Analysis
Customer Churn Prediction for 40-Person SaaS Scale-Up
FreeVerified credential2 weeksIntermediate
Overview
What this challenge is about.
You receive a dataset with 500 customers and 10 features (e.g., monthly logins, number of support tickets, contract length, industry). Your task is to perform exploratory analysis, build a logistic regression model, evaluate its performance using AUC-ROC, and identify the top 3 churn drivers. Success means a model with AUC > 0.75 and actionable insights.
CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced
The Brief
What you'll do, and what you'll demonstrate.
Identify the most significant factors influencing customer churn and build a predictive model to flag at-risk customers.
Earning criteria — what you'll demonstrate
- Apply logistic regression for binary classification
- Interpret odds ratios and marginal effects
- Evaluate model performance using AUC-ROC and confusion matrix
- Perform feature selection using stepwise or Lasso
- Translate econometric results into business strategy
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.