures are not intended to be superior to or substitute for our GAAP results. Please be sure to review the GAAP results and the reconciliations of our GAAP and non-GAAP financial measures in our earnings release and financial update available on our Investor Relations site.

This conference call is being recorded and a replay will be available for a period of time on our IR website. Now, I’ll turn it over to Adam and Matt for some opening remarks, then we’ll have the moderator take us through Q&A.

Adam Foroughi: Thank you all for joining us today. Q1 2025 was another fantastic quarter, marked by resilience and robust growth. After seeing the stock price rise roughly 50 times in two years, we faced short seller scrutiny, which we’ve addressed comprehensively and won’t revisit here. Our mission remains clear, helping advertisers reach new customers profitably. It’s important to remember, in our business, our only financial incentive is to drive measurable revenue and profitability to our advertisers. Without that, we could not scale our business nor would we get paid. As a leading performance marketing platform, our technological innovations have catalyzed the return to growth in the gaming ecosystem, reviving an industry that would otherwise be struggling without our advancements over the past two years.

We’ve empowered sophisticated media buyers investing over $10 billion annually with us driving strong returns and generating significant impact for their businesses. We’re now expanding into broader categories, confident in our ability to fuel their growth as we did for gaming. Few platforms operate at our scale, and we’re proud of our role in driving economic growth. Our partners’ vocal support this quarter was inspiring, and we’re doing more business than ever. Let’s dive into our outstanding Q1 performance. The first quarter is typically challenging for advertising due to seasonality and fewer days compared to Q4, yet we achieved remarkable growth. How? We further refined our machine learning models enabling mobile gaming companies to scale their campaigns on our platform.

Less significant, but impactful was a full quarter contribution from web advertisers. This diversification is transformative and fuels our excitement for what’s ahead. Today, we’re thrilled to announce the signing of the definitive agreement to sell our games business in its entirety. This strategic move sharpens our focus on advertising. To our studio teams, you’ve been instrumental in building the technology that powers our Axon platform. As you transition to a company dedicated to game development, we’re grateful for your contributions and excited for your future. Now, looking ahead, we’re focusing all resources on three key priorities for 2025. First, we’re relentlessly improving our machine learning models. Our research science team is leveraging rapid AI advancements to deliver even greater value to our partners, ensuring our platform remains a performance leader.

Second, we’re advancing our e-commerce and web advertising solutions with three areas of focus. We’re continuously refining our models. While our product already works well for many advertisers, it’s still early days, and we believe it can be significantly better. Each iteration brings us closer to that goal. We’re enhancing integrations with third-party platforms and attribution vendors to provide advertisers with a seamless measurement experience. The web advertising space is more fragmented than apps, so this will take time, but it’s a straightforward task. We’re also developing a self-service dashboard, and we’ll be launching it this quarter for select customers. Once fully rolled out, this tool will enable seamless automation, allowing new advertisers to set objectives, budgets, upload ads, and let our system deliver results.

While we’ve seen great performance so far in our web advertising pilot, we’re currently less than 0.1% of the potential market of total advertisers. Each new partner adds to our growth. It will take a few quarters to refine these tools for a broader release, but when we launch self-service globally, we expect it to unlock a massive opportunity. Third, we’re enhancing ad testing and automated ad creation. Improving the creative experience is a priority this year, enabling advertisers to better optimize campaigns effortlessly. These initiatives are both immediate and long-term, positioning us for sustained success. Now, let me address the potential impact of tariffs. 90%-plus of our revenue in advertising comes from mobile games, which aren’t directly impacted by tariffs.

In web-based advertising, some assume we rely heavily on large Chinese e-commerce businesses, which are impacted by the de minimis tariff exemption changes. In reality, we focus on mid-market web advertisers and aren’t yet working with the largest players, as we’re refining our tools first. It is absolutely possible some of the merchants we do work with will have their businesses impacted by tariffs. However, with such low market penetration, we’re well-positioned to grow through macroeconomic changes like tariffs without any visible impact on our business trajectory. I also want to address a few topics in the news. On competition, we embrace it. It drives innovation and pushes us all to improve. With our growing data moat and AI expertise, we’re confident in our leadership and ability to grow rapidly regardless of others’ advancements.

Regarding potential alternative payment systems in the App Store, we see this as a positive. Lower fees for content developers, our customers, means they can invest more in user acquisition, which benefits our platform. For context on our TikTok bid, please see my blog post we published a few minutes ago. Our lean team continues to impress, showcasing a model for how AI-based businesses can operate efficiently. Our run rate adjusted EBITDA per employee in our Advertising business has risen to approximately $4 million annually, reflecting our commitment to operational excellence and robust economics. Thank you for your continued support as we execute our vision to build one of the world’s most influential marketing platforms. With each quarter, I grow more confident in our ability to deliver incremental value to our partners.

With that, I’ll turn it over to Matt for a deeper dive on our financials.

Matt Stumpf: Thanks, Adam. And thanks to everyone for joining us today. We’re thrilled to share that Q1 was another outstanding quarter for us, showcasing the strength and efficiency of our business model. Total revenue soared 40% from the same period last year to $1.5 billion, and adjusted EBITDA increased a remarkable 83% to an impressive $1 billion, achieving a fantastic 68% adjusted EBITDA margin. We’ve driven a 600-basis-point increase in our EBITDA margin over the previous quarter, a testament to our ability to leverage our primarily fixed cost base while fueling revenue growth through cutting-edge technology. In the first quarter, we generated $826 million in free cash flow, up a staggering 113% year-over-year. Quarter-over-quarter, our free cash flow grew 19%, representing an impressive 82% flow-through from adjusted EBITDA to free cash flow.

