Authors: Sylvain Senecal; Pawel J. Kalczynski; Marc Fredette
Addresses: Department of Marketing, 3000 Cote Ste-Catherine, Montreal, Quebec H3T 2A7, Canada ' Information Systems and Decision Sciences, California State University, 800 N. State College Blvd., Fullerton, CA 92834-6848, USA ' Department of Management Sciences, 3000 Cote Ste-Catherine, Montreal, Quebec H3T 2A7, Canada
Abstract: This paper presents a model for identifying general goals of anonymous consumers visiting a retail website. When visiting a transactional website, consumers have various goals such as browsing or purchasing a particular product during their current visit. By predicting these goals early in the visit, online merchants could personalise their offer to better fulfil the needs of consumers. Most visitors remain anonymous to the website, however personalisation systems require demographic and transaction history data which is available only for registered and logged-on users. We propose a simple model which enables classifying anonymous visitors according to their goals after only a few clicks. The model is based solely on navigational patterns which can be automatically extracted from clickstream. Theoretical and managerial implications are presented.
Keywords: clickstream; consumer behaviour; e-commerce; electronic commerce; goals; anonymous visitors; personalisation; logistic regression; anonymous consumers; retail websites; navigation patterns.
International Journal of Electronic Business, 2014 Vol.11 No.3, pp.220 - 233
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 18 Jun 2014 *