Customer-Segmentation Study for a DTC Subscription Box
Overview
What this challenge is about.
Cluster 18 months of subscription data with k-means and HDBSCAN, then validate 4–6 segments. Deliver a notebook and playbook to earn your verifiable certificate.
The scenario
The Stockholm subscription-box company (around EUR 22M revenue, 38 percent first-box churn, 14 percent ARPU growth from upsells last year) needs sharper segmentation to improve both numbers — generic 'new vs returning' segmentation is wallpaper.
The Brief
What you'll do, and what you'll demonstrate.
Find 4-6 behaviorally coherent customer segments via unsupervised learning and produce a playbook with actions per segment.
Earning criteria — what you'll demonstrate
- Apply k-means and HDBSCAN to real behavioral data with proper feature engineering
- Validate cluster quality with statistical + qualitative checks
- Translate unsupervised-learning outputs into marketing-actionable segments
- Communicate ML findings to non-technical CMO audiences
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Machine Learning (CS Elective)
Master · General Studies
Strong alignment
This challenge maps to Machine Learning (CS Elective) at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Unsupervised Learning
Apply unsupervised learning to solve real industry problems and demonstrate production-level capability.
- Python Programming
Apply python programming to solve real industry problems and demonstrate production-level capability.
- Ml Applications
Apply ml applications to solve real industry problems and demonstrate production-level capability.
- Business Analytics
Apply business analytics to solve real industry problems and demonstrate production-level capability.
- Feature Engineering
Apply feature engineering to solve real industry problems and demonstrate production-level capability.
- Model Evaluation
Apply model evaluation to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Product Manager
Product managers who can read segmentation studies design lifecycle features that resonate per-segment instead of one-size-fits-all.
This challenge sharpens
- business-analytics
- ml-applications
- model-evaluation