At the end of the first quarter, we had $551 million in cash and cash equivalents. This quarter, we repurchased and withheld a total of 3.4 million shares for a total cost of $1.2 billion, primarily funded through our free cash flow as well as a temporary draw on our revolving credit facility, which we’ve now repaid. As a result of our strategic share management activities, we were able to reduce the total outstanding shares, net of share issuances to employees, demonstrating our commitment to delivering value to shareholders, and ended the quarter with 338 million shares outstanding. Shifting to the Advertising business, we generated $1.16 billion in revenue and $943 million in adjusted EBITDA, achieving an incredible 81% margin. Our revenue growth in the quarter was driven by a combination of factors, including continued enhancements in our AI-driven technology, which has delivered even better performance for the advertisers using app discovery and the full quarter impact of our web-based advertising solution, which continues to perform strongly while coming off a seasonally high spend period for e-commerce.

Quarter-over-quarter flow-through from revenue to adjusted EBITDA was an exceptional 104%, which is slightly higher than our normal levels due to certain non-recurring costs last quarter. However, after adjusting for these costs, our flow-through was still a robust 100% despite the step-up in data center costs I mentioned last quarter, highlighting our dedication to operating lean while scaling smartly. As Adam mentioned, we’re excited to share that we’ve signed a definitive agreement with Tripledot Studios to divest our Apps business. Consideration includes $400 million in cash and a 20% ownership stake in the combined business. Subject to regulatory clearance, we anticipate closing this transaction in the second quarter, and we’re confident in the success this business will achieve under new leadership while we sharpen our focus on advertising.

Finally, turning to our financial guidance for next quarter. In light of the Apps sale and our strategic focus on the Advertising business, we will only provide guidance for our Advertising segment. In the second quarter of 2025, for the Advertising business, we anticipate delivering between $1.195 billion and $1.215 billion in revenue, with adjusted EBITDA between $970 million and $990 million, targeting an adjusted EBITDA margin of 81%. We’re confident these targets position us to continue driving strong growth and value for our partners and shareholders. Now, with that, let’s move to Q&A.

Operator: We will now begin the question-and-answer session. [Operator Instructions] First up is Jason Bazinet at Citi.

Jason Bazinet: Good afternoon, guys. How are you?

Adam Foroughi: Good. How are you, Jason?

Matt Stumpf: Hey, Jason.

Jason Bazinet: So, I just had one quick question, maybe two parts. On the guidance for next quarter, I think it implies something, maybe I’m doing the math wrong, 3% to 5% sequential growth, which seems a little bit slower than I think your aspiration just on the mobile-only part of the business. But maybe I’m misinterpreting something or maybe something else is going on. That’s the first part of my question. And then, the second one is, I was just looking back towards your historic financials, and there have been some quarters where there were, like, sequential declines in ads revenue, but it ended up not being indicative at all of how much you are going to grow. And so, do you think investors should sort of brace for maybe somewhere down the future, there could be a sequential decline in ads revenue, but it doesn’t — it’s not really thesis changing? I guess, that’s my question. I think it was 2022 was the year. Those are my two questions.

Adam Foroughi: Yeah. So, I can answer the second part, and Matt can jump in if he wants to on guidance. But, Jason, 2022 was a lot different. It was pre-Axon model. And since we’ve released it, we’ve obviously seen an immense amount of growth. This thing continues to get better as it scales. And you get a really strong flywheel embedded into this type of a machine learning mall. As we get more impressions, more engagements with the ads, more conversions, the thing just get continues to get smarter and smarter. And then, you pair that self-learning with the technological gains that our team continues to layer on top, and the growth of the business has obviously been phenomenal since. So, I wouldn’t look back at ’22 and before.

Then, to your first question, the other thing you got in our business is in terms of seasonality, we have a bit of a unique advertising business because you typically expect Q1 to be a worst season. And our seasons are tied to time spent on mobile device, and Q1 gets the benefit of a whole bunch of holiday days at the beginning of the quarter, and then you’ve got other things like Ramadan, and spring break that take effect in Q1. Q2, you actually don’t have almost anything as only the tail end gets into summer. Q3, you get summer. Q4, you get the holidays. So, if you look last year at our quarter-over-quarter sequential growth, the only single-digit quarter was Q2. Now, we’ve said we’re looking to grow 20% to 30%, but there’s a whole bunch of unpredictable reasons why every year we think the growth could actually be materially higher.

We almost grew 20% quarter-over-quarter in a single quarter in Q1 over Q4 if you normalize by day. So, the business is growing really quickly. We continue to see a lot of excitement from advertisers on the platform. They’re spending more than they’ve ever spent before on the platform both across games and the web advertising initiative. And then, even more exciting, I touched on this in the talk script, we’re finally going to be releasing our new dashboard to some select advertisers for feedback this quarter. That’s a huge catalyzing effect. When we do go to a full self-service state, we’re going to open up our platform from a very small amount of advertiser penetration to the entirety of the world being able to come on to our platform. Now, there’s a lot to do between here and there, but once we do that, again, we’ll go through another one of those transformational moments where the business will just change a lot.

So, the past in our business isn’t really indicative of the future growth trends because we just haven’t been at a stable place yet.

Jason Bazinet: Okay. Thank you.

Operator: Next up is Matthew Cost at Morgan Stanley.

Matthew Cost: Hey, everybody. Thanks for taking the questions. Maybe I’ll start off just talking about category exposure. I think last quarter, you highlighted a couple of new categories, including fintech and healthcare and insurance that you’re having success moving into. So, I guess, are you continuing to push into new categories beyond the ones that you’ve talked about? And then, when you’re having those conversations with new types of advertisers, what are the pain points that they’re looking to have solved? Is it about onboarding those attribution partners? Is it about self-serve? And then, I have one follow-up. Thank you.

Adam Foroughi: Yeah. So, I would say, Matt, we’re not looking to push into any category of web advertising right now. We’ve got a line out the door of customers that have been waiting to come on to the platform, and then we’ve onboarded, I think I said, in a blog, hundreds of advertisers, but our team is small. So, when I say we’re not looking to push, we’re looking to push over time, but we need to get the self-service tools into the market so that we can pair that with the team to automate a lot more of the processes. What we’re excited about today is the model is still in infancy when it comes to web advertising. We think it can get a lot better. And then, you layer on those attribution integrations and platform integrations and make the integration with advertisers more seamless.

