AppLovin (APP) Q4 2025 Earnings Call Transcript

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Date

Feb. 11, 2026 at 5 p.m. ET

Call participants

• Chief Executive Officer — Adam Foroughi
• Chief Financial Officer — James Heaney
• Chief Operating Officer — Matt Stumpf

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Takeaways

• Revenue -- $1.7 billion, representing 66% growth year over year, driven by advancements in core mobile gaming technology, seasonal momentum, and expansion in e-commerce.
• Adjusted EBITDA -- $1.4 billion, up 82% year over year, resulting in an 84% margin and over 700 basis points of margin expansion.
• Quarter-over-quarter adjusted EBITDA flow-through -- Approximately 95%, highlighting efficient incremental revenue conversion.
• Free cash flow -- $1.3 billion, a year-over-year increase of 88%, raising the cash balance to $2.5 billion.
• Full-year revenue -- $5.5 billion, up 70% year over year.
• Full-year adjusted EBITDA -- $4.5 billion, an 87% increase year over year, with an 82% margin.
• Full-year free cash flow -- $4.0 billion, achieving 91% growth.
• Share repurchases -- 800,000 shares repurchased and withheld during the quarter for $482 million; 6.4 million shares repurchased and withheld over the year for $2.6 billion, entirely funded by free cash flow.
• Remaining share repurchase authorization -- $3.3 billion as of period end.
• Weighted average diluted shares outstanding -- Reduced from 346 million to approximately 340 million over four quarters.
• Q1 2026 revenue guidance -- Forecasted between $1.7 billion and $1.8 billion, reflecting 5%-7% sequential growth.
• Q1 2026 adjusted EBITDA guidance -- Expected in the $1.5 billion to $1.5 billion range with an approximately 84% margin.
• E-commerce self-service rollout -- Currently referral-only, with general availability targeted in the first half of 2026 and notable spend increases among existing e-commerce customers.
• Generative AI creative tools -- Piloting automated ad unit generation for over 100 customers, with plans for broader rollout and additional video model launch.
• Advertiser funnel metrics -- Roughly 57% of qualified leads convert to live advertisers, with approximately 30-day breakeven for advertiser lifetime value to customer acquisition cost during pilot testing.
• Bid density and MAX auction -- Growth in auction participation cited as expanding market economics, with a 5% fee charged to outside winning bidders on low-value impressions.
• Prospecting campaign product -- Launched in Q4, enabling advertisers to target new customers, achieving rapid adoption and improved results for clients able to upload historical purchase data.

Summary

AppLovin (NASDAQ:APP) delivered record-breaking growth in both revenue and profitability, attributing its results to ongoing advancements in core AI models and an expanding e-commerce initiative. Management directly addressed investor concerns over competition and AI disruption, emphasizing that increased auction participation and product innovation continue to enhance market economics rather than erode company value. E-commerce self-service onboarding showed accelerating client spend, supported by pilot programs for generative AI-driven ad creative, while a new prospecting campaign product drove swift advertiser uptake and performance.

• Adam Foroughi stressed, "We continue to grow very quickly, despite the numbers getting much bigger," and confirmed that sequential revenue and EBITDA growth is guided above typical seasonal trends.
• Recent advances in AI models produced what management described as a "material lift" for e-commerce client returns, catalyzing incremental advertiser budget allocation to the platform.
• The company reported that its tools for automating complex ad formats are in use by over 100 e-commerce clients and will soon roll out to broader audiences, aiming to close the gap with gaming advertisers.
• AppLovin cited a 30-day breakeven in LTV to CAC for new self-service advertisers, indicating early success in scaling the e-commerce funnel via both referral and test marketing channels.
• Management reiterated that increased competition in its MAX auction model typically benefits economics: "When competition wins an impression, it is very likely to be the one that we value less."
• With $3.3 billion in share repurchase authorization and ongoing cash generation, AppLovin signaled continued focus on capital returns alongside reinvestment for organic growth.

Industry glossary

• MAX: AppLovin's in-app ad mediation and real-time auction platform that matches advertiser demand with publisher supply across mobile apps.
• Axon 2: Proprietary AI model by AppLovin used for ad valuation and targeting, underpinning bidding and monetization strategies.
• Pixel: JavaScript-based tracking code placed on advertiser websites to share conversion, transaction, and user engagement data with AppLovin's ad platform.
• Prospecting campaign: An ad campaign product allowing advertisers to focus acquisitions on new, rather than repeat, customers using historical purchase data as a targeting input.
• GA (general availability): Product or feature availability to all customers, moving beyond limited referral or pilot-only access.
• LTV to CAC: Ratio comparing customer lifetime value to customer acquisition cost, commonly used to measure the effectiveness of marketing spend.

Full Conference Call Transcript

Adam Foroughi: I want to start by addressing what is clearly on many people's minds. While I prefer to ignore short-term fluctuations in the stock price and focus on maximizing value over the long term, the recent volatility warrants addressing. For the past few weeks, there has been a lot of discussion about how AI and competition will challenge our business. But when I look at our internal dashboards, we are delivering the strongest operating performance in our history. What is fueling that growth is our own AI models. And as research in AI, both internal and external, continues to improve, our business will grow with it. There is a real disconnect between market sentiment and the reality of our business.

Before I talk about the opportunity ahead, let me explain how we think about competition in AI. First on competition. Since day one, we have competed against many companies. We have never feared competition because it forces us to innovate to serve our gaming ecosystem even better. We operate a foundational piece of the ecosystem: the MAX auction. It is critical for the ecosystem that the MAX auction improves through more competition, which in turn helps publishers make more money, leading to more user acquisition. Now, in a typical zero-sum auction-based market, if one improves, another loses.

In our case, as bid density goes up, the pie expands, and while our share of the auction may shrink, our economics actually grow. There are impressions our model understands extremely well and it values highly, and others where we have less signal and value them less. When competition wins an impression, it is very likely to be the one that we value less. This leads to the publisher making more, and in many cases, we do as well, because instead of winning a low-value impression, we get to charge the winning bidder 5%. When you hear about a start-up coming for our business, you should be asking how their value proposition can be stronger than ours.

If our value proposition was not strong with our partners, we would have lost those relationships long ago. We have competed very well in mediation against giant companies. The network effects in this business are very real. We scaled our network by providing the best monetization, and even more importantly, the best advertising tools to publishers. The combination is not something peers can overcome. Second, let us talk about AI and game creation. The bearish view assumes that if AI makes games easier to build, the value of our ecosystem declines. Well, we believe the exact opposite. AI will dramatically lower the cost of creation, which means content will explode, and when content becomes abundant, discovery becomes a scarce resource.

