Customer Segmentation and Clustering

Performed Exploratory Data Analysis (EDA) on an eCommerce transactions dataset to extract key business insights. • Developed a Lookalike Model to recommend similar customers based on profile and transaction history, using similarity scoring techniques. • Implemented Customer Segmentation using Clustering algorithms, optimizing the DB Index for better evaluation. • Visualized customer clusters and provided data-driven recommendations to enhance business strategy. • Built and documented clean, efficient code in Python for EDA, recommendation modeling, and clustering