Both those two things, the automated tools, better integrations, paired with a much better model, which our model is inevitably going to get better as the engineering team has more time to evolve it, we think we’re going to get to a place in web advertising where we are in games. Today, if you’re a game advertiser, we’re the best destination in the world to spend money. Every type of game, regardless of whether it launches today or launched years ago in any category, plugs into our system, puts in a return on ad spend goal and scales at their goals. We’re not there yet on web across categories, but we’re seeing better performance than we expected this early. We’re going to get there. And when we get there and we pair that with the self-service dashboard and launch that product globally, you’re going to have an effect that catalyzes a ton of long-term growth.

Matthew Cost: Great. Thank you. And then, I think, you mentioned in the prepared remarks something about automated ad creation. So, is that essentially tailored creative? And if so, what is the cost benefit analysis given the cost of generating creative for advertisers in real time?

Adam Foroughi: Yeah. I mean, to answer the second part first, we don’t know the cost benefit until we do it. But what we want to do is generative AI-based ad creative. And if you think about the platform today, we serve over 1 billion daily active users. We’re serving a lot of impressions. But if you take a single advertiser, say, Activision with Candy Crush, they upload 20 static videos, let’s say, for their campaign. And that’s what their team can go create to run on our platform. And those videos go and serve, and they drive a certain response rate. Well, in the world of large language models and customization, we’re not going to get to the extreme where every single end user can see a differentiated video, but we can certainly get to a place where you can take the best videos that an advertiser uploads, run them through a large language model, get an output of more videos that are dynamically generated, run those videos through our platform, let the model then personalize the ad to the end user at a greater level.

When you’re able to test ad creative, it’s one of the biggest levers that advertisers have to move the needle on growth, on response rate. It’s free effectively. It’s a very low cost amount of production to get a much higher response rate on advertising. If we can systematically do it, and we’re certain we can, it’s just taking time to get this to market, we’re going to be able to extract a lot higher response rate from the audience that sees the advertisements. And again, every time we have one of those events, it creates both a short-term step-up in growth, and then that compounds over time, because the system then starts getting more transactions through it, it learns better, and it continues to build on itself. So, that’s another one of those events that we think are going to be very impactful and it’s something that’s a priority for us to work on across the rest of the year.

Matthew Cost: Great. Thank you both.

Operator: Next up is Omar Dessouky at Bank of America.

Omar Dessouky: Hi. Thanks for taking the question. Now that you’ve been in the pilot — excuse me, that e-commerce has scaled for a couple of quarters, I was wondering whether you had any updated points of view on churn, among your advertisers, whether you’re seeing any churn, and what would your go-forward assumptions on churn be? That’s one. And then, whether you’re seeing the spend per advertiser increase as the months go by or they may — or if that spend per advertiser is just affected by seasonal trends?

Adam Foroughi: Yeah. So, we disclosed to you, Omar, I think I said 600-some-odd advertisers in the blog, $1 billion run rate. In terms of churn and web spend growth quarter-over-quarter, a comp against Q4 versus Q1 isn’t particularly fair in shopping, so I’m not going to disclose growth by advertiser. But when we think about churn with where we are in the advertising product for web, we’re early. So inevitably, we’re going to have some customers where it doesn’t work for. Now, actually, right before this call, we pulled the number. For advertisers that spent run rate $250,000 a year, we had sub 3% churn. So, very little. Now, that’s not an acceptable number for us. In gaming, we have basically no churn. Unless a game is not marketable and it’s going to go out of business, companies in gaming do not drop off our platform.

We’re basically a requirement to their success. We want to be that in web advertising as well, but again, remember this product is months old. As the model gets better, we think we’re going to be a destination for any type of advertiser that has a website or an app or both to come market themselves and have success where we become a required marketing destination for them and their business.

Omar Dessouky: Okay. And if I could just ask a quick follow-up on a different topic? You disclosed 49%, year-on-year growth in net revenue per install. However, your e-commerce advertisers don’t drive installs, they drive actions. So, is that metric inclusive of the actions that are driven by e-commerce?

Matt Stumpf: No, it’s not, Omar. So, it’s inclusive of the revenue associated with those web-based advertisers, but that’s driving then an increase in the net revenue per install because the installation volume in that metric is staying stagnant, right? It’s only based on the CPI-based advertisers.

Omar Dessouky: Thank you very much.

Matt Stumpf: You’re welcome.

Operator: Next up is Chris Kuntarich at UBS.

Chris Kuntarich: Thanks for taking my question. Adam, you mentioned that advertising could be better for some of the advertisers on the web-based experience. Curious if there’s kind of a common thread that you would identify across those advertisers that we should be thinking about and some of the progress you could be making as we look forward into 2Q and later this year for just kind of road signs of progress for those advertisers.

Adam Foroughi: Yeah. I wouldn’t say it’s trends or anything specific because it’s just not the way the models work. But if you think back a couple of years ago on the game advertising call, pre-Axon 2 and what happened when we released the new version of the technology and what’s built, the customers get better ROAS and more scale. Every time the model becomes more predictive, that’s what happens. So, I sort of rate us as, like, a B+ right now with where we are. For how little time we’ve had a market with the web-based model, it’s performing really well, but we think it could perform a lot better. Now, games have grown a ton over the last couple years. I don’t know exact number, but I think I put in the blog. Ad spend on the platform has roughly quadrupled since we rolled out Axon 2.

Now, that happens because you have better ROAS and better scale because the model evolves and gets better. So, if we get to a place where tomorrow, one of our engineers release a new version of the web model that’s 30%, 40% better, I wouldn’t be surprised. That doesn’t mean that ROAS is 30%, 40% better because usually we achieve an advertiser’s ROAS goals, but it means at the comparable ROAS, they get 30%, 40% more scale. Then that starts compounding, but that ends up universal on the platform.

Chris Kuntarich: Got it. And maybe just one follow-up. As we talk to advertisers, one of the common feedbacks we hear is the desire to have exclusionary audiences. Curious kind of if you’re thinking around offering that to your advertisers, specifically on the web-based side, has evolved since we’ve last spoke.

