publication . Preprint . 2003

Predicting Online Purchasing Behavior

W.R BUCKINX; D. VAN DEN POEL;
Open Access
  • Published: 01 Sep 2003
Abstract
This empirical study investigates the contribution of different types of predictors to the purchasing behaviour at an online store. We use logit modelling to predict whether or not a purchase is made during the next visit to the website using both forward and backward variable-selection techniques, as well as Furnival and Wilson’s global score search algorithm to find the best subset of predictors. We contribute to the literature by using variables from four different categories in predicting online-purchasing behaviour: (1) general clickstream behaviour at the level of the visit, (2) more detailed clickstream information, (3) customer demographics, and (4) hist...
Subjects
free text keywords: Marketing; Forecasting; E-commerce; Classification; Clickstream data; Customer Relationship Management
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