Matt Stumpf, our CFO. Please note our SEC filings to date, as well as our financial data and press release discussing our third-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 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-Q for the fiscal quarter ended June 30th, 2026.

Additional information may also be found in our quarterly report on Form 10-Q for the fiscal quarter ended September 30th, 2026, 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 a 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 and transcript 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.

Thanks, everyone, for joining us today. We delivered a record quarter: revenue of $2.18 billion, up 55% year-over-year, the largest sequential dollar step-up in revenue with well over $200 million more than last quarter.

Both revenue and EBITDA came in well above the high end of our guidance. That's the standard we've always run this business by, outperforming our expectations.

That result belongs to our team. They're carrying out a model transition as significant as AXON 2.0 while running the business at full speed, and they delivered both in the same quarter.

I want to thank them. Here's what drove it.

During the quarter, we partially rolled out the next generation of our models, built on the architectural changes I described last quarter. Performance was strong.

Advertisers saw more spend deploying profitably at their target return on ad spend goals, and budgets stepped up. Our gaming business grew nearly 50% year-over-year, reaccelerating right alongside the rollout.

Here's the part I want you to sit with. This was a partial rollout.

The transition is still in front of us, and the new generation gives us meaningfully more room to optimize than the architecture it replaces. It also improves performance most where data is sparser: newer advertisers, smaller advertisers, newer categories, exactly where our consumer vertical lives.

As always, model gains won't land on a perfect quarterly schedule, and we won't promise a cadence, but the headroom is real, and we're still very early. Just as important, we did it with discipline.

While part of the team trained the new models, our engineers optimized how we serve them, even as training investment increased, data center costs declined as a percentage of revenue. Every dollar of this investment is gated on return, and this quarter, you saw both halves of that: the return in revenue and the discipline in margin.

Consumer had another strong quarter, and with Q4 now underway, the seasonal peak for these advertisers, consumer is set up very well heading into the biggest spending season of the year. On the long term, nothing has changed.

We run one auction across multiple advertiser categories. Gaming keeps improving, consumer keeps adding runway, and we believe this business can compound at roughly 30% annually over the long term.

As this year shows, we intend to run well ahead of that whenever we can. Our focus heading into next year is consistent: complete the model transition and optimize on top of it; expand spend from our current customers while really ramping up the rate of acquiring new customers; keep improving our creative tools and ad formats; and start expanding our efforts on CTV.

Let me close with this. A quarter ago, we stood here answering questions about a miss.

We told you what had happened, that it was fixed, and that the business was reaccelerating, and everything we told you showed up in this quarter's numbers. That's how we'll keep operating: build for the long term, be transparent about challenges and opportunities, and compound through the noise.

With that, I'll turn it over to Matt to walk through the financials.

Thanks, Adam. Thanks to everyone for joining us today.

AppLovin posted record third-quarter earnings. Net income grew 72% year-over-year to $1.44 billion on record revenue of $2.18 billion, up 55% year-over-year, with an industry-leading 66% net income margin and 84% adjusted EBITDA margin.

Revenue grew 14% sequentially and exceeded the high end of our guidance by approximately $100 million, primarily driven by the core mobile gaming business due to model improvements during the quarter, with continued scaling in the consumer vertical. Consumer advertisers spend continues to have healthy growth, with spend up double digits quarter-over-quarter and growing triple digits from the same quarter last year.

Adjusted EBITDA was $1.84 billion, up 59% year-over-year and also above the high end of our guidance range at an 84% margin, up approximately 190 basis points from the same period last year. Quarter-over-quarter flow-through to adjusted EBITDA was 87%.

Operating leverage remains strong. Our data center costs declined as a percentage of revenue due to optimizations rolled out by our infrastructure team, even as we invested in additional compute for training our existing models and for new model development.

We manage this business to EBITDA dollars and free cash flow rather than to a margin percentage, and will continue to deploy dollars when we see an opportunity to produce more revenue. Free cash flow for the quarter was $1.4 billion, or 77% of adjusted EBITDA, up from 53% in the second quarter.

As I mentioned on last quarter's call, second-quarter conversion was depressed by the timing of cash tax payments. We still expect full-year free cash flow conversion of roughly 70% to 75% of adjusted EBITDA.

To put our results in context, this earnings season, the largest platforms in digital advertising reported third-quarter revenue growth between roughly 10% and the mid-20s year-over-year. We grew 55%, several times faster than the market, and we did it at margins well above all of our peers across the advertising space.

The contrast is even sharper on cash. This quarter, our asset-light model converted roughly 65% of revenue into free cash flow.

We ended the quarter with $3.17 billion of cash against $3.5 billion of long-term debt, which puts net leverage below 0.1 times adjusted EBITDA, comfortably below the roughly 1 times net leverage where we'd expect to operate over the long term. During the third quarter, we repurchased and withheld a total of 4.1 million shares for $1.4 billion, a meaningful step-up from the second quarter, and ended the quarter with 331 million shares outstanding.