Adam Foroughi: Yeah. So, this is an interesting offering because it’s related to how they’re used to buying on Meta’s properties. And across Meta, this is just common. Advertisers upload an exclusion list and say, I want to target new audiences at this percentage of dollars spent versus retargeting. The way we look at our product again is it’s early. So, our best gauge of success is how we can scale at the ROAS that they want, not by divvying up audiences, but by just making the model better at matching. Now, over time, we may introduce things like exclusionary targeting, and we played around with some of it over the last few months as well, but it’s not a focus for us because we’re still too early in the product. If our product’s performance continues to improve — we ramped up on hundreds of advertisers to $1 billion run rate.

And I mentioned we’re sub-0.1% penetration in the market. So, despite being really early and despite having some bumps with some advertisers where we can look across the advertiser base and know, we’re not making it work for everyone. If we just open up the platform today, you’re going to see a ton of growth and we’re going to be working for a lot of advertisers. Now, we want to make it work for every single one, but we don’t judge ourselves by saying we want to build products that are similar to what others do. We want to build products that are improved to what others do for our advertisers. And so, we take these points of feedback, we think about them, but we’re focused on our own path, which is improve the model and give the advertiser what we think is the best outcome.

Chris Kuntarich: Very helpful. Thank you.

Operator: Next up is James Heaney at Jefferies.

James Heaney: Great. Thank you, guys. Just it’d be great to get an update on the velocity of new web advertiser additions in the quarter. Just interested to hear how the pace has changed since you last reported 600 customers in December. And anything around how to think about that going into Q2 and second half of the year? And then, I had a follow-up.

Adam Foroughi: Yeah. So, pace has slowed down because we just don’t have the resources. So, team is still about 20 people. So, if you think about, like, what a team consists of, there’s sales engineering, integration people, BD analysts at sales. So, there’s not a lot of people in any one of those groups across this team. The objective right now is to give them the self-service dashboard, the automated tooling, so then they could start onboarding at the pace that they were able to do to get up to the 600-and-change. And I’m sure we’re above that at this point, but the reality is we don’t have the manual resources to onboard the line out the door, but we’re there now with the dashboard that can really help the team. We’re going to be in testing with it.

We’ll get early feedback. It looks quite good to us. And we believe it’ll be quite good for the advertisers. Once we get that in the hands of advertisers where they can manually automate however they work with us, then the team is going to be able to onboard a lot more quickly. And so, you’ll start seeing phases of how we roll this out. You’ll hear about it on Twitter, I’m sure, with people playing around with the new dash and then us getting it into the hands of the advertiser base this quarter. And then, in the coming quarters, we’ll start opening it up more and more, and that’ll really help onboarding of advertisers to the point where, eventually, we will completely open it up, go global with the product, and then start really onboarding at a quick rate.

James Heaney: And then, just as another question, we’ve heard from a lot of your e-comm advertisers that the web product works really well for advertisers that optimize for those 24-hour conversion windows. I’d love to hear about any progress you’re making with helping advertisers that have longer consideration windows and higher repeat purchases.

Adam Foroughi: Well, look, we don’t have a conversion API. We don’t have what other companies have with e-mail address and phone number. So, we can’t attribute back anything outside of a cookie window. And the cookie window in this day and age, especially on Safari, is a very short window. What that means is that our model has to drive actions quickly. That’s great for most advertisers. Most advertisers aren’t selling a $20,000 product, but if you’re selling a $20,000 product, you’re probably not going to sell it in the matter of a few hours. So, on the one hand, because of our limited view on attribution, the model has to be really good at going ad to transaction in a very short window. If you can do that for a $200 shirt, that’s a great outcome, because the advertiser knows ad created actual intent and outcome.

If that sale had happened two weeks later, it’d be very hard for the advertiser to say, I can justify the whole value of that sale back to the AppLovin channel because there’s been a whole other — a bunch of other things that have happened in the middle there. What that does force us to do though is have a challenge when it comes to an advertiser that’s selling a much more expensive product. We probably have to go and optimize for that advertiser to something earlier in funnel, maybe a phone call, maybe an e-mail registration, but not all the way to the point of transaction if those transactions are basically impossible to drive in a matter of a few hours. Again, I remind you we have hundreds of advertisers into this thing. So, the world of advertisers here is so big.

Most sell products pretty quickly. So, this honestly isn’t something that we’re even thinking about right now because we have a lot of room to go get advertisers and grow this business before we get to the constraint of, okay, now we have to make the product sell that are in the thousands or tens of thousands of dollars per product.

James Heaney: That’s great. Thank you.

Adam Foroughi: Yeah.

Operator: Next up is Ralph Schackart at William Blair.

Ralph Schackart: Good afternoon. Thanks for taking the question, Adam and Matt. Just a question on self-service model. When you go live with that, obviously, you’re testing right now, how do you expect the platform to sort of respond? Or maybe better question is the advertisers, do you expect them to come with substantial budgets that you describe a line out the door? Do you think it’d be more like a dimmer switch where they would test and then add more budgets? Just trying to understand your best thoughts on what happens when you go live there.

Adam Foroughi: Yeah. Look, advertisers need to prove to themselves that the dollars are worth spending. So, no one just comes and floods a new system. They usually build up budget over the weeks and months that they’re live once they see that a campaign is actually achieving the goals that they have. Now, remember, we’ve constrained the audience in web advertising to US-only. That’s by design. Our business itself is probably, I want to say off top of my head, half-half US versus international. We don’t operate inside China. So, there’s a lot of opportunity to just flip that switch and go global. Now, we’ll pair the self-service dashboard with that. That’ll allow us to really quickly, dramatically increase the audience that sees these kinds of ads and pair it with the types of advertisers and count of advertisers that are onboarding into the system.

Then, it’s up to them to find their own way. The good news is we’re the last big advertising company that has a self-service dashboard. All the other ones, the social company, search, any display channel that’s of any sort of scale has this type of ads manager product. Once we release it, agencies and advertisers will know what to do.

