A retailer, well established in Belgium and other European countries, is specialized in the selling of clothes through two main channels : physical stores and mail order. In order to optimize their recruitment campaigns performed via direct mail, they frequently use the services of Bisnode to score the Belgian population based on their resemblance to the retailer's core customer profile. This scoring allows to contact only the people potentially interested in the products, and leads to a high response rate of their DM campaigns.
By analyzing the profile of the customers of the company, a predictive model was generated to find among the Belgian population the most similar profiles to the customer database. As several segments exist in the customer’s business (shops and mail order) different profiles were found, and thus two models were created.
At every recruitment campaign, the predictive model is applied on the Belgian population. Every individual is scored with the likelihood to be interested in the product at that given time and the best prospects are then selected and contacted.