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Algorithmic customer segmentation

Get a detailed overview of the most granular clusters within your customer base
Customer segmentation is an often linearly performed effort: a single parameter such as frequency, price sensitivity or family composition defines the broad distinction between all of the customers. The strength of a well-constructed customer segmentation is however, that all the items than can explain the slightest difference in customer behavior are taken into account. That is where the data magic comes in.
How do we make it happen?

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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