The Challenge
Podz needed to increase installs while bringing CPI down. Early performance showed higher costs and limited volume.
The objective was steady scale with tighter cost control, without relying on short-term spikes.
Podz needed to increase installs while bringing CPI down. Early performance showed higher costs and limited volume.
The objective was steady scale with tighter cost control, without relying on short-term spikes.
We ran a simple operating system focused on repeatable inputs.
1) Weekly testing cadence
We set a consistent rhythm for testing creative angles, hooks, formats, and placements. One primary variable per test, clear success criteria, and fast decisions.
2) Creative refresh built into the plan
We produced and rotated new creative continuously to prevent fatigue. Winners were rebuilt into variations, then re-tested and scaled.
3) Budget discipline
Spend moved toward ads and ad sets that produced installs efficiently. Underperformers were paused quickly, and learnings fed directly into the next test cycle.
4) Reporting loop that drove production
Performance data informed what we made next. This kept creative output aligned with what was converting in-market.
$6,966.20 spent, 1,181 installs, $5.90 CPI
This was the baseline. The account was generating installs, but efficiency left limited room to scale. The priority was to identify which creative angles and delivery settings could lower CPI without reducing volume.
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$18,172.07 spent, 5,821 installs, $3.12 CPI
By September, spend had scaled and CPI fell at the same time. This was driven by a consistent testing cadence and a steady creative refresh cycle.
Winning themes were not left untouched.
They were rebuilt into variations and re-tested to extend performance. Underperformers were removed quickly so budget stayed concentrated on what produced installs efficiently.
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$24,721.06 spent, 11,596 installs, $2.13 CPI
By January, the campaign system was producing higher volume at a lower blended CPI.
The creative pipeline and reporting loop enabled ongoing improvements without relying on one-off spikes.
Budget allocation continued to favor proven ads and audiences, while new creative concepts were introduced to maintain momentum and avoid fatigue.
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Performance change from March 2025 to January 2026:
These results show two outcomes achieved at the same time: increased delivery and improved cost efficiency.
The improvement was sustained across multiple points in time, supported by repeatable execution rather than a single short-term lift.
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"These results were not luck. They came from a proven system: test, learn, iterate, repeat. Each cycle tightened performance and kept results consistent."
Podz performance improved because the inputs were consistent. The team ran a structured testing cadence, maintained ongoing creative iteration, and made budget decisions based on what drove installs efficiently.
Over time, this created compounding gains: stronger creative response, tighter delivery, and a lower blended CPI as scale increased.
This approach also made performance more manageable. Instead of reacting to fluctuations, the account operated with a predictable cycle: launch tests, measure results, scale what works, rebuild winners into new variants, and replace what slows down.
That system is what supported growth from 1,181 installs in March 2025 to 11,596 installs in January 2026, while reducing CPI from $5.90 to $2.13.
Want to scale acquisition without losing efficiency?
Strataigize builds repeatable paid growth systems using structured testing, creative iteration, and performance-led optimization.
Book a call with our team to map your next growth cycle.
To learn more, explore other app case studies here.