HighlightsJournal 21 Paul Bowen March 26
In mobile gaming user acquisition, return on ad spend (ROAS) hasn’t always been the go-to metric for success. Before ROAS took centre stage, cost per install (CPI) was the primary focus, with advertisers optimizing for the lowest CPI possible without much thought to what happened post-install.
Then, as attribution improved, the industry shifted toward measuring D7 ROAS as a key performance indicator. This provided an early read on whether a cohort of installs would eventually break even. Over time, predictive lifetime value (LTV) models layered onto this, helping publishers refine their forecasts and ensure long-term profitability.
Now, in a post-Zero Interest-Rate Policy (ZIRP) world, CPI is making a comeback alongside ROAS as gaming companies sharpen their focus on efficiency and profitability. Let’s explore why.
Every mobile publisher operates under a simple equation:
LTV – CPI = Profit
The challenge? LTV isn’t static. It evolves as players engage, retain, and spend. Because of this profit varies and it’s worth asking whether mobile publishers should implement a maximum CPI (max CPI) as a safeguard.
If most of your projected LTV is tied to a small percentage of high-value players, your revenue model is fragile. If those whales disengage, your entire LTV assumption can collapse, turning a seemingly profitable cohort into an unprofitable one.
Think of it like investing. If you put all your money in Nvidia two years ago, you’d be up about 65%. But if you had diversified into the S&P 500, your return would be around 16%. While Nvidia outperformed, betting on a single stock is riskier than holding a balanced portfolio.
A max CPI functions the same way it prevents over-reliance on early, misleading data. Just because a cohort looks strong at D7 or D14 doesn’t mean it’ll hold up at D30, D60, or D180. A max CPI helps rein in reckless spending before it’s too late.
Multiplayer and social-driven games rely on network effects, where retention is closely tied to social engagement. Without a max CPI, you risk overpaying for a small subset of high-value users while neglecting the broader player base needed to sustain your game’s ecosystem.
A common misconception is that once a cohort reaches full recoupment (typically 1–2 years post-acquisition), CPI stops mattering. But that ignores risk management.
A max CPI works like an insurance policy. You don’t buy fire insurance to cover damage from a fire two years ago – you buy it to protect against future losses. Similarly, max CPI remains a safeguard throughout an install cohort’s lifecycle, ensuring advertisers account for market shifts, install quality variations, and changing player behaviours.
And let’s be clear: breaking even isn’t the goal. The goal is to drive sustainable profitability. A max CPI ensures financial stability over time, giving publishers more control over long-term margins.
Setting a strict max CPI can cap your ability to scale. In competitive markets, high-quality users come at a premium, and overly conservative CPI caps might throttle growth. The challenge is finding the right balance-controlling costs without suffocating acquisition.
Games that monetize primarily through in-app ads (IAA) don’t rely on whales as much as in-app purchase (IAP) games do. Since ad-based revenue is more predictable, CPI can often fluctuate more in IAP-driven games than in IAA games.
A rigid CPI cap can be counterproductive, especially during peak acquisition periods (e.g., holiday seasons), when competition drives up costs. A smarter approach is to adjust CPI dynamically, allowing flexibility based on market trends and campaign performance.
Max CPI is a powerful risk-management tool, but it’s not a one-size-fits-all solution. It prevents overexposure to volatile LTV assumptions and reckless spending, but it needs to be applied with flexibility. If you do decide to apply CPI caps, ensure you revisit these regularly, making data-driven adjustments to balance efficiency with growth.
CPI isn’t replacing ROAS – it’s becoming a crucial counterpart in a more balanced, sustainable UA strategy. The key is knowing when to optimize for each.
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