Given our continued confidence in the company's future, our board of directors increased our share repurchase authorization by an incremental $3.2 billion, bringing our total current authorization to $3.6 billion as of the end of October. Since we began the program, we have repurchased and withheld a total of 104 million shares for $9.4 billion at an average price of $90 per share, returning 85% of our free cash flow over that period and reducing our share count materially.

Our weighted average diluted share count has now declined for eight consecutive quarters and is down approximately 2% from a year ago, even as we invest in the business. That combination, 55% growth with a shrinking share count, is one very few companies can match.

Turning to our outlook for the fourth quarter of 2026, we expect revenue between $2.365 billion and $2.395 billion, representing approximately 43% to 44% year-over-year growth, or 8% to 10% sequentially. We expect adjusted EBITDA between $1.995 billion and $2.025 billion, representing approximately 43% to 45% year-over-year growth.

At the midpoint, this guidance implies full-year 2026 revenue and adjusted EBITDA growth of more than 50%. That outlook reflects normal seasonality, further scaling in our consumer vertical, significant model improvements that are already live and performing, and continued investment in training compute for new model development.

To close, we exceeded the high end of our guidance on both revenue and adjusted EBITDA, grew revenue 55% year-over-year, expanded margins, generated $1.4 billion of free cash flow, and returned $1.4 billion to shareholders. Our fourth-quarter outlook reflects that same trajectory.

With that, let's move to Q&A.

Great. Just a couple for me.

I'll start with Adam. Could you just talk about these new generations of models that you're rolling out?

Just curious what the biggest improvement that you see is compared to AXON 2, and then anything around just timing of the full rollout, and then I'll ask one to Matt.

Hey, James. We talked about it last quarter, but one of our objectives was try to get to a place where we could build bigger models, use more compute, and try to train a model that has better output.

I foreshadowed it for you last quarter. We're now starting to roll those out.

We've seen good results. We can't tell you or commit to when we can actually see a full rollout or how the progression of these models will go, but what I said in the talk track is these models have a lot more room to optimize them than the old generation that we were on, we're really excited about the future.

Great. Then one for Matt.

Just on the surface, it feels like the Q4 revenue guide of the 8% to 10% sequential growth seems a bit more conservative versus the 14% in Q3 when you layer in the strength of e-commerce in the quarter for Q4. Just how would you frame up that sequential deceleration?

Our guidance philosophy remains the same from what we've done over the past few quarters. We're guiding to what we know at that point in time, we're guiding to include the points that I said in my script, which are normal seasonality within the quarter, the model updates that we've already launched and are live and performing, and then obviously the increase in the data center costs, nothing there has really changed from previous quarters.

Thank you.

Mhm.

One question. I think last quarter, you guys talked about leaning into the referral program a bit more.

I was just wondering if you could give us an update on whether you're pleased or not with the progress you're making with those partners. Thanks.

Hey, Jason. Still work in progress.

Obviously, this is going to be multi-quarter, multi-year trajectory on this business. We're early in doing partnerships, but as you've seen, even in the rate of pixel counts, I think, you're publishing is that we've been getting more and more customers coming on, and the rate is accelerating.

That's only going to compound over time, because not only you're going to have more partnership deals, we'll start running more ad campaigns, but you're just going to have more positive sentiment on the product in the market as more customers start getting a good experience and doing it over time. Because the other thing you got to realize is we got customers that come on, they have to get campaigns that are scaled and optimized on our platform, they have to run an incrementality study, they have to prove that it works, and then they really scale for the long term.

We expect this stuff will just keep compounding over time.

Thanks.

Great. Thanks for taking the question.

I guess does the experience that you've had with this new model that just rolled out, does that change your expectations for how much runway there still is ahead to improve gaming ad revenue? Because you've been relatively specific over the course of this year about a 20 30 20% to 30% growth expectation and sort of law of large numbers weighing on gaming.

Would you reiterate all that at this point or is there potentially more headroom than you would have otherwise expected based on how it's gone so far?

What we've been specific on the last two quarters that we're committed to is an expectation that we can grow this business 30% year-over-year for the long term. We are a platform that's a unified auction.

Let's say in some world, we grew consumer 1,000% the next quarter. That's going to create more competition, right?

You can't look at it verticalized. As this consumer business is now growing more and more, it's very hard to judge a vertical by itself in a silo.

Now, that said, this model is for sure more accurate than the old model, and it has a lot more room to optimize going forward. If we're able to do that, of course, we would expect that gaming could continue to grow at higher rates for the long term.

It's just not something that we need, though, in order to hit that 30%, if we have both parts of the business growing pretty quickly. As we touched on in the talk track, the other side of the business, the consumer side, is growing triple digits.

When you have a business like that that now isn't immaterial in our business, growing at that rate with a lot of opportunity to grow in the future as we go get more customer penetration, it gives us a lot of headroom on future growth opportunity.

Got it. Thank you.

Then I noticed you mentioned CTV in the prepared remarks. I think it's been a little while since that's something you chose to highlight.

I guess how prominently does that feature into your product roadmap right now relative to 6 months ago?

We're making more progress there. If people watch anything on connected television, you'll start seeing some of our ads.

We've got pilot campaigns going now. The product is actually looking very promising.

It's early. It's a whole new market.