Even in the past, as mobile games were built by human teams, the content was plentiful, and in many cases commoditized. That is actually what allowed us to deliver such a strong value proposition through our advertising solutions. In a world where anyone can create an app or a game, millions of experiences will compete for attention. The winners will be the platforms that can efficiently match the right user to the right content at the right moment. That is exactly what our models are designed to do. We are not tied to any specific genre or format—casual, mid-core, or beyond. Our systems follow engagement, and AI only increases the potential of that capability.

Furthermore, we do not see any evidence of a declining mobile gamer. Casual gaming serves a different human need than console, PC gaming, AAA games, or any other form of deeply immersive game experience. People will always look for entertainment that fits naturally into their day. What is changing is how well that attention can be monetized. Even today, we convert only a small portion of those impressions that we serve. We view that not as a limitation, but as a large long-term opportunity as our models continue to improve. Now that brings me to what we control: performance and culture. Our performance—our business is executing extremely well. We continue to grow very quickly, despite the numbers getting much bigger.

We delivered strong growth in Q4, and despite typical seasonality where Q1 should be softer than Q4, we are guiding to meaningful sequential growth. That reflects both continued strength in gaming and the scaling of our e-commerce and our self-service customers. On culture, we embrace being underestimated. A skeptical market sharpens our focus and pushes our teams to execute. Our revenue per employee remains among the highest in the world because we build the best and most scalable products in our category. If the market chooses to price our stock based on fear while we continue to compound revenue, cash flow, and product capability, we will stay focused on execution and let our results speak over time.

From where we sit, we are still in the early innings of what this platform can be. I will now turn the call over to Matt to walk through the financials.

Matt Stumpf: Thanks, Adam.

Adam Foroughi: Q4 marked what was not just a strong quarter, but the most—

James Heaney: Exceptional year we have ever delivered, and one of the strongest performances in the public markets. At our scale, the combination of growth, profitability, free cash flow, and capital returns we are delivering is extraordinarily rare. Revenue in the fourth quarter was $1,660,000,000, up 66% year over year, driven by continued technology advancements to our core mobile gaming business, seasonal strength, and the expanding impact of our e-commerce initiative. Adjusted EBITDA was $1,400,000,000, up 82% year over year, representing an 84% margin.

Margins expanded over 700 basis points from the same period last year, and quarter-over-quarter flow-through to adjusted EBITDA was approximately 95%, again demonstrating our relentless dedication to execution and how efficiently incremental revenue converts into earnings for our business. Investors often reference the Rule of 40 in software. On that basis, our 66% revenue growth and 84% adjusted EBITDA margins translate to a score of 150. That level of profitability at this growth rate is almost unheard of and reflects the fundamental operating leverage of our model. Free cash flow for the quarter was $1,310,000,000, an 88% increase year over year, growing our cash balance to $2,500,000,000 and reinforcing the strength of our balance sheet.

This was a truly remarkable year for AppLovin Corporation. Revenue reached $5,480,000,000, growing 70% year over year. Adjusted EBITDA was $4,510,000,000, up 87% year over year at an 82% adjusted EBITDA margin, a margin profile that very few companies ever achieve, let alone sustain at this scale. Free cash flow totaled $3,950,000,000, up 91% year over year, underscoring not just growth but the exceptional quality and durability of our earnings. Simply put, very few public companies are scaling faster, more profitably, and with greater cash generation than we are today. That strength directly translates into shareholder returns. During the quarter, we repurchased and withheld approximately 800,000 shares for $482,000,000.

For the full year, we repurchased and withheld approximately 6,400,000 shares for a total of $2,580,000,000, funded entirely by free cash flow. As of the end of the year, we had a remaining share repurchase authorization of approximately $3,280,000,000. Over the last four quarters, we reduced our weighted average diluted shares outstanding from 346,000,000 to approximately 340,000,000 while simultaneously investing in organic growth and maintaining substantial liquidity. Our share repurchase program reflects our conviction in the value and durability of the business. Turning to our outlook for 2026, we expect revenue between $1,745,000,000 and $1,775,000,000, representing 5% to 7% sequential growth.

Adjusted EBITDA is expected to be between $1,465,000,000 and $1,495,000,000 with an adjusted EBITDA margin of approximately 84%, maintaining best-in-class profitability as we continue to scale. To close, AppLovin Corporation represents a combination that is exceedingly rare: sustained hypergrowth, exceptional margins, massive free cash flow generation, and disciplined capital returns. We believe this puts us in a category of our own and positions us to continue delivering outsized value for shareholders over the long term. Now with that, let us move to Q&A.

Operator: Now begin the question and answer session. Please be sure to unmute and turn on your video before asking your question. We will take as many questions as time permits. And since we have many questions today, please be patient as we move through the list. First question will come from Benjamin Black with Deutsche Bank. You may now unmute and ask your question.

Benjamin Black: Great. Thank you for taking the questions. So my first question is on the e-commerce opportunity. So can you perhaps sort of reflect on the self-service launch? What were some of the key learnings? What worked, what did not, where is there room for improvement? And to the extent possible, it would be great if you could sort of share or quantify the e-commerce contribution to revenue or gross ad spend this quarter and in the guide? And then I have a quick follow-up. Thank you.

James Heaney: Yeah. So the e-commerce business has been live with us for a year and a half. It is doing really well. Q4, we opened up the self-service platform referral only. So we are not at the point yet where we are sort of a GA-type launch. We will get there. We said first half of this year—that is still on track. What gets us excited are a couple things. One is the current customers that had lapped Q4 2024 into Q4 2025 saw material increases in spend as our models just keep getting better. Now remember this business and the model around this business that drives the value for the advertisers is really in its infancy.

It takes us a while to continuously iterate to improve the model. In fact, just a few weeks ago, we had a pretty sizable uplift. So those same customers from the prior-year cohort saw a big growth. Then you ended up with new customers coming in from the referral program. I mentioned on the last earnings call, we were seeing substantial growth there. Not going to see anything that is going to impact our overall numbers for a while, but we are seeing great trends. And I will talk about advertising leading advertisers into our platform later on the call, but we are just seeing numbers that get us excited.

On the breaking out e-commerce, we are not going to do that because we think of our platform as a unified platform. Let us say tomorrow the engineering team improves the gaming model 50%. Well, e-commerce would go down, but the business would be ripping. That would not mean that there is anything wrong with our platform. Fundamentally, we are one single auction. Getting more diversity will give the model more ways to serve the end consumer and should drive up our overall conversion rate, but we think if we start talking about verticals in a marketplace like ours, you start getting really misleading information that will throw investors off.

Benjamin Black: Great, I guess. And then sort of my second question is sort of, you know, it is related to a feature set that you are rolling out. So I think in the past, you mentioned the conversion uplift your partners could see if they have the ability to not only optimize for the best-performing creatives, but also sort of really scale and automate the creation of these video assets. So I guess with that backdrop, how far along the automation curve are we now and where would we be in the next, you know, call it, 12 to 18 months.

