This project employs K-Means and the RFM model to segment customers in an online retail dataset. It involves data exploration, RFM attribute creation to understand customer behavior, and K-Means and hierarchical clustering techniques are employed to categorize customers into distinct clusters. The analysis offers insights for targeted marketing and customer engagement strategies.
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hetvimwaghela/online-retail-clustering
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Online Retail K-Means & Hierarchical Clustering
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