User Segmentation, Experimentation, and Retention Analytics

About this course

You'll learn to analyze user behavior through advanced segmentation and retention techniques that directly impact business decisions. By completing this course, you'll gain the expertise to identify distinct user groups using clustering algorithms, design statistically valid A/B tests, and calculate retention metrics that guide product strategy. You'll benefit professionally by developing skills that make you invaluable to product teams and growth organizations. What makes this unique is the integration of unsupervised learning, experimental design, and survival analysis - combining technical data science skills with business-focused analytics. You'll work with real user data to create actionable insights that drive user engagement and optimize product performance across different acquisition channels.

What you will learn

• Apply k-means clustering to segment users and create actionable profiles that inform targeted marketing strategies and product decisions.
• Design A/B tests with proper power analysis and identify common biases that can invalidate experimental results and business insights.
• Calculate and compare N-day vs rolling retention metrics to evaluate user engagement and distinguish between seasonal and churn patterns.
• Build Kaplan-Meier survival curves to analyze retention across user groups and determine statistical significance of differences.