Methods on Mining Personalized Requirement Characteristics of Customers Through the Analysis of Their Customization Behavior Data

This paper investigates the methods on mining the requirement characteristics of customers by analyzing their customization behavior data during product configuration process. In order to obtain rich data and information from customer's product configuration process, an extended product family architecture (EPFA) was established and the functional regions of product configuration system were defined as well. On the basis of these, the customization behavior data of customers was collected by using Morae software. And them, these data were divided into different fragments from several aspects such as product structure, system function region, and configuration item contents and so on according to customer's customization behavior. Furthermore, the basal statistical parameters that reflect the behavior characters of customers were extracted. By combining these basal parameters with different modes, a more profound parameter can be defined that reflects the personalized requirement character of customer. Finally, a case study was used to verify the feasibility and effectiveness of methods and principles mentioned above.