Pricing Experiment Framework
Built a repeatable A/B testing framework for pricing and packaging decisions.
Data AnalysisGrowthSystems Thinking
Problem
Pricing changes were being made on instinct with no structured way to test impact safely.
What I built
A standardised experiment framework covering design, sample size, and rollback rules.
My contribution
Designed the statistical approach and built the tooling that made experiments self-serve.
Process
Set guardrails
Defined minimum sample sizes and automatic rollback triggers.
Built tooling
Made it possible for others to launch a compliant experiment without a data scientist.
Outcome
Gave the leadership team a repeatable, low-risk way to test pricing changes instead of guessing.