Ralph Schackart: Great. Maybe a question for Matt. Matt, I think, historically you’ve talked about the growth algorithm being around 20% or 30%. Obviously, the business is growing very robustly. Is that still the right sort of framing for the model? Just kind of curious on your thoughts there.

Matt Stumpf: Yeah. I mean, we continue to believe that 20% to 30% is the right long-term growth rate for the company. As we’ve talked about before, that’s comprised of two components. One is the ongoing reinforcement learning, right, from the model just transacting and then teaching itself and improving over time. And that component we think is about kind of 3% to 5%, which is how we’re guiding on a quarterly basis. That’s the component that we know is very stable, very predictable. And so that’s what we’ve included within our guidance. Above and beyond that are directed enhancements, right, models going from ChatGPT 3 to 4. Our engineering team are working on all the time. And when they launch a new model, those provide step function increases.

And so, those increase the annual growth rate in addition roughly around 10% is what we’ve kind of seen thus far. But we’ve had a lot of those quarters luckily where the engineers have launched those model enhancements and we’ve seen those step function increases. So, we think that we should be able to do at least one of those step function increases per year going forward. And it’s a relatively conservative assumption from our perspective given where we’ve performed thus far over the past couple years since launching.

Ralph Schackart: Okay. Great. Thanks, Adam. Thanks, Matt.

Operator: Next up is Rob Sanderson at Loop Capital.

Matt Stumpf: Robbie, you’re muted.

Operator: Next up is Matthew Thornton at FBN Securities.

Matthew Thornton: Hey, Adam, Matt, David. Hope everyone’s well. Good to see you guys. Maybe two if I could. I guess, first one, maybe for Adam. If we think about some of the next layer of initiatives, and what I’m getting at there is really the non-gaming app-to-app user acquisition as well as the dynamic personalized ad creative that you alluded to earlier, should we think of those as initiatives that could actually start to contribute in 2025, or should we think of those as more of 2026 type of initiatives? And then, just one quick housekeeping follow-up, Matt. I think you guys have talked about the non-gaming audience plus business maybe being 10%-plus of total advertising revenue this year. Is that still how you’re thinking about that business for 2025?

Adam Foroughi: Yeah. On the question on the new stuff that we’re really prioritizing, I don’t know if it’s new, just expansion of what we’re working on. I said in the talk script that focus is for this year to execute on that list. If we do that well, we’re set up to have a fantastic 2026. We’re already on the way to have a fantastic 2025. I don’t know of any other tech company with the financial profile that we have and scale growing the way we are. I think it’s on a rule of 150 or something. And what we’re focused on when we talk about priorities is how’s 2026 going to be? How’s ’27 going to be? If we execute on self-service dashboard, put it out in the market, automate media buying on our platform, make it simple for advertisers of any kind, let them come in, put in their goals, off they go, the business is going to have many quarters and years ahead of it of immense growth.

At some point, we’re going to become a marketing-based business. We can run AppLovin ads for any sort of small business to come in and buy on us, and you’ll have an LTV to CAC model because the value of every one of those advertisers given where we’re starting an advertiser penetration to the millions that we can go after would be immense. And then, pair that with dynamic ad creative continued model improvement, the self-learning in the system, and we’ve got a lot of vectors of growth that we’re really excited about for the rest of the year and then beyond.

Matt Stumpf: And in terms of web-based advertising contribution, Matt, and we had mentioned previously, right, that we thought that they would become kind of 10% of the overall contribution in revenue. It’s very difficult to guess where that might go within the year because we’ve got a lot of factors, right, on both the existing mobile gaming business, how that develops over time based on these model enhancements that we’re launching. To the extent that we launched significant model enhancements, that business could grow at a faster pace than e-commerce, but we’re very optimistic about the e-commerce business. After we launched the self-serve model, that business could grow quite significantly and outpace that 10% metric that we provided previously. So, it’s quite likely that it could represent a larger than 10% portion of the revenue this year.

Matthew Thornton: Great. Appreciate it. Thanks, guys.

Unidentified Analyst: Hello. Good afternoon. Matt, to follow-up on what you said a couple of questions ago, I think last year, we had two quarters where there was I think the term is human-directed enhancements, right? So, I think it was Q1 and Q3. And, do I understand correctly that you’re saying that, that can happen even, like, three, four, five years into Axon 2? It’s not a function of the life stage of the machine as the — it’s a function of its — constantly learning? And then, a related question. So, help us understand, or at least me, is it the same learning that’s applied to gaming and e-commerce, or are those two different processes that can happen, let’s say, in one quarter, like, e-commerce learned something and stepped up and gaming did not?

Matt Stumpf: Yeah, those are great questions. I’ll address the second one first. So, they’re two different — two separate models. So, both models are learning at the same time. So, you’ve got reinforcement learning occurring to both models, and then you also have directed enhancements that the team could launch on either model. Obviously, we’ve got teams — we have a team that’s working on both models at the same time, similar to what Adam mentioned about our business development team. We run lean, and so we have a very small team that’s working across both. But they’re constantly testing potential changes to the model that we could launch on either to provide these step function increases at any point in time. And there’s a laundry list of these things that they’re testing at any given point in time to assess whether or not they could potentially have an impact.

And then, we launch those model enhancements. So, you could have the mobile gaming — the existing mobile gaming model improve in one quarter, and the e-commerce model only have reinforcement learning and that more kind of stable growth, plus adding new advertisers there, which is obviously going to increase at a faster pace than the mobile gaming side of the business where we basically have all mobile gaming advertisers at this point. So, those two things are moving independently.

Adam Foroughi: Yeah. [Vasily] (ph), I would add a couple of things too is, let’s not forget these this form of understanding how to work with neural nets is really new. I mean, you’ve seen it, like, we all can play with it with ChatGPT. If you look at how quickly they’re releasing models, there’s a lot of research in the space that is guiding engineers across companies that have gotten very good with models to build new versions of the models. And as you build new versions of the models, you train them on the data. If they’re more predictive, they’ll be improved. The beauty of our business model is that one, we’re cutting-edge. We’re on a lot of the latest research. We built an exceptional implementation of this kind of technology.

