Understanding Applovin's Advertising Performance

We’re Spending $50,000/Day on AppLovin—Here’s What We’re Seeing. We’re currently scaling an e-commerce client on AppLovin, spending $50,000 per day, and the results are impressive. Here’s what’s happening and what you need to know about this untapped channel: Consistent ROAS, Even at Scale We’re seeing a consistent 2.5-3 ROAS on AppLovin. As we scale, we double the budget every 48-72 hours. Yes, there’s a temporary dip in ROAS for 24-48 hours, but that’s normal. The performance corrects itself and stabilizes. Cross-Channel Lift One of the most exciting effects is the massive cross-channel lift we’re seeing on organic search and Google paid ads. We measure this using northbeam, and the data shows a clear correlation: scaling AppLovin boosts visibility and performance across other channels. Why This Lift Happens AppLovin runs ads on many Google-owned apps, which seems to feed valuable retargeting data back into Google’s ecosystem. This synergy between platforms amplifies overall results. 78% New Customer Rate AppLovin is helping us reach an untapped audience. About 78% of purchases are coming from new customers—people who aren’t active on Meta platforms but spend time on apps like games, tools, or hobbies. For example, my wife uses a drawing app and got hit with our ad. This proves we’re reaching people we couldn’t engage otherwise. Creative Strategy We’re finding that the same UGC creatives that perform on TikTok and Meta are working on AppLovin too. When combined with strong end cards that drive clicks, the engagement and conversions are incredible. Getting Started on AppLovin Right now, AppLovin is invite-only for brands spending $600,000+/month on Meta. If you meet this threshold, they’ll onboard you, provide ad credits, and manage the setup with weekly support. Self-serve is coming next year, so more brands will have access soon. Is It Worth It? Absolutely. AppLovin delivers consistent ROAS, drives a high new customer rate, and boosts performance across your marketing ecosystem. It’s not just an ad channel—it’s a growth driver for your entire business. If you’re thinking about AppLovin or have questions about scaling on this channel, let me know in the comments or send me a message.

The discourse around AppLovin is clearly polarizing. At Haus, we deal in data - here’s what we’ve seen from 35 incrementality tests run since November. First, how does holdout testing work?  - Divide the country into two statistically identical groups of markets. - One gets AppLovin spend; the other doesn’t. Everything else stays constant.  - Measure sales lift in geos where Applovin was running. The results: - 58% of tests delivered iROAS > $1. - 59% of incremental revenue came from new customers. - Efficiency was stronger at lower spend levels, but as you can see, more mixed at higher spend levels. The questions around how AppLovin drives performance — and if it can scale — remain open. And as expected, the story is not black and white (it almost never is), but marketers who run regular incrementality tests know that iROAS > $1 is rare, and worth paying attention to. Note: Chart includes only tests where iROAS was measured as a KPI

I spent the last 2 months testing Applovin (got some free credits). Real talk - first 10 days were dead. Then something clicked. Their AI finally dialed in the targeting and BAM 💥 Here's what I’ve learned so far → The setup is embarrassingly simple: • Dump in your video creative • No complex campaign structures • No testing frameworks • No scaling rules Feels like this is what advertising SHOULD be. Performance snapshot → shooting for 20X increase in spend • Started at $500/day • Scaled to $2k/day smoothly • Just hit $5k/day recently • Pushing past $6k/day • Target: $10k/day next week Currently 30% of our spend with 50% better efficiency vs Meta (for now). Creative approach is dead simple: • UGC content • Podcast-style clips • High production ads • Influencer content • No copy needed What we’ve done → just toss in any video content that works elsewhere. Your success formula: • Upload diverse video content • Let the AI learn (give it 10-14 days) • Kill underperformers • Replace with new content • Scale gradually No fancy tricks needed so far. Simple has worked for us. I’ve been managing $1M+ monthly ad spend for years. This is the most straightforward new channel I've tested in a while. Will keep you updated as we scale this further. BTW, if you want to get on Applovin, they’re only onboarding brands spending $20k a day or more on Meta for now…

💰 The trick to generating incrementality on AppLovin is creative testing. 💰 We have a business pushing a boutique subscription product that has spent $2.8 million YTD on Applovin ads. It's 25% of their mix, their second biggest spending channel. 86% of conversions are new customers. They're getting a better 1-day click ROAS than what they get on Facebook, where they're run ads for years - at half of the new visit percentage they get on FB. The first touch vs last click ratio is 93%, meaning most of their Applovin revenue is coming from first-touch and not relying on the help of other channels. They're capturing gamers that, although they likely have social media accounts, the business was unable to reach through other algorithms. For whatever reason, this audience was just not accessible via other platforms. After seeing this, the business hit Applovin in force, running aggressive creative tests featuring angles and hooks from other platforms. The result: extreme scale. The business was able to do this with the help of Northbeam. Check the chart: this is Applovin attributed one-day last-click revenue and Applovin spend for the brand YTD.

Since the release of AppLovin MMM Benchmarks - Part I, interest in the new channel has only intensified. Which is why I’m excited to release the second installment from Prescient AI visibility into trends around AppLovin —from Spend, Halo Effects, and BFCM recap to New Customers/CAC. A quick recap from insights and hypothesis extracted from the data: (1) Brands in the private beta continue to consistently spend a healthy average of ~10% of their weekly total budgets on AppLovin. Top brands have spent upwards of ~20%+ of their total mix. (2) ‘Halo Effects’ have substantially improved and are on pace with channels like Google and TikTok. Halo Effects were especially strong during the BFCM period, demonstrating further signs that AppLovin may be more than just a direct-response channel. (3) While AppLovin’s percentage share of the overall media mix dipped during BFCM in favor of core channels Meta, Google, and Amazon, gross dollar spend increased substantially with general budget increases. Efficiency remained strong and exhibited even more strength against Meta on average due to the increase in Halo Effects. (4) Rumored marketer concern around AppLovin retargeting old customers may have some merit in certain scenarios of rapid scaling and high spend. AppLovin MMM New Customers and CAC still appear efficient at specific levels of spend that are more in line with Google and Amazon’s share of the mix. Read on below for more details from the analysis.