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Dynamic identification of anonymous consumers' visit goals using clickstream

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.