Abstract:

Customers are increasingly demanding, and successful companies need to design and introduce new ways to offer customer value. However, the process is not complete until they design control systems, provide a support decision tool able to identify and distinguish customer behaviour profiles according to their loyalty, and help marketers to readapt relationship marketing strategies in order to increase efficiency. LAMDA (Learning Algorithm Machine for Data Analysis), an artificial intelligence technique software tool enabling forecasting and identification of customer behaviour, is based on a self-learning classifying technique that relies on the generalizing power of Fuzzy Logic and the interpolation capability of logical hybrid connectives. This paper specifically examines the efficiency of the LAMDA classifier in identifying and distinguishing between the various degrees of customer loyalty. The study carried out in this project is based on data gathered from the customer loyalty cards of a Spanish grocer, Supermercats Pujol, S.A.