I wouldn't bank on it at all for being accretive to numbers in anytime soon, but it's something that the team is actually gaining a lot of confidence in with where they're at in the product roadmap. If it gets to the point where it actually starts showing really good results for customers, we'll talk about it more.

Internally, we're now very excited about it.

Great. Thank you.

Great. Thank you for taking my questions.

Adam, you've spoken in the past the need to collect more data on the consumer side to refine the model and to improve performance, and then the flywheel around that. Now with the new architecture, do you have sort of line of sight to potentially getting the flywheel to reach a sort of a tipping point to where you were with gaming a few years back?

If not, which incremental investments do you think are required?

Now, look, these two things go hand in hand, right? Every day that we stay in business, we get customers that come into the platform, they share data with us, we get more data density.

As you fast-forward that quarters, years, you then need to pair it with model architecture that can actually process more data and generate better output. You write a bigger model, more complex model, you train it on a larger compute cluster, and you end up with better output.

What this new architecture allows us to do, on the gaming side and on the consumer side, is just train bigger models. We're going to be starved for data.

The more data we get into the system quicker, the better the output of our predictions model is going to become. We're never going to stop looking to go get data, whether it's promoting ourselves through referrals and advertising, as we just touched on for new customers, or potentially some sort of data acquisition, we're going to be looking for ways to get data into this model, because we've seen every single time we add more data, we're able to write a more complex model, we're able to train a bigger model, and just get a better output on the other side.

Great. I guess, how are consumer advertiser budgets shaping up for the holiday shopping season relative to last year?

If you think advertisers see strong returns this quarter, how much of that spend could ultimately prove sticky into '27, or should we expect sort of a seasonal reset as usual in Q1?

I think it just follows the normal patterns. Look, we're still early in the curve.

It's not even into the holiday season, so that stuff takes form really over the next couple weeks. That seasonal reset, that's consistent in e-com now.

We do have the benefit that so long as we're growing this business at this rate and we're pretty early in its evolution, we still have rate of customer acquisition allowing us to grow the business even in more traditionally seasonally difficult quarters like the Q1 versus Q4 comp. That said, the same advertiser, like for like, will have a huge Q4 and follow it up with a weak Q1.

That's just the reality of the e-commerce business. If you looked at the business growth sequentially in our business, our Q1s have been pretty strong because gaming has a phenomenon called Q5, where going into Q1, they know that there's not as much competition.

The models, whether just selecting gaming more often because return on ad spend is compelling or the customers being willing to take bigger risks because they're coming off of a very high-priced Q4 into this post-Q4 season, they end up spending very competitively. We've been more insulated than other advertising companies, but as we get more deep into e-commerce, we should see bigger Q4s followed by tougher Q1s.

Great. Thank you very much.

Hey, thanks. Hi, Adam.

Hi, Matt. Thanks for taking the time.

I think I was talking to some of the advertisers on your platform, and they said something curious. They were anticipating that the pricing on the auction is going to start getting inflated because you're going to have incremental bidders from e-commerce coming in and taking up the prices, they were preemptively taking some of the budgets to some of your competitors in anticipation of what might be compression of ROI.

Which kind of seemed like a strange thing to do, but it did make me worry about, I guess, the amount of inventory, which I think you've addressed in prior periods of this being, I guess, a demand-constrained industry as opposed to supply-constrained industry. Can you talk about how your thinking might have evolved, or things have changed at all in terms of AppLovin's ability to absorb all this incremental ad spend without having some of the ROI get compressed for some of your incumbent customers?

Thanks.

If you look at our business over the last 3 years, we've gone a lot more competitive. The business is much, much bigger.

The ROI, return on ad spend for customers, is stronger than it was 3 years ago because the spend is materially larger, right? The better these models get at taking an impression and predicting an outcome, the more accurate they can price.

Our step-up this quarter in net revenue dollars against the last quarter, I don't know how much of our competition that's publicly reporting has in terms of scale to directly compare to that, but I think it's a lot of their annual reported revenue that we just put up in one quarter of growth. I think these industry checks tend to end up being flawed, because you're looking at a small subsegment of the ecosystem.

The customers that are taking time talking to you all probably aren't working that hard. The ones that are working hard and succeeding probably aren't talking to you all.

I would say we're pretty good indicator on the market, and our technology has proven to be great at getting better pricing for customers. That doesn't mean that just looking at a CPM, the price is not going up.

In fact, if we get better targeted so that our conversion rate goes up, the CPM will go up. The down-funnel effect of a better prediction is that the return on ad spend is going up, and that's why we're able to grow so quickly.

Thank you.

Hey, thank you for the opportunity to ask a question. Just wanted to ask a little bit more about the architecture.

Is that something as it becomes larger or allows for more data and the models get bigger, is that something that also becomes more generalizable? I know in the past, you've talked about keeping the consumer and the gaming models separate.

Is that something sort of where the models become sort of more generalizable across media types, across client types over time?

It's possible. Oh, sorry to interrupt on the second question, but you're right.

It is possible that we will eventually be able to take this architecture that direction.

Got it. Then just wanted to ask a little bit about maybe brand performance, if you will.

