| D.: Visualizing and Classifying the Pattern of User’s Browsing Behavior for Website Design Recommendation (2004) | |||||||||||||||
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| Abstract. E-commerce website design is a highly complex and subjective task which is often very difficult to get right from the start. Once a design has been implemented, customer behavior usually needs to be monitored in order to correct bugs and inefficiencies. While there are tools available that record and visualize customer click stream data, the information provided by these tools cannot be directly translated into changes in the website design. Rather, an expert needs to go through a lengthy process of manual data analysis in order to identify and overcome weaknesses of websites. In this paper, we describe a click stream visualization technique using footstep graphs. We describe the experiment that produced these graphs and show how specific patterns can be identified that both point to problems with the website design and contain information about how to remedy them. We contend that the results we present in this paper represent the first step towards a technique for producing automatic recommendations for website improvements. 1 | |||||||||||||||
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