We might be one of the best examples of how software can unlock value from this kind of AI movement. But the reality is it’s really, really early. So, there’s plenty of research out there that our team still needs to parse through. There’s internal research that we pair with that. And this is never ending. I don’t see any end in sight for us as human beings to be working on these types of AI technologies. The opportunity is just too great. And so, we probably shouldn’t call Axon 2. Maybe it’s just the Axon model. There’s going to be many different iterations of this thing that we go through in the coming quarters and years. And every single time when we have a lift, something that’s material, where we can step it up where you would say like Axon 3 — not Axon 3, Axon 2.2, Axon 2.3, Axon 2.4, those incremental changes have shown to be double-digit growth in a single quarter, quarter-over-quarter.

And we have a less incremental lift, but a nominal enhancement where the team is still working on improving the model, but it doesn’t step up as much, it’s still very impactful to our business at the scale that we operate at. So, we have a long pipeline of things to work on, and we expect that the research science team till the end of time is going to be constantly improving this model.

Unidentified Analyst: So, very quick follow-up. So, in simple terms, what Matt was saying that these are two different models, right? So, is it possible that you have Axon 2 running, and then there is a ’22 level of event that happens with the e-commerce model, right, and it steps up in efficiency, and they will be not synchronized, but improving at a step function at different? Is that what you’re saying?

Adam Foroughi: Yeah. It’s — the reason why I keep saying e-comm model is early is exactly that. It’s like when we launched Axon 2 for gaming, we’re multiple iterations in now. So, the teams had a lot more time to evolve the gaming model. The e-commerce model is a couple of quarters live now. It’s not — it hasn’t been around for that long. It also doesn’t have as much of a data feedback loop because it doesn’t have as much impressions, transactions, scale to then retrain itself off of as well. So, you have two very strong levers there that are coming.

Unidentified Analyst: Okay. Thank you very much.

Adam Foroughi: Thanks, Vasily.

Operator: Next up is Clark Lampen at BTIG.

Clark Lampen: Hey, guys. Good evening. Thanks for taking the question. Adam, as we are sifting through sort of Q1 performance for the Advertising segment within the sort of 20%-ish sequential growth that you referenced, I’m curious if that sort of as Matt put it before, did that include some benefit from step function rather than sort of reinforcement learning-type improvements, i.e., sequential growth for gaming was probably ahead of the typical low- to mid-single-digits rate of growth?

Adam Foroughi: Yeah, for sure. So, look, you have two less days. Q1, even though it’s a good season with some of those holiday days, it’s not compared to Q4, a good season. So, it was a huge step-up quarter. I mean, again, we might be the fastest-growing tech company anywhere at the scale that we operate at. So, there had to be multiple drivers there. And I mentioned on the talk script that there was better efficiency in the model. So, the team is constantly improving the model. Now, we don’t call it, like, what would self-directed lift or a model change. This wasn’t a material change to the model, but the team found wins in the model and it became more effective. Self-learning is an aspect of it. And I did say the advertiser contribution from e-comm getting a full quarter of the run rate that it had gotten to in Q4 was also impactful.

And I think I said it was less impactful than the gaming side. So with that, you can infer the greater than 50% of the quarter’s growth came from the gaming side. There’s still a lot of room to go there. I mean, these advertisers, when we become the channel that they depend on, both the advertisers and the publishers need us to do our job. We’re doing it very effectively, but we’re still at a very low conversion rate per thousand impressions to where we think we can get to even in the gaming category. And so, the technology is still early. We’re going to find more lifts. The team has got a long pipeline. So, we’re really excited about both opportunity for the model to keep getting better in that flywheel effect because the scale has gotten so big, paired with what the team is going to be able to unlock as they make the model better.

Clark Lampen: Okay. That makes a lot of sense, and it’s helpful color. Maybe for a second question, just a quick housekeeping one. Does — maybe this is for Matt. Does the guidance for the second quarter include any of the upside or recognition from legacy studio spend? I believe way back when you guys disclosed a sort of total software transaction value metric, and for accounting purposes, you weren’t recording revenue from first-party studios. Now that they’re third-party, I would imagine that there probably will be some transition so long as they’re still active. Is that in the numbers, or is it material at this point?

Matt Stumpf: Yeah. So, after signing the agreement today with Tripledot to divest the Apps business, our expectation is that the transaction is going to close towards the end of the quarter, actually, Clark. So, within the guidance, we have not assumed any incremental uplift from having those studios be external parties and the premium rate on the user acquisition cost that we would normally charge. That being said, it’ll obviously depend on how Tripledot runs those businesses as to whether or not they will continue to spend at the same level. And it’s not a material impact on the business one way or the other. It’s a nice premium to have, but we don’t expect that it’ll move the needle.

Clark Lampen: Thank you, guys.

Matt Stumpf: Yeah.

Operator: Next up, we have Alec Brondolo at Wells Fargo.

Alec Brondolo: Hey. Thanks so much. Adam, if you can maybe elaborate on the App Store regulatory news, some of the fee relief that mobile games might enjoy as we move through the year? I guess, one, how do you think about the potential impact on the business from an ad spend perspective? And then, two, how do you think about positioning the business to maybe assist in that transition, position yourself best to win some of that incremental spend to the extent that it materializes? Thanks.

Adam Foroughi: Yeah. So, look, we’re the largest channel there is today for mobile gaming customers to spend their money, and I think we’re the best destination for it. So, maybe we’re likely to be the biggest beneficiary of this change. And just as simple terms, if you’d assume it’s — the fee isn’t going to go to zero. So let’s just, for my example, assume you go to half, 15% fee, you take $1 that the customer was charging — the mobile game developer was charging a consumer. Before, they were getting $0.70, and then they would plug that into a ROAS model with us to go spend dollars. If that’s $0.70 in a $0.15 fee structure becomes $0.85, they make 20% more. It’s immediate 20% uplift to their revenues. That 20% in some portion or in total is going to come back to a marketing platform that’s as scaled as ours.

