Unsupervised clustering techniques enable us to detect the most granular distinctions between customer groups. Such algorithmic method is in need of a bag of features that are decisive for a difference in customer behavior. For this reason, we make sure the set is put together in close collaboration with the management. After the algorithm has worked its magic, the last task consists of giving the right explanation to each of the generated clusters.
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