Analysis
Optimizing Subscription Pricing for a Lagos D2C Cosmetics Startup
Overview
What this challenge is about.
Your task is to analyze GlowCycle's customer data to identify segments with different price sensitivities and churn risks. Develop a predictive model to forecast churn probability for each segment. Then, using prescriptive analytics, propose a tiered pricing structure that balances retention and revenue. Success means delivering a data-driven pricing recommendation with projected impact on churn and LTV, supported by a clear optimization model.
The Brief
What you'll do, and what you'll demonstrate.
How should GlowCycle restructure its subscription pricing to reduce churn and increase customer lifetime value?
Earning criteria — what you'll demonstrate
- Apply predictive analytics to forecast customer churn
- Use prescriptive analytics to optimize pricing decisions
- Segment customers based on behavioral data
- Communicate data-driven recommendations to stakeholders
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career mappings coming soon.