A/B Testing Framework

RolePaid Media Strategy Lead

ChannelsMeta

Developed a controlled testing framework to evaluate messaging resonance and audience performance before a larger annual media investment.

This case study focuses on experimentation methodology, variable isolation, and the decision framework developed to reduce risk before scaling media investment.

Testing Objective & Planning Scope

Planning Area

Scope

Testing Horizon

4 Weeks

Isolated campaign flight designed for structured comparison

Testing Structure

2 Phases

Sequential message and audience evaluation

Campaign Architecture

Isolated Test Cells

Controlled setup designed to minimize audience and learning overlap

Context & Challenge

An emerging fintech app needed to determine which messages and audiences had the strongest potential to scale before committing a larger annual media investment.

The challenge was designing a test that produced clear, usable findings without allowing too many variables or campaign overlap to distort the results.

Strategic Approach

What Was Delivered

Execution-Ready Test Architecture

A two-phase campaign structure that translated the testing hypothesis into a clear setup for activation on Meta.

Message and Audience Test Matrix

A structured comparison of functional and lifestyle-led messaging across cold and first-party audience groups.

Controlled Measurement Framework

Defined variables, consistent campaign parameters, and evaluation criteria designed to improve the clarity of test findings.

Scale Decision Benchmarks

Clear criteria for determining which message and audience combinations should advance into larger media campaigns.

What I Bring

This work demonstrates my ability to design practical testing frameworks and translate findings into clear recommendations that guide future media investment. It also reflects how I work closely with clients to manage their budgets responsibly and validate growth opportunities through measured testing before committing larger investments.