We're hearing from more brands, maybe because of the issues in mobile web, both in terms of inventory supply, but also iOS 26, focus more on mobile app inventory. Do you see that as an opportunity that's potentially attractive or interesting for AppLovin going forward?

Certainly if it's a performance marketer. I would split up performance brand into true performance where they're optimizing to incremental ROAS or a down-funnel purchase transaction.

Then you've got performance brand that still is looking for audience reach. A lot of the mobile web advertising and a lot of what's called, I guess, traditionally open web is more of the latter.

They're just trying to buy audience and trying to price effectively as cheap as possible to reach that audience. We try to price the discovery all the way to the point of transaction.

If that's what they care about and they're able to track it all on digital, then yes, we think a lot of those dollars will shift into the app space. It clearly performs really well.

It's much, much bigger. I said this, I think, on the All-In pod at the All-In Summit, the scale of this space is getting very, very large.

You can back into the gross spend numbers that we have, and they're pretty substantial. If you then gross that up for the whole space, this is one of the largest advertising opportunities that there are outside of social and search, maybe the largest outside of social and search.

We fully expect more dollars will follow, given the performance is there.

Great. Thank you.

Hey guys, good evening. I had two, if I may.

Just Adam, I sort of wanted to pull at this model thread. Based on everything that I understand about where you guys are going right now, I think one of the bigger derivative benefits of success would be opening up a lot more inventory or available inventory, I guess, within the same sort of base of games and supply that you have right now, which probably should get filled because of auction dynamics by non-gaming advertisers.

Is that right? I guess just sort of number one, as we think about the second-order benefits beyond just sort of more ads per 100 that you're buying right now translating to revenue-generating customers for e-commerce or gaming developer in and of itself, I guess is there a way to frame for us just how significant, I guess, this sort of available or effective supply expansion could be?

Yeah. Look, I think the challenge with supply expansion is that the MAX market or the gaming advertising market is a lot bigger than people realize.

When you've got this market that's in the tens of billions, we can go get new supply, and, in fact, this model that we're now on and that consumer vertical growing gives us a lot of opportunity to go get more supply. There aren't that many supply sources that are sort of open to third parties that could be a huge needle-mover in one shot.

Then you'd need to compound it over time. The reason CTV is compelling to us is there's not a true top-of-funnel to bottom-of-funnel performance offering on connected TV.

If we can figure that out and be the first to market with something that's scalable there, there's a lot of available inventory that's undermonetized there. It's sort of what mobile looked like to us 10, 15 years ago when we started the business.

Something like that could be impactful. Anything else, not so much.

That's why we've always talked about this conversion rate. We're still very low on what we think is the possible conversion rate inside this gaming ecosystem.

What consumer gives us is the chance to diversify the ads that someone's seeing. Instead of showing the same user 20 gaming ads in a week, we might show them 15 product ads and 5 gaming ads.

That doesn't mean that the gaming customers lost 75%. It just means that the model can get much more targeted so those same 5 impressions that would have driven the conversion are still going to sit there, and now all of a sudden, you have all these product ads.

That's really the focus area. That's the largest needle-mover in the short, medium term.

Long term, for sure, supply expansion is something that we're going to be focused on.

That makes sense. For Matt, I guess just sort of net of, what I think we were seeing just a moment ago in terms of after-hours share price reaction, your stock is still down ballpark 40% year-to-date, and it's only retraced, most of the sort of post-2Q earnings step-down.

Does the buyback give you flexibility, or the added authorization that you guys just layered on, give you flexibility to be more aggressive, I guess, and opportunistic, if you think that the share is or the share price is meaningfully disconnected from intrinsic value, or is this mostly going to be, programmatic going forward?

No, you saw within the quarter as well, Clark, that we did a meaningful step-up, and so that was directly as a result of what you're referring to, right? That was us opportunistically ramping up the buyback because we saw this dislocation in the stock price versus the actual intrinsic value of the company.

We have the ability to do that going forward as well.

Thank you, guys.

Yep.

Hi, thank you for taking my question. A question for Adam.

At an industry conference, you referenced that dynamic product ad for e-commerce sometimes can work better than video. Wanted to get your thoughts on the longer term.

Do you think a more diversified ad format is the ultimate goal to make e-commerce more effective, or are you still just waiting on gen AI video creation to make volume and quality of video ads higher, and this dynamic product ad is just an intermediate step for your advertisers to get volume in front of customers?

Look, I'd say it's both. As the large language models that are applied to creative continuously improve and there's a lot of companies in this ecosystem building ads now out of the box, you're going to see better advertiser performance.

We're also going to create more ad formats that can service advertisers in hopefully better ways. What we want is diversity of what the consumer sees.

When you serve as many ads a day as we do, that diversity of content can create an uplift. That's why in my talk track, that was one of the bullets.

It's an area of focus for us. This product is still really new.

I know we're a couple years in, but it's a really new product. The ad format hasn't evolved that much yet.

We fully expect it to evolve a lot more over the next couple of years.

Got it. A follow-up on e-com, if I may.

When you compare this year going into the holiday season versus last year, how would you say the learning budget or learning time is for e-com customers? How has that improved, if any?

