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Using AI Techniques in the Grocery Industry: Identifying the Customers Most Likely to Defect

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Abstract:

The food retailing market has reached a mature stage where companies need to be competitive if they are to survive. Customers are ever more demanding and retailers need to design and introduce new ways of learning about their customers if they are to retain them (Leeflang & Van Raaij 1995). This article examines the efficiency of the LAMDA classifier (Learning Algorithm Machine for Data Analysis) (Aguado 1998; Aguado et al. 1999) in identifying customer's behaviour; specifically examining which customers are most likely to defect when a new retailer appears on the scene. The study carried out in this project is based on data gathered from a Spanish grocery chain: Supermercats Pujol, SA - 'Plus Fresc', winner of the 1998 Global Electronic Marketing Award, www.plusfresc.es

Keywords: Artificial Intelligence; customer behaviour; fuzzy logic; learning algorithm; retailing; segmentation

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/09593960410001678426

Affiliations: 1: Universitat Ramon Llull ESADE Business School Barcelona Spain 2: Universitat Politècnica de Catalunya Barcelona Spain

Publication date: July 1, 2004

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