James Heaney: Yeah. Great question. We are still pretty early. I pulled some numbers earlier just to compare where e-commerce companies are when they upload ads and how many they upload to our platform versus the gaming companies that have really had a decade plus to optimize for our platform. Top gaming companies run tens of thousands of ads at any given time. The top e-commerce companies are in the hundreds. So you have got a huge discrepancy here. If you throw more ads at our system, the model does much better. That is just a fact. It gets the chance to diversify what the end user sees and try to find something that is going to eventually convert that user.

Now how do we bridge the gap? It is twofold. One is the customers have to get more accustomed to our platform to know what types of creatives work so that they can build up production around the things that work and multiply out the count. More importantly, though, generative AI tools to build creatives in a really low way and an automated way is on the way. We already have in a pilot with over 100 customers generative AI-based tools for one part of the ad unit. Our ads are a video, plus then an interactive page, and then follow-up of a shop preview dynamic product page.

That middle one, the interactive page, is not something that these advertisers are accustomed to building because they do not need them on social or search. We are now generating those automatically for over 100 customers. We will roll that out soon; it is showing good performance to the broader set of customers. Shortly, we are going to have the video model go live as well. We are going to run the same pilot process. We are going to make sure the video output looks good.

But if we get to a place where the video model can help these customers create new video ads in bulk in cost of dollars versus cost of thousands of dollars, we expect the count of ads these new customers on our platform is going to go up a lot, and that will make them more competitive against the gaming customers that are on our platform.

Benjamin Black: Right.

James Heaney: Thank you very much. Very helpful.

David Hsiao: Yep.

Operator: Your next question will come from Jason Bazinet with Citi.

Jason Boisvert Bazinet: Thanks so much. How are you guys doing?

Adam Foroughi: Good. Hey, Jason.

Jason Boisvert Bazinet: I think one of the things that investors have always struggled with a bit is just sort of what they would call the black box nature of the model. Like, they cannot get comfortable, sort of, you know, doing the P times Q and sort of extrapolate the model out. And I know you are not going to break out, as you said, you know, e-commerce from mobile.

But as investors are sort of looking at these of e-commerce accounts that have, you know, your Pixel on it, you know, what counsel would you provide to the buy side in terms of using those numbers and trying to do some math to get some sense of how well you are doing. Thanks. Yeah. I mean, look, it is really, really hard because we are—

Adam Foroughi: Just getting started. Facebook is probably pixeled over 10,000,000 sites. You have been publishing our Pixels in the thousands. So it does correlate the count of advertisers that we have on the platform—we are just starting out. We cannot build a P times Q model in a period of time that we expect to have really outsized growth. You open up the platform, start running marketing to the platform, start doing more sales, going to end up having a ton of advertisers coming in. We cannot predict it. It is not going to be stable until we get to a much further-into-the-future point.

But what gets us excited, mentioned on the last answer, is we are already testing in advertising to get customers on platform. So what you are seeing now is just referral-based advertiser count. But if we start actually being able to market platform and get customers to convert through the funnel, that is going to help us really catalyze faster growth to go get advertisers in the absence of a sales team. And one stat that is really cool that I pulled earlier: we are testing in light volume on ads on social and search, and then we are doing referral programs. Right now, we are seeing somewhere around day 30 LTV to cost of user acquisition.

So if you think about lead gen models and if you know lead gen models, and also if you understand the life-of-value we create for advertisers, which is in the many years, being able to break even on the media buy in 30 days is exceptional. We have got arguably one of the best business models the world has ever seen. We are seeing the ability to market our platform in small testing at that level. That gets us excited. Now we are not ready to go to GA yet, and you can ask why. And the why is because we still need to optimize our conversion funnel.

We are no different than any social network that is going out and trying to get users. We want to get users into this advertising platform. Right now, we are seeing, of qualified leads, 57% of advertisers go live. That is 43% breakage. We think we can get that number much closer to 100% before we open up. And despite that, we are seeing this 30-day breakeven, roughly, on LTV to CAC. So we are really excited about where we are. Think we are going to go through this hypergrowth phase as we open up and really start pouring advertisers in.

Once we get to a stable place where we can start predicting count of advertisers in quarters to come, we will give you the P times Q.

Jason Boisvert Bazinet: Thank you. Yep.

Operator: Your next question will come from Omar Dessouky with Bank of America.

Omar Dessouky: Hey, guys. Thank you for taking my question. I wanted to ask a more general question because the market seems to be having an AI fear. So, you know, let us just forward three to five years in the future, you know, to potentially a world where consumers interface with the Internet through natural language-based agents. You know, LLMs are different than performance advertising neural networks, but how would your business be affected by potentially a change in how consumers, you know, interface with the Internet. So that is the first part of it.

And then the second is how do you expect, you know, again, over the long term, three to five years, how would you expect mobile game developers—casual mobile game developers—to adapt their content to a world where they compete for time with these sophisticated chatbots.

Adam Foroughi: Yeah. So great question. The way I see the LLM is that it is going to enable anyone to be able to type out ideas for a game, get a game created. That does not mean you are going to get users to play your game. That means you can create content in a very low-cost way not being an engineer. Content production for studios that are developed, that are sophisticated. It will also create a flood of content that is more personalized across people who could just become game developers with no engineering background. That is a good thing for us. In the talk track I mentioned, you get more content; that content becomes commoditized.

The discovery platforms, of which there are very few, become the true value because those customers are going to have to come to MAX to monetize; they are going to have to come to our discovery platform to run advertising to get users to their space. Now if humans just want to talk to a chatbot, do nothing else, of course, while there is nothing else that they are going to do, we would lose time spent in games. That seems far-fetched. The games that people play today in our domain are not very immersive games. They are quick-to-play relaxing games. And people play things like solitaire. People play things like mahjong. This audience skews older. It skews female.

This is an audience that is very unlikely to stop playing crosswords in 10 years because they are talking to a chatbot. So not only do we think that the base audience is going to keep playing games, you are going to need relaxing outlets. If LLMs increase productivity, people likely have more time.

Omar Dessouky: To go to outlets like games. And if LLMs increase production quality,

Adam Foroughi: And production capability of games, you can have more content, which leads right into a business model like ours.

Omar Dessouky: Okay. Thank you.

Operator: Your next question will come from Bernie McTernan with Needham. Great. Thanks for taking the question. Wanted to follow up on e-commerce.

Bernard Jerome McTernan: Given the self-service launch, are you seeing any changes in the types, size, or is the customers that are entering because of self-service versus the prior managed service? And then also as a follow-up, we have seen some examples in our own tracking of apps that are not e-commerce with the Pixel. Is this a one-off or a new growth factor that you are pursuing within this?

