Complete segmentation overview — key metrics, cluster insights, and business conclusions.
This project successfully applied K-Means clustering to the Mall Customers dataset to identify 5 distinct customer segments. The optimal K=5 was validated by both the Elbow Method (WCSS bend) and the Silhouette Score.
The segmentation reveals clear income-spending patterns: Target Customers (high income, high spending) are the most profitable segment, while Careful Spenders (high income, low spending) represent the largest untapped revenue opportunity.
The marketing recommendations generated from each cluster profile provide a data-driven roadmap for personalised customer engagement — from VIP loyalty programmes to social media campaigns.