Analyze Users & Optimize Product Retention
By External Provider
About this course
Transform your product analytics capability with advanced user segmentation and retention optimization techniques. This course empowers data analysts to move beyond surface-level metrics to uncover deep behavioral patterns that drive product success. By completing this course, you'll master the application of k-means clustering to identify distinct user segments and gain the analytical sophistication to evaluate rolling-cohort versus N-day retention methods for strategic decision-making. You'll learn to profile power users through RFM analysis, create compelling data narratives for stakeholders, and publish technical guidance that elevates your team's analytical capabilities. This course is unique because it bridges the gap between technical implementation and business impact, teaching you to transform raw user data into actionable product insights that directly influence retention and growth strategies. To be successful in this course, you should have experience with data analytics, basic understanding of machine learning concepts, and familiarity with Python or similar analytical tools.
What you will learn
- Clustering-based user segmentation uncovers behavior patterns for better personalization and targeting.
- Retention methods shape insights—choosing the right one ensures accurate product health assessment.
- Identifying power users enables better retention, feature design, and lifetime value growth.
- Clear communication and documentation turn technical analysis into actionable, team-wide impact.