Look, learning is two-sided. Our model has gotten better, and this new model architecture also, as I said in the talk track, is faster when there's less data.

On the other hand, customers are risk-averse going into a new relationship. When they buy on us, even if the result looks better, they still need to validate it.

In this category, if you talk to the customers, not only do they want to see spend and return on ad spend, they need to run incrementality studies too. There is a slow ramp-up, that's just a fact of the industry, but our product is getting better.

Every quarter that we go on and we have a new release, part of the space of getting it better is just improving it for current customers. The other space of getting it better is that so customer now clicks in, they don't have much data in our system, how quickly can we show them a good result, because that's how you lower your churn rates.

Thank you.

Thank you. Good afternoon, everybody.

A couple questions on consumer as well. Growing triple digits, obviously, good trajectory here.

Any commentary on sort of conversion of new leads coming through self-service or through your referral partners or any specifics on customer outcomes? I'm just kind of wondering, there was still a bit sort of hit-and-miss kind of depending on sophistication of the advertiser.

Are we still seeing sort of similar trends or anything you can comment on sort of how the go-to-market is progressing?

Look, we're still early in the product. If a customer goes through our team, much higher likelihood to succeed than they just go through self-service channel and they're on their own.

Now, if they go through self-service and they're on their own and they're sophisticated, they absolutely can have success. If they're a very small business, something that is just what you would classify as complete SMB, that's still further into the future for us.

There is a roadmap on this thing where the more data you get into the system, the more predictive you can be in the absence of data, and we're not at the point yet where somebody can just plug in tiny business selling jewelry, we've never seen them before, very little data, very little GMV, and it just plugs in and they go. But 5 years from now, if we've got a lot of scale of data and the model has time to get evolved to the point of 5 years from now, you're going to have much better outcomes across the board.

This is just a roadmap. We've got to build this product out over time to tackle every single circumstance.

It is working really well for the customers that we either handhold or that come in and are sophisticated.

Is ad creative still a primary barrier? That was a lot of the points of failure, a lot of things that weren't working.

It's kind of stalled out at the ad creative. Is that still kind of the primary sticking point?

If we kind of asked this question a year ago, did you expect the industry would be a little further ahead on gen AI tools by this point, 1 year ago? It seems like to me, at least, maybe things are a little bit slower than we would have thought.

Look, on the latter, the large language model companies in the West are focused on something else, and so you have less R&D outside of us on this problem, right? On the former, I wouldn't call it a barrier, but it is an opportunity cost or opportunity lost for customers that don't invest in creative.

If you talk to customers that buy on Meta, they buy on TikTok, they buy on us, there's a constant point that they make that you need to put more creatives into AppLovin to have success on our platform. The ones that know that have more success than the ones that don't know that.

The ones that don't might be smaller. It's probably not a barrier to working at all, but they're missing a point of scale.

The challenge is that our ads are just much longer, and they are seen. When you go into another platform and you load 10 ads, they're not seen that long, and a lot of them aren't seen.

You load 10 ads into our platform, on average, you're getting over 35 seconds of watch time. User can't do anything else on the screen, it's a full-screen ad.

They are being seen with 100% certainty. Ad count and quality of ad combination is what creates scale in our platform.

Some customers know it, they're able to become our large spenders. The others have to learn it.

I'm going to try to sneak one more in. You're talking about significantly larger models, right?

Step function in scale. Are you generating enough data organically, you've got to feed the models, and you did talk a little bit, Adam, about maybe opportunities to acquire data.

I'm assuming you'd be looking for customer data, transaction data, but what types of data would be most helpful? Does it need to be evergreen?

Do you need it even? Are you generating enough organically?

Look, obviously this quarter, we had a fantastic quarter, best we've ever had, with the data that we had. There was no incremental data into the system, right?

There's, on the one hand, just processing the data you have available to you in smarter ways can create uplifts. On the other hand, these models just need more data.

That's consistent across any company in a modeling space. Getting more data into the system is important for us.

We're not rushed. The business is doing really well.

Every customer we get live is a data relationship on top of a business revenue relationship. Long term, if we can add ways to get data into our system quicker, the business is going to have much more runway in the short term.

Thanks, guys.

Thanks, Rob.

Hey, thank you for taking my question. I have a high-level question.

Some of my questions were asked. As an ad tech company, for investors who are questioning the visibility of your business model and how much confidence you have in the durability of your top-line growth, is there something else incremental that you would consider sharing that would give more confidence in terms of the way your product works, the visibility you can offer, and the moat that you're building?

Thank you.

Look, I think over the last, I don't know, it's been 16 quarters or something, we've had 15 phenomenal quarters. Our growth rate has been higher than almost any tech company in the world that's public at the scale that we operate at, and our margins are probably second to none.

You've got a business that while is unpredictable in the future and we can't really give KPIs to predict something that isn't there, a lot of it is tied to actually us being able to improve our technology. Then a lot of it's tied to new customer growth.

We're so early in that consumer segment that there's nothing that's material there yet that can be predictive into the future. You sort of have to make your own guesses.

