A data-driven customer segmentation project using hierarchical (Ward.D2) and k-means clustering on retail survey data. The analysis applies z-score normalization, Euclidean distance and cluster validation (NbClust) to identify four distinct segments and translate insights into strategic targeting recommendations using the McKinsey GE Matrix.
-
Updated
Dec 31, 2025