clustering-and-segmentation

Group customers, products, stores, sessions or any records into segments, and pick the clustering method that fits the data and the business use. Use whenever someone wants to segment, cluster or group similar items, build personas or cohorts from behaviour, run k-means, hierarchical clustering, DBSCAN or Gaussian mixtures, choose the number of clusters, read an elbow plot, silhouette score or Calinski-Harabasz index, profile or name clusters, build an RFM segmentation, cluster mixed categorical and numeric data, or check whether segments someone else built are real. Not for reducing the number of columns before modelling, and not for predicting a label that already exists.