I said this, I think, I don't know, maybe 12 quarters ago, early in AXON 2, I said when human beings tend to think about predicting something, everyone gets negative on the future. In our business, they can be negative and positive, but almost all those quarters, I think it's been 14 out of 16 that we've beaten the high end of our guidance, and not by an immaterial amount.

We've been consistently outperforming what anyone would have expected. I think a lot of this is over time.

People have to go, this is a bigger ad tech company that's sort of independent ad tech without a first-party site, bigger than anything we've ever seen before. We're a very large business at this point.

We create a lot of cash flow, and we're delivering to our customers in a very large amount of scale, return on ad spend, tens of billions of dollars of revenue on the other side of the ad spend that they put into our platform in any given year. We're a very large economic force at this point.

That ad spend is creating GDP, it's creating new transactions that otherwise wouldn't have been there. As a very large business, we're growing quickly.

We can't give those KPIs that you're looking for, because we're just not at that point of stability. We have something that is a catalyst that is also very valuable.

Our engineers improving our models and more data into the system is not predictable, but it can create very high upside.

That's fair. That's helpful.

Thanks, Adam.

Yeah.

Adam and Matt, Adam, in the talk track, you talked about or referenced this model step change is as big as AXON 2.0, I think you said. I'm just curious, is it fair to think of this as a AXON 3.0?

Just really trying to frame this model update, because when the model transition to AXON 2.0, you had a fairly significant inflection point. Obviously, the business a lot larger now.

Just if you could help conceptualize how impactful this new model will be once it's fully rolled out, and the impact on the business would be great. Thanks a lot.

I'd put it from a technology standpoint in terms of technical complexity on that level. In terms of business, look, this is the next generation of the model.

We're not a direct-to-consumer AI company, and so we don't increment the model. The reality is this gives us a lot bigger path in the future in terms of processing more data and spinning up bigger clusters and hopefully getting better output.

Team's really excited about what it means. We're still in partial rollout, it has to roll through all of our models.

There's still a lot of complex R&D work there. It gives us a much longer roadmap than the old models would have given us, so that gets the team really excited.

Great. One follow-up.

Obviously, the results tonight speak for themselves, but after last quarter, there was a ton of competitive concern. Maybe just give us an update on the market and the competition as you see it today.

Thank you.

Look, the industry checks out there show you all. Other companies are performing really well in the market.

We've said since we went public, this is not zero-sum. Our prediction, the impression, what we price for a customer is going to be different than any other model.

What makes this category great is that the sum total of all the models improving give these customers better businesses. It's never been the case that other companies growing should squeeze us.

I said it on the last earnings call, that was not something that actually happened, and it was our own foot-fault. That now shows true to you all in the face of other companies doing well, and it's not just one, it's multiple, all at the same time.

We put up a massive quarter.

Awesome. Thanks, Adam.

Thanks, Matt.

Yep.

Hey, thanks, guys, for taking the questions. I guess, just really curious, Adam, you had mentioned at the All-In Summit, I believe that gross spend flowing through AppLovin's ecosystem was approaching maybe $20 billion annualized.

Can you just talk about going forward in order to achieve that 30% long-term growth algorithm overall, how much of that growth will be from greater ROAS achievements through this new model versus incrementally adding new customers both on the gaming and consumer side? Then I guess, Matt, more near term, obviously good to see that outperformance in 3Q.

Implied 8% to 10% sequential, totally appreciate greater consumer seasonality into year-end, but just curious what's embedded there from a gaming perspective as you continue to roll out the new model? Thank you.

Look, long-term growth for us, the components of are hard to predict. Of course, new customers coming on is now going to be a component.

Not in gaming, we have every mobile gaming company live probably, but in consumer, we're really early. The data in the system will improve.

The model architecture now gives us a long runway to improve it. We don't know.

It's also interesting that every quarter can be different. If you verticalize the business, we could have a lift on the gaming side that doesn't apply to the consumer side, and that takes off one quarter, and then next quarter, it flips.

What gets us really excited is that consumer is growing very quickly and is starting to become more and more a part of our business. That on its own has much longer runway because we're so lightly penetrated into the market of customers.

As each quarter goes on, more customers find out about us, that business is going to grow really quickly.

On the guide, Brian, we don't break out obviously between gaming and consumer, and I won't give you the specific splits. What we've assumed for gaming and for consumer is consistent.

There's seasonality, right, as we look into Q4. Obviously, both are strong for different reasons.

You have the consumer period, right, of Black Friday, Cyber Monday, and then the holidays. You also have, on the gaming side of the business, there's seasonality as well, and Q4 is always strong.

We've assumed that within the guide, and then obviously the model improvements that we've had thus far, those are reflected in the 8% to 10% as well.

Great. Thank you both.

You're welcome.

Hey. Can you hear me?

Yeah. Thanks so much.

Appreciate the question. Maybe two for me.

I think first, you mentioned in response to a question about e-commerce or web advertising the idea of a data acquisition. I think that there's this kind of idea percolating that there could be tuck-in M&A leverage to kind of accelerate the capabilities in e-commerce.