And remember, we run a dynamic auction. So, if one customer says, “Hey, I want to bid 20% more, because I bank 20% more. I like the profit margins I run at. I want to get more growth,” then every other customer has to do the same thing because it’s competitive auction. So, over time, what’s going to happen is it’s really good for the ecosystem. It will create more growth and it’s exceptionally good for the advertising businesses because the dollars will come into the marketplace and allow the advertisers to bid more competitively, which benefits us, and that feeds back to the publisher. It also feeds back, obviously, to our bottom line and benefits our shareholders.

Alec Brondolo: Perfect. Thanks so much.

Adam Foroughi: Thank you.

Operator: Next up, we have a Jim Callahan at Piper Sandler.

Jim Callahan: Hi. Thanks for taking the question. Big investor question we get is just your ability to sort of monetize a relatively, like, static base of inventory. Now that we’re a couple quarters into sort of launching e-comm, would be curious your sort of thought or if that’s changed at all.

Adam Foroughi: Well, look, we have a very large scale static base of inventory. I’d say if you look at Meta’s business or YouTube, these are static bases of inventory. It’s not like there’s new users pouring in, especially in the States. But what’s happening across the companies that are doing well in performance advertising is the matching and the technology algorithm is getting stronger. We’re starting at a very, very low place. I think in the past, we’ve said, look, we’re driving a 1% transaction right now. We’ve grown a lot, so that’s probably gone up a little bit. Doesn’t have to go up a lot for our business to expand dramatically. We think that can go up to become 2%, 3%, 4%, 5% over time. The ads are very, very impactful.

It’s full-screen video. It captures the user’s attention. And the more advertiser demand we get as we open up our self-service platform and hopefully bring on thousands, tens of thousands, eventually hundreds of thousands of millions of customers, we’re going to have more content to show the end consumer. We’re going to pair that with personalized ad creative. The consumer response is going to go up. That’s going to help us. It’s going to help our publishers. It’s going to help our partners, and we think it’s going to catalyze potentially years and decade plus of growth.

Jim Callahan: Got it. That is helpful. And then just quick one on gaming macro. Obviously, not really seeing any signs of weakness in the results, but anything to call out with regards to, like, the studio launches or geographies that are worth noting?

Adam Foroughi: I mean, our business is really diverse at this point. One game was never going to move the needle at the scale that we operate at. So, there are — I guess, there have been some bigger launches or marketing in the ecosystem around a couple games, but nothing dissimilar to the past history of the pace of game launches. I don’t think the tariffs impact the digital economy here. And in terms of the economy and slowdowns, free-to-play gaming is a very cheap and accessible form of entertainment. So, we’ve always felt that it’s quite insulated from economic change or distress. And so, we’re confident with the position we have in the market.

Jim Callahan: Great. Thank you.

Operator: Next up is Martin Yang at Opp Co.

Martin Yang: Hi. Good afternoon. Thank you for taking my question. A couple question on the self-serve dashboard. First, has your view changed on who can have access first to the self-serve dashboard? Is it your existing customers primarily, or are you applying this to anyone regardless of their annual spend budget?

Adam Foroughi: Yeah. We’re going to roll it out in stages, Martin. So, right now, it’s current customers. We’ll have a feedback group. Once it gets past feedback group, it’ll open up to all current customers. The goal with that is to just help our team. The team right now is do a bunch of manual labor, and we’re capped, we’re resource limited. So that’s going to happen pretty quickly here over the coming weeks. I mean, I mentioned in my talk script. We’re getting this in the hands of clients now. So that’s going to be short-term. In the medium- to long-term, we’ll go through stages of opening it up, where eventually long-term, and this isn’t too long-term, but several quarters, we’ll go completely open. But in between now and there, you’ll have stages of opening it up to new types of clients so that we ensure the quality of client is high. The platform can be bug-free. It can work under all scenarios. The models have time to improve. We open it up, and off we go.

Martin Yang: Got it. And a follow-up on that is when you think about this potential to give you more data or maybe increase your capacity to process more, do you think near-term, this is — could be a near — helpful near-term boost to how you improve the performance of [web/app business] (ph)?

Adam Foroughi: Look, the more customers we get, the better the model will get. Just if you think about it just logically, if you’ve got 10 beauty companies live or you have a thousand beauty companies live, you’re going to be better in a category if you have a thousand live than 10 because you have more diversity of product to show the end consumer. This type of a product is a recommendation engine. Give it more options to recommend something personalized and it’s going to, by effect, get better. Now, I’ve said this in the past, we’re at a point where we’re not perfect, we’re not making it work for every customer. Whereas we do that inside gaming. So, we don’t want to go to a thousand beauty companies and say, “Look, 800 of you are going to work perfectly well.

200 of you are not going to work.” Our shareholders will be ecstatic. If we open up the platform and become thousands to tens of thousands to hundreds of thousands of customers, the business is going to be multiples bigger than it is today. The growth rate is going to be phenomenal. The problem is we want to make it work for everyone. We really set a high bar of perfection in anything that we do. We want to build the best performance product that these customers have ever seen. And so, we’re not there yet. We’re going to get there. When we get there, we’ll open it up, and that’s going to catalyze a lot of growth for the long-term.

Martin Yang: Got it. Thank you.

Operator: Next up, we have Eric Sheridan at Goldman Sachs.

Eric Sheridan: Thanks so much for taking the questions. Maybe two if I could. Adam, first for you, I got a chance to look at the blog post about TikTok, and I totally get your labeling and it’s a bit of a long shot to use your phraseology from the end of the blog. But my understanding was you were more interested in the US ring-fenced process that’s going on under the Trump administration now, and this seems like it’s a bit of a broader proposal, ex China globally as opposed to maybe what the Trump administration is trying to [solve for] (ph). So, I just want to make sure I understand a little bit of the messaging off the blog and how to reconcile it with what is going on in DC right now with respect to TikTok US and how you’re positioning yourself vis a vis that.

