Customer Revenue and Cohort Analysis with Python

Understanding where your revenue comes from and how customers behave over time is critical for any growing business. This text-based course guides you through the core concepts of customer revenue analysis and cohort exploration using Python. You will learn how to clean raw transactional data, group customers into behavioral cohorts, and identify trends that drive business growth. By the end of this course, you will be able to apply modern Python libraries to analyze customer lifetime value and retention patterns. What you'll learn: Understand foundational customer metrics and revenue analysis terminology; Clean and transform raw transactional data using modern Python libraries; Build cohort tables to track customer retention and behavioral patterns over time; Visualize cohort analysis and revenue trends using standard Python plotting libraries; Apply basic machine learning concepts to model and predict customer lifetime value; Write clean, maintainable data analysis code using modern Python best practices. The course starts with essential definitions of customer metrics before moving into hands-on data manipulation, cohort construction, and predictive modeling. You will progress from raw data import to structured business insights through clear, written explanations and code examples. This course is designed for aspiring data analysts, business analysts, and beginners who want to learn practical data exploration techniques. No prior experience with cohort analysis is required. Start reading today to unlock actionable insights from your customer data.