This is a hands-on end-to-end Brazilian e-commerce use-case with detailed Exploratory Data Analysis (EDA) steps and business action items. We apply the RFM Segmentation and Customer Analysis to the Brazilian E-Commerce Public Dataset by Olist. It focuses on the lifetime value of customers, and it’s the preferred customer segmentation methodology for eCommerce businesses that focus on retention strategies more than on client acquisition.
K-means Clusters – Cohort Analysis applied to E-Commerce Understanding who your customers are and what they want is a fundamental part of any successful business. It can become increasingly challenging to create a one-size-fits-all customer profile. This is where the concept of cluster-based cohort analysis comes in.
AI-Powered Customer Churn Prediction Churn is a good indicator of growth potential. Churn rates track lost customers, and growth rates track new customers—comparing and analyzing both of these metrics tells you exactly how much your business is growing over time. In this project, we explored the churn rate in-depth and examined an example implementation of a ML/AI churn rate prediction system.