Cluster a Mid-Market SaaS Customer Base for Account-Tier Re-segmentation
Overview
What this challenge is about.
Pull 12 months of usage signals from the warehouse: feature adoption depth, session frequency, integration counts, ticket volume, NPS (Net Promoter Score), seat utilization. Standardize features and run K-means, hierarchical, and HDBSCAN clustering. Compare cluster stability across algorithms and choose 4-6 clusters defensibly. Validate with 4 CS leads via a workshop: do the clusters match their lived experience? Iterate once. Deliver a clustering notebook, a 10-page re-segmentation memo with playbook implications per cluster, and a quarterly cluster-drift monitoring plan.
The Brief
What you'll do, and what you'll demonstrate.
Re-segment 3,400 accounts into 4-6 usage-based clusters validated with CS leads, with differentiated playbook implications and a drift-monitoring plan.
Earning criteria — what you'll demonstrate
- Engineer features from real product-usage data, not synthetic vectors
- Compare clustering algorithms on cluster stability, not just silhouette
- Validate clusters against domain-expert intuition without anchoring on it
- Plan for drift monitoring before clusters go stale in production
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.
Product Manager
Product managers who can co-own segmentation decisions stop relying on contract size as a proxy for everything.
This challenge sharpens
- data-storytelling
- stakeholder-communication
- clustering