CUSTOMER SEGMENTATION / CLUSTERING

Effective customer segmentation using the recency, frequency, and monetary framework, combined with density-based clustering

Pairs an extended RFMI framework (Recency, Frequency, Monetary, Interpurchase) with density-based HDBSCAN on an H&M transaction dataset, recovering five interpretable customer segments plus a small noise group and improving segment fidelity on sparse, irregular retail data.