Based on the supplied data we have analyzed active users of Baťa club according to their product preferences in order to find segments for targeted direct mailing campaigns. Generally, the following approaches have been combined:
RF(M) analysis which primarily segments club members based on their activity. This analysis is recommended for the following campaign as a starting point to distinguish the style of communication regarding the last shopping user interaction.
Basket analysis identifies links between purchasing a product X and Y. This analysis has not been carried out on products, but instead product groups. This method is useful primarily for product upsell in the form of recommendations.
Affinity analysis for products answers the question “what does a user typically buy?” The outcome of this analysis are segments which we recommend to communicate with RF segments and propose a suitable tempting offer matching their preferences.