Segmentation of customer's behavior
From a dataset of items sold to customers, we are asked to segment customer's behaviors in order to be able to set up a classifier and then be able to classify as soon as possible, what we be the behavior of a new customer.As a first step, a clustering of articles was done in order to be able to then make a Bag of Words articles. Then using various aggregations to have additional features (purchase frequencies, average bill price, time since the last purchase, ...) a new dataset per customer was set up. Starting from this new dataset, a second clustering was set up to segment the clients. After an analysis of clusters and related behaviors, a classifier was put in place to predict which category a client could be.