Based on the Salesfact database perform various customer segmentation studies Including only continuous variables: customer segments are based on purchases of 3 main product families (food, drink and nonconsumables). What are the characteristics of customers in each segment?

Perform a profiling study on three categorical variables that are not included in clustering. That is how the clusters vary in different levels of these categorical variables such as gender or member card. Which data preprocessing tasks do you apply before applying clustering algorithms?

Do you need to scale (z-normalize) the data?

Solve the clustering problem with k-means, PAM, CLAA, a hierarchical agglomerative method and a density based method DBSCA Experiment with a few different number of clusters (k) and choose and appropriate k What is the effect of increasing k?

Apply the procedure fining number of clusters with PAM or CLARA, Interpret the resulting clusters and profiles comparing results of different algorithms. What marketing strategies could be developed on these clusters or customer segments.