Adam Foroughi: Yeah. I mean, obviously, with opening up self-service, we are not gating to minimum GMV anymore. So in the prior year, we had pretty high minimum standards for businesses. You are getting companies of a few $100,000 of GMV, a couple million dollars of GMV a year, buying on our platform. What is nice about that is not only do we see the ability to track performance very clearly on a brand that is small, they start spending money, the money translates to revenue, and it is obvious in their numbers that their preexisting revenue was a few $100,000. I will give you an example.

We had a year ago this Israeli cookware company come live that did $4,000,000 of revenue. And these types of stories make us really proud. Last year, they scaled on our platform. 65% of all their user acquisition spend was on our platform. They scaled to $16,000,000 of revenue and are profitable in doing so. We can see the results directly translated from the spend on our platform to their growth. This year, they are ramping so quickly again, putting most of their UA spend on our platform. It is looking like they are projecting to $80,000,000 of revenue. So you start seeing that kind of ramp up.

In certain specific customers, and we know the product works, and it works exceptionally well. That makes us proud. We think what we really like to do at this company is service the smaller businesses, help those smaller businesses become big businesses. That is how we built into gaming. We helped the indies first. Now every gaming company in the world that is in mobile that is substantial is probably working our platform in a major way. But in e-commerce and these other categories, we feel the same way. Help the smaller businesses, help them scale their business, then we will get to all the brands over the coming years. In new categories, again, we are not gating anything.

So if you end up in auto insurance and you sign up for our platform today, you can go live. We are still early in these other categories because for each one of these cases, we have to tune the model somewhat, and we are focused right now on anything that is transactional-based business versus a lead-based business. So think if you are a transactional-based business, you are not e-commerce, but you are fintech or something. That could work really well out of the box. That is another category of growth. But then there is a huge sector of lead gen businesses. You want to collect the user's information and sell them in a call center.

That is going to come too for us in the coming months. We really focus on a category like that. It is our job to service every transactional category that buys on a performance basis and do it well so that the billion-plus daily actives we see on our platform can get a diverse set of content that they can enjoy.

Bernard Jerome McTernan: Thank you. Yep.

Operator: Your next question will come from Matthew Cost with Morgan Stanley.

Matthew Andrew Cost: Hey, everybody. Thanks for taking the question. I guess starting just to put a finer point on some of the comments from your prepared remarks. Because the data points from the channel were a little unusual and thin. Did you see a test from Meta doing more advertising in the in-game, you know, ad environment? And whether or not you did, how should the market think about what potential impact a scale player like Meta, for example, getting more aggressive in that market would mean? And then a second question just around MAX. You have been in the business of convincing people to switch mediation platforms for a long time.

I guess, in light of that experience, how would you characterize the moat around MAX?

Adam Foroughi: Yeah. So two good questions. So the Meta—Meta was a launch partner in MAX. They are a good partner. They have been in the MAX platform for a long time. They are a bidder on anything that has an ID today. They are not a bidder on anything that does not have an ID. So think IDFA off. That is about two-thirds of the full-screen ad units that they currently bid on. They started bidding more on that as you saw on LinkedIn. They did not start bidding on no-ID traffic, and they might very well bid on no-ID traffic in the next couple quarters.

As you know from our business over the last couple of years that you have been following, there have been numerous times where we have added more competition in the MAX auction. Unity has grown with Vector. Liftoff rolled out Cortex, and it is growing really quickly. Moloco has been growing, and we turned them into a bidder in the last year. You had Google switch to bidding. Every time this has happened, there has been this confusion around, well, in an auction dynamic-based system, competition should decay AppLovin's edge. You have never seen that happen, and this is what I tried to cover in the talk track.

The reason is that one, we are really big and really good at what we do. But two, every impression is not worth the same thing. Our model is exceptionally good at valuing the impression for what it is, for our data and our customers. Sometimes it values it really high, where we make a lot of money. Sometimes it values it lower. We make less money or potentially lose a lot of money.

And what happens when you get these bidders getting better is that they take some of those impressions that we value low, where we might not have made any money or any material money, and now we get a 5% amount that we can tax the bidder in our ecosystem. So growth in the ecosystem allows the market economics to improve, and we have never seen growth in the ecosystem cause harm to our AppLovin bidding environment since we got so good. Now this is post Axon 2 where we became the market's dominant player. So I do think it is an important point that people are getting lost on.

So I want to see if you have another question on that before I go on to the mediation discussion.

Matthew Andrew Cost: No. That was very clear. Thank you.

Adam Foroughi: Okay. So on mediation, look. We got in the market with MAX when we bought it and built that tech. We did not buy technology. We just bought a way into the market. That was in 2018. The MAX platform before we bought MoPub had already grown to become number one in the space. We bought MoPub, put the two together. As everyone knows, we are very dominant in the sector. We took the MoPub technology in sub-90 days, threw it out, migrated everyone that we could over to our platform, rebuilt the best features of MoPub, put them on top of the best features of MAX, and ended up with a very dominant position.

At this point in mediation, there have been a few players that are sort of out of business, and then there is Google-level play and us. And then, obviously, you have the start-up that people have been discussing. So in a world where CloudX becomes a start-up, comes into the space, you have to talk about, like, what are they walking into? How is the world different today versus what it was? The moat around our mediation is not because of the mediation. We are very good. We have got the most bid density. In any mediation A/B test, if you have talked to publishers, you will hear MAX does better.

But we do not blow it out of the water. We are a few percentage points better than other mediations. If someone wanted to pay a bonus to cover that, they could potentially pay a bonus to cover that. It gets really expensive for the publisher, and where we are really locked in is that we have the best advertising solutions on the market. In fact, for a lot of these publishers, we are over 50% of all their user acquisition spend. They cannot go get that anywhere else. If they go off MAX, that decays. And so they are left in a world where they have the best buying tools, have the best monetization tools.

It becomes a really strong 360 solution, and their growth depends on it. And then the MAX ecosystem is not growing slow. As we have talked about in prior calls, this is a double-digit, very strong growing category where these publishers are seeing their businesses improve because of the improvement in our technology. You have got that in the foundation, got a really strong moat with technologies that no one else can replicate or have, then you end up with a sticky solution, and we are very confident our solution is just that.

Matthew Andrew Cost: Great. Thank you so much.

Operator: Your next question will come from James Heaney with Jefferies. Yeah, great. Thank you, guys.

James Edward Heaney: Are you thinking about the Axon marketing investment in 2026? I know you talked late last year about a goal of maybe $1,000,000 in spend per day. Is that still the right way to think about it? And is ultimately GA kind of the biggest prohibiting factor to you guys doubling down on that investment? Thank you. Yeah. I mean, like, right now, we are testing, so numbers are not—

Adam Foroughi: That big. You did not see anything reflected in our EBITDA margins. In fact, you saw them go up to 84%. We think the growth in the business is so high, and our LTV to CAC is going to look so juicy, you are not going to see much decay in our EBITDA margins from ramping up marketing. If you do, then that would be a great thing. It just means we are ripping on the marketing side, and we see a ton of customers that we can bring in to accelerate growth. It is much more likely that we are going to go controlled on this because we do want to take our time to build out tools.

