Gaining Customer Preferences from E-Shopping Log-Files
نویسندگان
چکیده
Nowadays most commercial e-shops do not offer any shop assistance or just in a very poor manner. But an e-customer expects guidance and advertising as he or she is used from traditional shops. In this paper we present an approach how personal shopping feeling and individual advertising can be integrated into a shop of the new economy. We show how customer behavior can be described in the preference model of Preference SQL. In this setting we extract customer preferences automatically from e-shopping log files using commercial statistical software. We point out the powerful benefit of our approach by analyzing log data from our real-life e-shop COSIMA and indicate how the detected customer preferences can be applied to upgrade the personal guidance and assistance of our e-shop.
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