CASE STUDY
PrecisionMkt — Scaling Revenue 3.2x While Cutting Cost-Per-Acquisition
3.2x
Revenue growth
38%
Lower CAC
4.6
ROAS
12mo
Engagement
01
The Challenge
What needed solving
PrecisionMkt was spending heavily on paid media with limited attribution. Different team members managed Meta, Google and TikTok in isolation, with no unified view of what was working. CAC was rising, revenue was flat, and the founder couldn't answer the basic question: "where should the next cedi go?"
02
The Strategy
How we approached it
We rebuilt the attribution layer first — implementing server-side conversion tracking via GA4 and Meta Conversions API, then unifying everything into a Looker Studio dashboard the founder could read at a glance. Only then did we touch the campaigns themselves. The principle: never optimize what you can't measure.
03
The Execution
Bringing it to life
Month 1 was instrumentation. Month 2 we ran controlled cohort tests on creative and audience hypotheses. Month 3 onwards we scaled the proven winners aggressively while killing the rest. Weekly bid and budget reallocation reviews; monthly creative refresh; quarterly strategy resets.
04
Engineering
Technologies & tools
Meta Ads Manager
Google Ads
GA4
Meta Conversions API
Looker Studio
custom Apps Script automation
05
The Outcome
Results achieved
Monthly revenue scaled 3.2x over 12 months. Customer acquisition cost reduced by 38%. ROAS improved from 1.8 to 4.6 on the primary channel. Marketing budget was reallocated 5 times during the engagement based on data — each reallocation produced measurable lift.
See the build
View the full project
Visit the project page for a deeper look at features and screenshots.
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