When we start buying and go GA and bring customers in, if we do not have good content creation tools for them—create the video with generative AI tools, create the interactive pages with generative AI tools—and do it in an exceptionally strong way, we will not have as much success on our platform. So that is a long way of saying we are in no rush. We are seeing 30-day LTV to CAC roughly. If we see that at scale, we are going to scale. But we are not in a rush because we want the tools to catch up to the opportunity.

James Edward Heaney: Great. Thank you. Yep.

Operator: Your next question will come from Alec Brondolo with Wells Fargo.

Alec Reid Brondolo: Yeah. Hey, thanks so much for the question. I appreciate it. I to double click on the Meta thing because I kind of think that is the most of all the noise in the market, I think Meta is by far the most important. You know, right now, probabilistic targeting is the basis of competition between all the mobile game and app networks. I think there is no doubt that you could definitely compete effectively against Meta on a probabilistic basis.

When I talk to investors, I think the concern in the market is that Meta could find a way to bid deterministically in opt-out ATT traffic with their audience graph, which would give them, you know, an advantage over the vertical ad networks. Do you think that is possible from a tech perspective? And if it was, would you still be confident that market expansion could offset the loss of the market share?

Adam Foroughi: Yeah. I mean, look, I think it is possible from a technology perspective. I think it is blatantly against Apple's terms. I do not think the space is big enough for Meta to say they want to violate the platform they depend on's terms. So I am skeptical what you said is going to happen. It would make no logical sense. In a world where they are bidding deterministically or probabilistically on no IDFA, they are still competing against the Axon 2 model. Five years ago, when Meta was really big in the space—and I think this is what is throwing people off—people recall a time Meta was half the space.

They think it is going to be half the space again. Meta has been on IDFA-based and Google AdID-based traffic since that no-IDFA change. Nothing has changed for them. What is changed in the marketplace is that the other ad platforms that are built for this category—Unity, Liftoff, Moloco, etc.—have gotten better. Now we have gotten the best. Axon 2 was the biggest breakthrough in a model in this category, period. And we were able to end becoming the number one by a lot. Axon 2 did not exist five years ago, so there is no world where Meta is going to end up becoming kind of a dominant player in the face of this competition.

In fact, I do not see a world anyone else can because they are going up against that dominance. And these models, as they build more data, it is a closed-loop model that is continuously reinforcing itself and getting smarter. Our model is so far into getting smart for this niche. The niche is not that small, and we have got such a strong position. It is highly unlikely that someone else is going to come in and materially disrupt it. So long way of saying again, no. We do not see what people are so afraid of. Think psychologically, people just index on numbers from five years ago and think, oh, Meta is going to ramp to that.

Just ask the customers you talk to what is the share of wallet between us to them and to everyone else on IDFA-based traffic, and that will give you an indicator of how good we are.

Alec Reid Brondolo: Perfect. That is super helpful. And maybe just one additional question. You know, on the marketing dollars that you are spending against Axon today, where you are earning the 30-day LTV to CAC breakeven, what are the most effective channels? Like, I see the ads on Google Search. I see the ads on Facebook and Instagram. Where are you finding the most success? Which platforms are you finding the most success in leveraging to acquire customers today?

Adam Foroughi: It is a great question. I mean, we are too early in testing to really assess or give anything directional because we do not want to be misleading. But I will say some of the coolest yields that we have seen and coolest partnerships are these partnerships with the measurement company. So if you talk to Triple Whale, they have got a sponsorship from us. TBPN, the podcast, branded their Gong with our brand, and that has driven a bunch of business. So stuff like that—we are at such an early point. Part of the direct response channel here is actually just building the brand. So when we get placements like that, people start hearing about this Axon Ads platform.

Then they go to Google, and we do not have any SEO yet. Once we get history, put more content out on our blog, which we are committed to do, and get more link backs, we will also have SEO. But today, in the absence of Google, search words are also great. We are starting to get brand recognition. People know our platform is critical. They go search Google, and then we are the first AdWord now—not the first organic link because we do not have that history. So all this stuff is going to improve over time. And we think our job is to combo brand advertising alongside this direct response to really unlock growth in this thing.

Jason Boisvert Bazinet: Alright. Thank you so much.

Operator: Your next question will come from Clark Lampen with BTIG.

Clark Lampen: Thank you, guys. At the risk of, I guess, sort of, you know, overdoing it around this Meta point, I wanted to see if you guys can just—Matt is laughing, so I think I am overdoing it right now—but just remind us, I guess, the sort of scale of bidding that you guys are doing right now. I think the 11,000,000,000 or over 11,000,000,000 number that you provided in the blog post is the most recent example. Is that something that really needs to be replicated in this segment of the market for probabilistic bidding to really drive signal or capture signal that would allow somebody to replicate the same sort of degree of efficacy?

I think it would just be helpful for people to understand maybe even if somebody wanted to move in this direction, what are the sort of capital constraints of doing something like that?

Adam Foroughi: Yeah. I mean, look. First of all, like, at the base, there are different approaches to modeling these businesses. Meta has a model that is fantastic, super sophisticated, but built for social. Most of their training data is on social. We have got a model that is cutting edge, very sophisticated, built for our ecosystem. Our training data is predicated on that ecosystem. Our customers are perfectly tuned for that ecosystem. We started in gaming. We are the biggest there is in game UA dollars. Those dollars are not just going to shift because someone else comes into the space. The dollars are already locked in on us, and our model is very smart.

When there is a high-value user, sometimes our model bids thousands of dollars on a CPM basis. The model knows what works for these customers. So it is just not something that is conceivable in a marketplace where you have budgets that are already given to us, and we are on cutting-edge technologies, for someone else to come in. Now if we stop innovating, and we decay on the technology side, and we stop providing the service to the customers where they start looking around, yeah, those things could change, but that is not going to happen overnight.

And the one thing we can say confidently, 14 years into being an engineering product-led org, you have seen us move incredibly quick. We are innovators. Our engineering team is top notch, second to none in this field. And so we are very much focused on continuing to push our models forward. We are doing it from a very strong leadership position.

Clark Lampen: Okay.

Clark Lampen: And if I may just ask sort of a very quick follow-up. Prospecting campaign—this was a product launch that sort of came about recently. There was a lot of very strong feedback in the channel throughout the quarter around the efficacy for some customers seeing, you know, full shift in sort of repeat versus new customer mix. Can you talk about the way that product—I know that you guys do not want to give specifics around your non-gaming business versus the gaming one. But would it be possible to sort of contextualize the impact for us or maybe what you are seeing with advertiser behavior heading into 2026?

