CPI under $2. Manual targeting beat Meta's own algorithm.
Advantage+ is Meta's default. It was not the right choice for this app.
Meta Ads · Manual TargetingWhat was broken
CPI needed to stay under $2 to scale profitably
Above $2, the unit economics broke down. Campaigns would slow, budgets would shrink, and growth would stall. The target was non-negotiable.
Meta's Advantage+ was not hitting the target
The default automated setup cast too wide a net. Targeting was imprecise, creative testing was slow, and CPI stayed stubbornly above the threshold.
No repeatable framework for profitable scaling
Without a consistent method to acquire users at or below $2, increasing budget would only amplify the problem — not solve it.
What we did
Bypassed Advantage+ entirely
Launched with manual targeting from day one. Defined specific interests, demographics, and behaviours that matched the app's core user profile precisely.
Ran creative A/B tests in 48–72 hour cycles
Multiple ad variations ran simultaneously. Underperformers were paused within 72 hours. Budget moved immediately to what was working.
Reallocated budget to winning combinations
Audiences and creatives that consistently hit the CPI target received more spend. Those that did not were cut — no exceptions.
Weekly refinement without disrupting winners
New hooks, visuals, and formats tested weekly in isolated ad sets — protecting the performance of existing winners while continuously improving.
What we achieved
Maintained consistently — the target that unlocked scaling
By controlling targeting precisely and iterating creatives faster than the algorithm could, CPI stayed below $2 — making profitable scaling possible.
Creative test to decision
Faster creative cycles meant faster learning — and faster reallocation to what was working.
Precision outperformed automation
Advantage+ is built for broad reach. Manual targeting is built for precision. For an app with a specific user profile, precision wins.
Why it worked
- Manual targeting wins when you know your audience — Advantage+ works well for broad consumer products. For niche apps with a defined user profile, manual selection consistently outperforms it.
- Creative velocity is a competitive advantage — most advertisers test one or two creatives at a time. Testing multiple variations with 48-hour decision cycles compounds learning much faster.
- Budget follows performance, not schedule — moving spend to winners and cutting losers immediately — rather than waiting for a weekly review — significantly improves average CPI.
- The framework scales with budget — once a manual targeting structure is proven, increasing budget simply means applying the same precision to larger audiences. CPI stays stable.
Want results like this for your app?
Book a free strategy call. We will show you exactly what is holding your app back and what we would do about it.
Book a Free Strategy Call