Perhaps if you could talk about what the ideal acquisition candidate or what the ideal data you're looking for is, that would help people kind of frame that opportunity. Then secondly, you mentioned the pixel data, I guess it's fair game.

It seems like mostly the inflection in e-commerce customer growth is coming from APAC. Why do you think that region is finding kind of stronger product market fit first relative to the US and Europe?

Thanks.

I'm going to take second first. We've got sales teams on both North America, I guess EMEA as well, but APAC and the North America team are the two biggest.

We've always traditionally been focused on both those two markets, which are big ones on the Western advertising side. The APAC customers, because they're tapping into the Asian supply chain, a lot of times they spin up sites that are specific to certain type of products that aren't buying elsewhere.

For them, if they go spend $1,000 on us, they either make money or they lose money. It's very easy because there's no attribution complexity.

Sometimes those pixel sites are brand-new sites that just didn't exist, they're spun up specifically for our channel. North American customers are bigger enterprises.

They're not going to go spin up the next version of Wayfair, right? It's one domain.

I wouldn't read into the counts as, I'm seeing more pixel counts out of APAC, they're getting more penetration into the customer base over there. It might be just one is creating a lot because they don't have the same attribution complexity that some of the Western companies do because they're just longer-standing brands.

On the acquiring data point, the M&A that we did in the past that maybe is our best is when we bought MoPub. We were already succeeding with MAX.

It was a great product, and at the time, no one understood it. This crazy company bought a company and put it out of business.

We put it out of business in 90 days. We got all the customers over to our platform because we just build great products, and by doing that, we ended up with what MAX is today, which everyone knows is a really valuable business.

That transaction has paid for itself many times over now. What we would look for is, can we buy data relationships, customer relationships that are valuable for us?

We're going to get all these customers over the next decade anyways. If we can buy it and get the shot in the arm to bring all these customers onto our platform quickly and get all that data into our platform quickly, it'll accelerate this business to get through what could be a decade's worth of work in much shorter amount of time.

Same sort of structure as that kind of deal is what we would look for.

Thank you so much.

Thanks. Hi, Adam and Matt.

Thanks for taking my question.

Hey, Omar.

In your old models, you used to continuously retrain on live impression data, and that resulted in a steady 3% to 5% self-learning growth, and that's distinct from engineer-directed model uplifts. You didn't address it specifically on the last conference call.

Can you tell us if you see that three that same 3% to 5% tailwind from self-learning and intra-quarter model retraining off of live impression data? Did you see it in Q3?

Is it assumed in your Q4 guidance? Kind of looking forward, how much visibility do you have as to that component of growth, or are you just wholly reliant on engineer-directed model enhancements going forward?

Look, in all these models, you have this sort of reinforcement that happens. You get a prediction, you get data that comes into the system, and they get smarter.

That is true in any sort of category of companies that are writing deep learning models at this point. You don't actually know, is it 3%?

Is it 3.2%? Is it 4%?

You can't really track what the model is improving on its own, but there is always going to be this self-learning notion that exists in a company that's running a model, creating a prediction, reassessing its own prediction, and hopefully getting smarter as it goes forward. That's what these models are built to do, right?

They're structured similar to the human brain. We as humans learn from our memories and get smarter as we go forward.

These models do the same exact thing. I just wouldn't split it up into, this is a growth driver, let's plug this number in here, and then on top of it, let's put a model enhancement, because we talked about back in the day also, we'd have one big one a year.

Probably over the last 16 quarters, we've had multiple A/B test lifts pretty much every single one of those quarters except the last one, that contributed to very outsized growth for the business. This stuff's not all that predictable, nor is it able to be dissected down to a specific percentage, but it all compounds into the business that we have today.

Thank you.

Hey guys, thanks for the question. Adam, I think last year, you mentioned supply growth across MAX growing double digits.

Any comment on what that looks like this year or to 2027?

Look, it's still strong double digits. I think last quarter, we told you in a single quarter it grew double digits.

It's a very fast-growing space in the advertising ecosystem, where I think most ad spaces in terms of just supply growth and value of that supply aren't growing all that fast, probably very low double digits to possibly single digits. This MAX market is growing a very strong double-digit growth rate every year.

Great. Then anything on the cost of supply acquisition?

We've kind of heard this come up in checks a little bit that the cost of impressions broadly has gone up. Any way to frame how that looks today and kind of how that could look into next year as well?

Look, there's two drivers to MAX growth: more supply and the cost going up. Cost effectively companies getting better at monetizing the impressions, the value of the auction goes up, the publisher makes more.

Now, on the other side of that, we're either going to have to pay out more for publisher inventory or improve our own technology at that same rate, or improve our own technology more than that rate to grow our business even faster than that market. A lot of the innovation that we've had over the last 4 years has been the latter.

We've been improving our technology better than the market, and therefore our business is growing much faster than the market's growing.

Thank you. Adam, I wanted to ask you to comment on the take rate directionally maybe compared to last quarter and maybe year-on-year, whatever is easier.

Then the question I had with these models, separate models for consumer and gaming, would there be a reason why the take rate fluctuation on one would be greater than the other? Can you help us frame it for us, how to think about it?