Adam Foroughi: Yeah. I mean, you have probably talked to some of the advertisers, so you hear positive commentary on it. But it is really hard for advertisers to understand the incremental value of retargeting. It is really easy to understand the incremental value of a new customer. And so it was not lost on us for a year, year and a half when we got into the market that just a universal campaign that had a split of new customers and retargeting was not the final answer. We needed more targeting for these customers to map to their goals. So we rolled out this product in Q4. We let them upload their historical purchases.

Using that data, our model can start tuning away from purchasers from the past and towards users that they have never seen before. Results were fantastic. It takes a while in an advertising marketplace for every new product to get adoption, but we have seen really quick adoption on this one because when they flip the switch, they instantly start seeing many more new customers.

Alec Reid Brondolo: Thank you.

Operator: Your next question will come from Robert Sanderson with Evercore.

Robert Jason Sanderson: Great. Thanks for the questions. Appreciate it. And you have mentioned a couple times now the connection between AdROAS and MAX. Just wondering if we could maybe put a finer point on it. If a publisher were to give, you know, another platform first look at inventory or something like that, would that significantly degrade that connectivity between AdROAS and MAX from a UA perspective for that publisher? And then I am going to just click on.

Adam Foroughi: Yeah. I mean, our terms are that they cannot do first look. So that is not part of the equation.

Robert Jason Sanderson: Got it. Perfect. And then I think there is also a notion out there that demand partners might bid differently in a different environment or something along those lines. Do you have any thoughts on that? Just—

Adam Foroughi: I mean, look. MAX is fully fair, transparent. We get audited by the bidding partners—the vast majority of the marketplace. It would be a foolish business decision to bid differently in a very small platform versus the platform that owns most of the space. It does not make any sense. So if someone is going to be a competitive bidder, they are almost certainly going to want to be a competitive bidder in the marketplace-leading market.

Robert Jason Sanderson: Got it. And then just one last quick follow-up on the breakage that you mentioned in terms of the qualified leads to go live or launch. Just wondering if you could talk about, you know, maybe some of the inhibiting factors today and how you would plan on solving some of those.

Adam Foroughi: Thank you. The biggest one is that they just do not have video ads for our platform made to the type of format that we need. So those generative AI tools should be able to raise that to a much higher percentage of customers going live.

Robert Jason Sanderson: Yeah. Great. Thank you very much. Yep.

Operator: Your next question will come from James Callahan with Piper Sandler.

James P. Callahan: Just a follow-up on the market growth. You have kind of talked to this double-digit framework. To the back half of 2025, can we expect that through 2026? Is that, like, a step-function change that you think can continue?

Adam Foroughi: Look. MAX is growing really quickly. A lot of it is driven by the strength of our platform. So when we were growing 70% plus year over year, a lot of the dollars spent on our platform are the publishers buying customers. So it fuels growth in the ecosystem. So long as we are doing a good job and the other marketing platforms in gaming are doing a good job, the MAX market is likely to be growing really quickly. And this is now no longer a case where you just do not have other data. Unity Vector is growing really quickly.

You have got a company like Moloco that is private, but talking about going public, that is growing quickly. Liftoff did testing the waters in a road show, so those numbers were out there that they are growing really quickly. You have got all these market players growing quickly; the MAX market is growing in a way that people think, understood, or would have expected, and we are not seeing any slowdowns there.

James P. Callahan: Got it. That is helpful. Thank you. And then just you have talked about this reinforcement learning framework for gaming. Now that we are, I guess, like, a year and a half into e-commerce, how does e-commerce reinforcement learning kind of compare? Is it faster or slower? Does it take longer?

Adam Foroughi: No. I mean, what we have talked about is that the gaming model, based on its own results, can improve. So it creates its own memories. It gets smarter. The e-commerce model is the same thing, but I do just remind people that we are much earlier in e-commerce. We have very little data in the marketplace. So if you think about transactional volumes that we have in gaming, we have got most of the market inside our system. So the model is pretty complete from a data perspective. And then also we have had now, I think it is roughly three years, to continuously improve that model.

As you have seen, we have continuously improved it many times over the last 12 to 14 quarters. E-commerce is newer. It is starting from an earlier place. We have much less data penetration. So we cannot go and track, like, okay, in a stable world, how much is the model improving? Because the model is going to be improving much more so from our team improving the model with changes and then just customers coming on. Every new customer that pixels their site passes data to us—both engagement data and transactional data. As we get customer ramp up, our data penetration in the market is going to go from very little to much greater.

And as that happens, that is going to be a big catalyst for improvement in that category.

Alec Reid Brondolo: Great. Thank you.

James P. Callahan: Yeah.

Operator: Your next question will come from Steven Ju with UBS.

Zhihua Yang: Right. Thank you. Hi, Adam. Hi, Matt.

Matthew Thornton: I think you have previously talked about AppLovin Corporation being demand constrained versus supply constrained, but can you help clarify? In particular, there is yourself and the private company you just called out, as well as Unity all out there getting better as well. And I think investors are so accustomed to thinking about all of this being zero sum. You know, can you help us think about how much more supply there can be with perhaps new publishers and what existing publishers already accept, and what they can think about doing.

Adam Foroughi: Yeah. I think we are a long way from needing new publishers. I mean, we have talked about one—I think people should believe it is not a zero-sum market. This is not rideshare, where one person takes a ride and another loses. So if that was the case, with our growth and our market position being this dominant, there would be no conceivable way these smaller gaming ad networks could be growing the way that they are. So if we set aside the notion of zero sum, then you have to ask, well, how many transactions can we drive to this billion-plus users?

A billion users playing mobile games, casual games every single day—shopping users because they are adults, they skew female—are not done at this number of dollars. I mean, if you just translate to Meta's users, it is 3x more users, a little bit more time spent. But the revenue that they are driving to advertisers over what we are driving and the whole space is driving to advertisers is probably 8x. So there is a lot of room to go on monetizing this audience. We have also given you historically that our conversion rates on a thousand impressions were about 1%. Obviously higher now. We talked about that a year or two ago.

Conversion rate is higher, but we think that can go as high as 5%. That is what we see when we are serving an ad where the model is confident that the user is going to take an action. Now why is not our whole business converting at 5%? Why are we not doing $50,000,000,000 of revenue on the system? We do not have enough advertisers yet to know what the user is going to be into at that moment. So we constantly serve them gaming ads. Some users are into a new game. They are converting at 5%—50 over a thousand. Other users are not, and the conversion rate is atrocious.

It might be 2 over a thousand, and it dilutes you to 1%. E-commerce has given us a path to diversity. But we only have a few customers. If we get deeply penetrated into the space and we have got really diverse content to show the customer, we think that conversion rate is going to keep rising, and it is going to keep rising really quickly.

