Skip to main content

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

Buy Article:

$55.00 plus tax (Refund Policy)

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
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

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

Document Type: Research Article

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

Publication date: 2004-07-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more