AppLovin's Revenue Jumps 55% to $2.18 Billion on a New AI Ad Model

AppLovin turned $2.18 billion of third-quarter revenue into an 84% margin on adjusted earnings before interest, taxes, depreciation and amortization (EBITDA), and CEO Adam Foroughi credited a new generation of ad models on the company’s earnings call.

Foroughi told analysts that advertisers saw more of their spend deploy profitably at their target return on ad spend, and that budgets stepped up as the models went live. For an advertiser, the number to watch is the return on each added dollar, not the size of the budget.

What did the models do to the margin?

AppLovin’s data center costs fell as a share of revenue in the quarter, even as it bought more compute to train models, CFO Matt Stumpf said. The company held its margin while it spent more to build the next model.

AppLovin’s earnings release puts revenue at $2.185 billion, against $1.405 billion a year earlier, and it topped the high end of AppLovin’s guidance by about $100 million. Adjusted EBITDA came to $1.84 billion, up 59%. Mobile gaming, the core business, grew nearly 50% as the models rolled out.

How much of the gain is still ahead?

Foroughi would not commit to a date for the full rollout and said model gains will not land on a quarterly schedule. AppLovin has so far switched on only part of the new models.

Its fourth-quarter outlook counts only models already live. AppLovin expects revenue of $2.365 billion to $2.395 billion, which implies growth of about 8% to 10% from the third quarter, down from 14% in the third quarter.

Is the market growing as fast?

Stumpf put revenue growth at the largest ad platforms at roughly 10% to the mid-20s over the past year, against AppLovin’s 55%. Meta’s own third-quarter release shows revenue up 26% to $64.6 billion, which sits inside that range and gives the claim an outside check.

AppLovin’s consumer advertisers raised spend at triple-digit rates from a year earlier, Stumpf said. UBS analyst Stephen Ju asked whether the e-commerce bidders arriving in the auction would inflate prices and squeeze returns for existing advertisers. Foroughi answered that better targeting lifts conversion, which pushes up the price of each thousand impressions, and that return on ad spend rises along with it.

The test for an advertiser: did return on ad spend hold or rise on AppLovin as the price of each thousand impressions climbed?