Look, we don't talk about take rate in the business, and frankly, it happens after the fact. When you have a conversion rate that's a little bit over 1%, if we were buying on 1,000 impressions, somewhere around 987 of them we're losing money on.

Just there's no take rate, we lost everything. On the other ones, you have almost an infinite take rate because you're making ton of revenue with a very small amount of outlay.

It's just not a function that we optimize to, and it really does tie to the point that I made earlier. If our engineers created a massive uplift in the next 2 weeks, we'd be able to take more because we out-innovated to everyone else in the market.

If we innovate at the rate of the market, the market pricing stays consistent, we're sort of where we always are, which is pretty consistent. Then if we fall way behind, we just disappear for 5 years, our take rate will contract because the market pricing will get better than the rate of improvement on our technology.

Now, what you've seen with our team and the opportunity that we put in front of us with these different business lines and where we are in them is that we're really good at executing. We've been able to execute better than others in the ecosystem for a very long amount of time now.

Our team is very seasoned on improving these technologies, and when they have R&D breakthroughs like we just had, usually those end up being before everyone else. Before anyone else even understands how to have a technological breakthrough like that, we're many quarters or years ahead.

Is there something inherent to consumer versus gaming that would drive different...

It'll be consistently, again, similar. This is why I always say it's like one auction.

Let's say gaming has a predictive value of $20 CPM, 2 cents for the impression, and a consumer comes in and wins that impression at $21. It's so close to each other, you're paying out to the publisher, and if the model's very predictively accurate, you're not going to have one be at $50 and the other one be at $20.

They're pretty competitive to each other.

Makes sense. Thank you.

Mhm.

Thanks so much. I have a question about data, and it's about data provenance versus data processing.

Question is really who owns the data in your transactions? Is it your mediation platform that processes the data or is it the original game developer or the monetization platform that handled the transaction?

What data are you talking about? Just mediation data?

We have a lot of data in our system, I didn't follow exactly.

Yeah. The data originates through transactions, whoever processes them, but your mediation platform kind of creates these packages and you have this sort of new package data.

I guess my question is, who owns that data?

What is package data? If you just give me an example with an ad served, it'll help me answer it for you.

If an ad is served, and you process the transaction versus somebody else processes the transaction, you can see the data that is going through these transactions. You incorporate these data into your mediation platform.

I guess my question is, Does the data belong to the original game developer or ad tech company that processes the transaction, or through the mediation platform, do you gain provenance over that data? Does that make sense?

I think there's not really, because I think there's a disconnect on what you think we have access to in mediation. When we have a mediation auction run, there's every company bids into the auction.

To the MAX system, of course, we see all the bids. We don't know what people bid for.

The only data that's available to our AXON models or our system are did we win the ad or did we not win the ad? What was the price for the winning auction?

Then everyone who loses gets the price for the losing auction. That's it.

No one should have access to what other people serve. We don't have visibility into, an auction cleared, someone else won it, they served exactly X.

That exact X is the ownership of the advertising company, the company that wrote a model, that processed a ton of data, has a relationship with customers and consumers to show an advertisement, that's their data. It's an output of their models, that remains with them.

There's nothing that gives us magical data access from the mediation. In fact, when we built MAX, what we did was we commoditized it all.

We said everyone's going to have the same access to data as we will as a bidder into MAX, because what we wanted was a fair marketplace. The reason MAX outmonetizes the rest of the world of mobile gaming is because we made it fair, and that fairness is what drove the price of every single impression to be the highest possible.

That answers it. Thanks very much, Adam.

Did that answer your question?

Yes, I got it. Thank you.

Oh, great. Thanks for squeezing me in.

Congratulations on the quarter. I guess on the consumer side, Adam, you mentioned there's some hand-holding in terms of the initial on-ramp if you're not a more sophisticated customer.

I guess a two-parter there. One, how much of it is on you versus them in terms of improving that initial performance?

Is it still about the models, which is about them learning how to kind of better optimize their usage of the platform? Then secondarily, when you're kind of targeting customers, it seems like these real sophisticated users are the more likely to generate revenue immediately.

Is that more the priority, or are you looking for kind of the best long-term partners for AppLovin?

I think a lot of this is a learning curve. We're a new platform, a lot of these customers have not bought in games, they're not used to an ad that actually gets watched, and certainly not used to an ad that's watched for that much time.

If you have a shop, sometimes I think about we're asking the customer to create 60 seconds of content to showcase a shop. What are you even showing that ad?

It's like shops aren't that exciting. On the gaming side, they're creating minigames, someone's playing a preview of their game.

It's straightforward. There's a learning process here that has to happen so that the media buyers really understand the framework.

Then once they do and more and more media buyers understand it and more agencies are trained, then it'll become standardized. There'll be playbooks for our platform.

It's not dissimilar to buying on social 10 years ago. It was brand-new, the scale was way smaller, people didn't know what to do.

Now everyone knows what to do, because if you don't, you're probably not scaling your business. On the priority of the type of customers we go for, we are looking for the more sophisticated ones.

That's why these partnership deals make a lot of sense. Rather than just run AppLovin ads everywhere, through strategic partnership deals, we can get real customers coming on.

Thanks.