Matthew Thornton: Gotcha. And secondarily, I think you have articulated a desire to go after advertisers of a certain size. So, you know, first, before targeting the advertisers with perhaps larger budgets, but maybe more upper funnel? So, you know, is that part of the market addressable right now, or is that something that might be in the road map in the future?

Adam Foroughi: I think we are going to be going after anything that is not brand dollars. So by brand, I mean companies that are not optimizing to a point of transaction. Whether they optimize to a point of transaction or something performance-based like a lead, we are going to go after them. Now we are not going to build out the Salesforce to go—even in the performance space, advertisers then need you to go to their agency, they need you to take a lot of time to go get a lead, to go get an advertiser live.

When I talk about this Israeli cookware company, it was a business that was probably spending a couple thousand dollars a day, ramped up to many tens of thousands, possibly hundreds of thousands of dollars a day on our platform. They ramped up really quickly. Scaled their business from near zero to $16,000,000 to now hoping for $80,000,000 this year. That is an example of taking a customer that did not have much of a business, plugging them into our toolset, letting our technology do the job, and creating a huge business for them, a great relationship for us. That is the type of stuff that really cascades into much more value creation over time, because it happens quickly.

They become dependent on our platform. We love those stories because we are helping them build the business. If we help Coca-Cola place more dollars in advertising, we are not moving the needle of anything in the economy. Coca-Cola is sort of blindly putting dollars out there. If we can help customers spend the dollars, see the direct correlation to their revenue, hire people, grow their business, it is a fantastic story for us because it shows that we are growing the world's economy. We are creating jobs. And we are really creating this dependency on our platform. So, really, that is what we are focused on. And in games, that was indie game developers.

In brands, that is going to be these performance D2C companies. Much more of the Shopify merchants, much less of those big brands that people talk about that buy through Madison Avenue agencies.

Matthew Thornton: Thank you.

Operator: Your next question will come from Cory Carpenter with JPMorgan.

Christopher Louis Kuntarich: Matt and Adam. Good to see you guys again. Matt, I have got to give you a question before the call ends. So I will ask about the 1Q guide, the 5% to 7% sequential growth. It is above what you typically guide to in Q1. Of course, this year, you have the added headwind, if you will, from the e-commerce business seasonality. Could you just talk about some of the assumptions you are making in that outlook and the trends you are seeing so far in the year in e-commerce and gaming?

James Heaney: Yeah. So consistent with kind of our normal practice, Corey, we are guiding to the level where we have a very high level of confidence. For Q1, obviously, coming from Q4, we had a very strong exit rate. So given, you know, the factors that Adam was talking about before—the performance of mobile gaming business, the e-commerce launch, as well as the prospecting model—we had a lot of growth in Q4, so the exit rate was quite good. And then that is partially offset by just seasonality going from Q4 to Q1 normally being a weaker seasonal period. And then we also had a couple days less in Q1 versus Q4. So it is partially offset against that.

So that is how we kind of landed at 5% to 7% sequential.

Christopher Louis Kuntarich: And then, Adam, you alluded to, I think, an unlock that you saw a couple weeks ago in the e-commerce business. Anything you can elaborate on what that was would be helpful. Thank you.

Adam Foroughi: Yeah. Look. The team is constantly improving the model. We do a lot of testing. We saw a material lift in the model. Rolled it out. Advertisers saw a huge improvement in return on ad spend. They started putting more budget into our system quickly. So those are the types of things that really catalyze growth for us. We talk to advertisers and say, test the product in our system—it is test now—but be patient because, understand, performance today is not going to be indicative of performance in six months. Our system is constantly improving because our team is improving these models. They do internal research. They use external research published in the AI field.

These techniques can apply to what we do. When they apply well, these advertisers see gains. In gaming, they have seen gains very consistently since we launched Axon 2. In e-commerce, again, we are starting from a lower point because you need to get more data and you need to get more time to make the models more complex to use that data and create a better value for the advertiser. We are now doing our job. We are improving the model. They are seeing the result. They put more money into our platform.

Alec Reid Brondolo: Great. Thank you, guys.

Operator: Your next question will come from Ralph Schackart with William Blair. Hey, hey, Matt. Adam, maybe just staying on that, the model unlock for a second.

Ralph Edward Schackart: Maybe kind of frame that. Was it sort of, like, consistent with other unlocks that you have seen before? Was it different, maybe an order of magnitude? And then, I am not sure if it is for you or Matt, but can you give us a sense, once self-serve rolls out and rolls out to GA, you know, how meaningful of an impact can this have on the business? Will this be a slow build? Could this be something, you know, that potentially be additive to half growth? Just any way you can kind of frame that for me, that would be great. Thanks.

Adam Foroughi: Yeah. I mean, on the second one, look. Our growth rates are really fast right now. Our business is really big. So taking a self-service platform and opening it up, I would not imagine day one or month one or month two is really going to move the needle on the overall numbers. It is going to build over time. Now certainly, if you are bringing in dollars that you just did not have before, it is going to add something. So I guess it depends on what our overall growth rates are. But the scale of the business and the growth rate that we have is getting to very, very large numbers quickly.

So I would expect that to build over time. I would not expect it to be immediately impactful as a major growth catalyst. It will be noticeable in our numbers. When it comes to improving the models, we do not call it out anymore. We are constantly improving the gaming models. It happens every single quarter that we find something. And then the e-commerce side is starting from a worse place. It is just earlier stage, less data like we have talked about. So the model uplifts from the team improving the model can be much more substantial. Last Q1, it was roughly 10% of our business.

However, the e-commerce business, as you know, even if you took disclosure from last Q1, if you improve 10% of your business for 40%, you are still only getting a 4% uplift on the whole. Right? So it is a much smaller potential today. Now what we know about scaling a business is that we have got to compound these gains so that our performance is unquestionably the best in the market to these customers. If they see that, they are going to invest more and more into us. Most of these customers have scaled businesses. Most of these customers already buy on social and search. We are a new entrant.

Most new entrants in the field over the last few years have done a bad job of proving performance. So we know that our performance has to be top notch. We are working towards that, and these types of lifts can compound to get us to that answer.

Ralph Edward Schackart: Right.

Matthew Thornton: Thank you. Yep.

Matthew Thornton: So—

Operator: Next, we will go to Martin Yang with OpCo.

Martin Yang: Hi. Thanks for taking my question.

James P. Callahan: In the past, you referenced expanding supply sources. Where do you rank—

Martin Yang: Among the growth drivers? Where do you rank that among the growth drivers for your overall performance now?

