QUBRAZ — Intern (Customer Segmentation Analysis)
Performed customer segmentation by running K-means clustering on transactional datasets to derive labeled customer groups. Used clustering results to support downstream business decisioning such as retention targeting and revenue attribution. Translated analytical outputs into actionable recommendations for at-risk segments and lifetime value strategy. • Applied K-means clustering to identify 4 distinct customer segments. • Interpreted segment distributions (high value segment generating 52% of total revenue). • Produced churn reduction recommendations for segments identified as at risk. • Provided outputs intended for targeted retention investment decisions.