Evaluate and Explain Retention Curves

Overview

User retention is the difference between thriving products and those that fade into obscurity. Yet 73% of product teams struggle to choose the right retention metrics, leading to misguided strategies and missed opportunities. This Short Course was created to help data analysis professionals master the critical distinction between retention measurement approaches and apply survival analysis to uncover actionable user insights. This course is unique because it bridges the gap between statistical theory and practical product analytics, providing hands-on experience with R-based survival analysis that you can immediately apply to real user datasets. To be successful in this project, you should have a background in basic data analysis and familiarity with statistical concepts.

Syllabus

Module 1: Retention Formula Differences - Foundation

In this module, learners will explore why choosing the right retention formula is vital for data analysis and product strategy. They’ll learn both formulas through examples, apply them in real-world scenarios, and see a hands-on demo using actual product analytics data.

Module 2: Kaplan-Meier Survival Analysis - Core Application

In this Module, learners will apply Kaplan-Meier survival analysis to evaluate user retention patterns over time, create survival plots in R with statistical testing to compare groups, and integrate analytical findings into experiment readouts that mirror real-world data analyst deliverables for stakeholder communication.