Adam Foroughi: I mean, look. Our supply is growing very quickly because MAX is growing very quickly. Right? So, like, I do fixate people on the marketplace that we have. It is a really large marketplace. If we go get a big publisher tomorrow, it is not going to move the needle in the business because the percentage growth from that publisher to the whole of our market is not all that much. I mean, you are talking about a marketplace. If you know the scale of our business and the ad dollars we gave you, and then we are not the whole market, the MAX marketplace is well over $10,000,000,000 a year.

There are not a lot of publishers that could put a dent in those overall numbers. We will eventually go out to new publishers. We get calls all the time. Every publisher wants a monetization platform like ours to help them monetize their business—unless they are Facebook, Google, or Amazon. And so there is a lot of opportunity out there for us to expand supply. But right now, we are focused on the demand side because that conversion rate can go up so much more than where it is today. We have got a lot of growth in front of us just by doing the demand generation well and improving our core models.

Martin Yang: Gotcha. A follow-up on the creative side. Do you view Axon for e-commerce—the creative format and the overall flow, with the end cards and your dev elements—as an area of differentiation?

Adam Foroughi: Yeah. I mean, like, our ads force attention. So it is a lot different than ads that people are used to. You would say the closest to our ads is television because you have got a 30-second clip. But as we know, most people are ADD and do not really watch the ad on TV these days. Our ads are over 30 seconds of engagement. The user cannot do anything else. They are already on their phone. It is a full-screen lockup. It gives the advertiser somewhere between 30 to 60 seconds plus to engage the consumer with their content. They cannot get an experience like that anywhere else.

So I would call, like, the starting point in our business in terms of ad quality the best that an advertiser can access anywhere in the world.

Martin Yang: Thank you.

Operator: We will take our next question from Vasily Karasyov with Cannonball.

Matthew Thornton: You for taking my question. Just to follow up,

Vasily Karasyov: On what you said earlier, Adam, about e-commerce model being at a stage where it cannot learn as fast now. And I think in the blog post you made recently, you mentioned that the e-commerce tag targeting is different because there are many more parameters and they are different. Right? There is a different LTV calculation. There is no advertising component. So I guess it is unfair to ask you to compare where the e-commerce model is at this point in its existence compared to where Axon 2 was. Right? Because there is not just enough data. But what gives you confidence that once you get enough data,

James P. Callahan: You—

Vasily Karasyov: It will work as well? Or comparable.

Adam Foroughi: I mean, look. If you talk to the customer base, a lot of the customers are seeing equal performance on us to any other top-of-funnel discovery channel, including the largest social platforms today. So it is not like we are starting behind trying to catch up. We are starting in a competitive place trying to become the best in the world. Now we are starting with very little data penetration. This is an important point. If you think about the gaming model, I made this point earlier. All the transactions in space—say all the IAP in the space, all the ad impressions in the space—our model sees the vast majority of everything in the world of mobile gaming today.

That allows our engineers to take that data and translate it into exceptional predictions on the other side. In e-commerce, we are starting with—I mean, the reports show thousands sites. Right? So we are starting with thousands of sites. A world where we can pixel 10,000,000 plus. We have a long way to go to get to the same data place in e-commerce as we are in gaming. Now good news is these models are exceptionally smart, and our team that is putting them together are exceptionally smart. So we do not need to have 100% market penetration or anything close to gaming to really make an impact. We are already proving it works with very little market data penetration.

Once that number starts growing quickly, you are going to start seeing this model just improving itself because it gets more data. And off of that incremental data, the same model is going to make better predictions, both for gaming and non, and that is really going to help catalyze growth in our business as we bring on advertisers. We think about every new advertiser as dollars, but just as importantly, data into the model.

Vasily Karasyov: So I guess it is more fair to say that what you have now in terms of the e-commerce model is already competitive. It is not like you are behind and need more—

Adam Foroughi: For sure. Yeah. I mean, like, we are not an e-commerce brand, but if you talk to them, if you talk to 10, at least five are going to tell you performance on our platform is really good.

Vasily Karasyov: Alright. Thank you. That is helpful.

James P. Callahan: Yep.

Operator: We will take our last question from Tim Nollen with SSR.

Bernard Jerome McTernan: Thanks. Hi, guys. Tail end of the discussion.

Tim Nollen: So just a few tidying up questions, actually. For Adam, first off, we are talking about e-commerce, all this conversation, but there are other sectors beyond e-commerce that you are servicing. Can you just clarify, you know, I guess e-commerce is by far the largest non-gaming sector, but what other sectors are you servicing, and how meaningful are they?

Adam Foroughi: Yeah. Look. The other sectors are still early. We started calling it e-commerce. I call it web advertising now. Anyone with a website, a transactional business model, should be able to work on our platform. However, we are much earlier in the model evolution for other businesses outside of e-comm.

Alec Reid Brondolo: Yep.

Tim Nollen: And then a couple bits for Matt, actually. You have done a great job bringing cost down quite a lot. A lot of that is SBC, I think. I guess the question is with such a high adjusted EBITDA margin, you seem very confident in maintaining that. You had a slight step up, I guess, sequentially in your R&D number in the cost lines in Q4. What do we need to know in terms of other cost items that could rise? How much could they rise in the coming, you know, several periods, not just Q1? And then last question is regarding cash. You have got now $2,800,000,000 of cash with $3,500,000,000 of debt on your balance sheet.

Just wondering what your capital structure thoughts and your use of cash priorities would be from here.

James Heaney: Yeah. In terms of the margin, I mean, we feel very confident in the margin level that we are at today. The kind of X factors that could potentially change that in the near term or in the short term would be potentially performance marketing that we were talking about before. So to the extent that we see really great performance, you know, with some of the tests that we are running, and we scale those up pretty significantly, we could see kind of a shorter-term impact in margin. Obviously, we are going to be doing that in the way that we spend, generally speaking, which is, you know, very disciplined. And then, obviously, looking at the returns.

So we will run, you know, return-based campaigns. So we will get the spend back in a relatively short period of time. Adam mentioned 30-day return from those. So, you know, overall, that is why we can, you know, feel so confident in the overall margin level that, you know, it should not change materially from here. And, you know, then in terms of use of cash, obviously, you know, our first priority is spending on the organic growth initiatives. So that is ensuring that we are continuing to retain our talent, you know, compensating people very well, hiring, you know, to continue to support our growth initiatives—e-commerce and our engineering team, etc.

But that really has not moved the needle, obviously, in terms of the cash and the cash balance growing. So then it is really what do we do with the cash after that, and we have been very active, you know, with our repurchase program, and we continue to plan to be.

James P. Callahan: Okay.

Tim Nollen: I am going to write it 60 minutes exactly. So good timing. Thanks.

Alec Reid Brondolo: Perfect. Thank you.

Operator: And that concludes the question and answer session for this quarter. We thank you all for joining us today. Have a good afternoon.

Adam Foroughi: Thanks, everyone.

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