Data-Driven Meta Ads Overhaul

For several consumer-focused brands I manage, paid media is already running on Facebook and Instagram, yet the numbers show a clear gap in post-purchase engagement and repeat revenue. My priority is therefore customer retention, and I want every decision inside Ads Manager to ladder up to that single goal.

Here’s how I picture the collaboration:

1. Audit and Structure
We’ll open the account together, evaluate current campaigns, identify waste, and rebuild the architecture so budgets, audiences, and placements support a retention-first strategy. Expect interest-based segmentation to be the default lens, with room to test look-alikes or broad when data suggests.

2. Creative & Messaging Tests
I’ll provide brand guidelines; you’ll turn them into test matrices that isolate hooks, offers, and formats. Incrementality and statistical significance matter more than vanity metrics.

3. Optimization & Budget Allocation
Using real-time data, you’ll adjust bids, budgets, and exclusions daily, documenting every change so we can trace results back to actions. Meta Business Suite, Ads Manager, and any preferred analytics layer (GA4, Looker Studio, Power BI) are all fair game.

4. Reporting & Insights
A concise weekly report should translate ad performance into business language: CAC vs. LTV, retention cohort movement, and next actions. Numbers alone aren’t enough—I need recommendations that close the loop between acquisition and lifecycle marketing.

Acceptance criteria
• 30-day uplift in repeat purchase ROAS vs. current baseline
• Clearly annotated testing roadmap covering at least three variables per month
• Dashboard that auto-updates key retention metrics and flags anomalies

If your approach is experimental yet disciplined and you enjoy proving hypotheses with data, this project should be a great fit.