And then, Matt, you guys continue to produce a lot of efficiencies while growing at very high rates. Any updated views on how you guys are thinking about incremental margins in the business over the medium- to long-term, or steady-state rate on incremental margins? Thanks, guys.

Adam Foroughi: Yeah. Thanks, Eric. I don’t want to spend too much time on TikTok, but just briefly, yes, we’re going after world outside of China. We think the biggest priority is to solve national security concerns with regards to biases in the algo and data in the US, but that’s important outside of China everywhere. And to do that, you really truly do have to have operational control. Unless the US app is a separate app from the rest of the world, which it cannot be, would just deflate the app’s productivity, then some company needs to have control to rewrite parts of the algo and to ensure that this thing complies with the standards around national security. We think our proposal is best suited to do that. In fact, we think we may be the only one who could do that with the knowledge that we have of models and the proposal we put forth.

And on top of that, we think we would solve the present and be the best operator of this business long term through this type of partnership structure we propose. So, I put the thoughts out there. I wanted people to have context. It’s absolutely a long shot. We do go after long shots. That shouldn’t be surprising to our shareholders at this point. We think we’ve got the best performance advertising AI model the world has ever seen today, and that paired with an audience as large scale as TikToks could unlock immense economic potential and value for shareholders. So, it’s something that we’re excited about, and I put the rest of the details in the blog for others to read.

Matt Stumpf: And in terms of your second question, Eric, further the margin profile of the business and expectations going forward, I mean, as Adam mentioned, we continue to expect to run the business lean and it’s part of the ethos of the company. So, as we continue to grow top-line, we’re trying to find ways to do that in an efficient manner. Obviously, we’ve been talking about the self-serve platform. That’s one obvious way that we’re planning to grow by not adding any to the cost base. So, we do expect that the primary components of the cost base should remain relatively flat with obviously the exception of data center costs, which are more variable. What we’ve seen thus far as we grow revenue is that we’ve been adding on data center costs on an annual basis at least around kind of a 10% of the overall revenue growth, and we expect that that should continue.

So, the margin profile of the business should continue to grow from where we’re at today on the advertising business, up to that kind of asymptote, and then we’ll see where we can take it from there.

Operator: The final question is from Rob Sanderson at Loop Capital.

Rob Sanderson: Thank you. Can you hear me this time?

Matt Stumpf: We can, Rob. Yeah.

Adam Foroughi: Yeah.

Rob Sanderson: Okay. Sorry. Apologies for the technical difficulties.

Matt Stumpf: No worries. Good to hear you.

Rob Sanderson: Obviously, I’m not being on camera because that’s where I failed last time. So, we’re going to play it safe. I have two questions, please. Can you — first, can you help us understand maybe and delineate to the extent that you can sort of trends in the app product versus web? And the lines are obviously are really blurring here. And, Matt, when you talk about potential for 10% contribution from web this year, like, you’re talking gross or net, or how do you even parse out the difference as — there’s — you’re obviously serving a lot of ads on inventory you’d be buying otherwise? And I’ve got a follow-up as well.

Adam Foroughi: Yeah. Rob, I’ll go with the first. Matt can go with the second. Look, over time, this is just content marketed through our platform using our models to drive a result. So, whether the advertiser is an app, a website, a web and an app, the model should be able to deliver the result. Now, we started with mobile gaming advertisers who had apps. And so the first version of our business for 12 years was focused on one specific use case. Now, we built into the web use case. Now, we’re also building into the web and app use case. But over time, the way we envision our product is that advertisers come in, they say, here’s where I want the user to go. Here’s my app. Here’s my website. Here’s the return on ad spend target that I want or the cost per purchaser that I want.

Here’s my budget. Upload a few videos. AppLovin, go take care of the rest. Deliver result, create your own videos, personalize the advertising, and then I’m really happy. And so, we think all of this stuff is going to merge together as we get to a place quarters or years from here.

Matt Stumpf: And to clarify on the 10% contribution, Rob, so that would be on a net basis. So, we believe that the web-based advertising solution should contribute at least 10% to the overall net revenue of the advertising solution.

Rob Sanderson: Okay. Thanks for that. And then, question on sort of longer-term avenues for self-attribution. It’s sort of little bit of a hole right now for you, just not having the identity and whatnot. But, you know, are you always going to be sort of dependent on third parties for this? Or are you limited to this maybe lower consideration, high turnover products like you described earlier, Adam? Or is it sort of you just got lots of demand to serve right now and years of growth in front of you, and you’ll sort through that challenge over time. Like, what can you share on that at this point?

Adam Foroughi: Yeah. So, like, the third is true. We’ve got lots of demand and opportunity in front of us. The products that we can service is — on app are attributing with third-party companies like AppsFlyer and Adjust. So, we were built for third party attribution on app. On web, we built the product to be self-attributing, so our own attribution platform. And it’s not high turnover products. I mean, like, most products in the world are not selling something greater than $250. Our product — our models can go deliver something that’s a couple hundred dollars within a few minutes of the ad being seen, and it it’s happening quite often. I mean, obviously, scaled at the $1 billion run rate that I mentioned. So that’s something where — we don’t get a long window today, but it’s not harming us.

In fact, it’s forcing us to work at a higher level, and that standard makes it so that our product is delivering a specific value in a short window, which allows the advertiser to see more incrementality on the dollars that they spend and question attribution less. Now, over time though, we want our advertisers to be able to measure us based on the way that they want to measure us. And companies use different attribution tools, some of them have internal tools. So, the same way on mobile app we integrated with third-party solutions, we are working on integrations in the web space as well so that the advertisers can have multiple reference points. They can feel confident in the dollars that they spend as they scale us. And our aspirations are to become their biggest or their second biggest channel, period.

And if you become that big, you want them to have a lot of confidence in the dollars that they’re spending.

Rob Sanderson: All right. Thank you, guys.

Adam Foroughi: That’s it. Thanks, everyone, for joining us today.