Abstract

Web Mining (WM) remains a relatively unknown technology. However, if used appropriately, it can be of great value to the identification of existing customers’ behaviours online. The recent technical advances in the field of WM enhance tremendously the analytical Customer Relationship Management (aCRM), still usually related to a simple transactional function. This study follows an exploratory approach to assess whether WM fulfills, alone, all three objectives of the second theme of Xu and Walton’s1 adapted aCRM framework for customer knowledge acquisition, namely the identification of existing web customers’ behaviour. It also investigates to what extent WM should be used in conjunction with traditional marketing research to optimize CRM, and hence marketing, in a web context. In-depth, semi-structured interviews reveal that WM is very well suited to understand existing web customers’ transactional web behaviour(s) (i.e. navigation patterns; amount of purchases by week, month, and region; and cross-selling and up-selling opportunities). Nevertheless, WM does not do well in understanding less obvious, underlying dimensions of customer behaviour, including how existing customers develop satisfaction, loyalty, defection and attachment on the web. WM still needs to be complemented with traditional marketing research in order to reach these more difficult but essential aCRM objectives. To cite this document: Myriam Ertz and Raoul Graf, How do they behave on the web? An exploratory study of mining the web for analytical customer relationship management, International Journal of Electronic Commerce Studies, Vol.6, No.2, pp.289-304, 2015. Permanent link to this document: http://dx.doi.org/10.7903/ijecs.1398 Â

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