HA76 : Fuzzy clustering of customers and analysis of their behavior using dynamic data mining approach (Case Study: Samsung Mobile Phones)
Thesis > Central Library of Shahrood University > Industrial Engineering & Management > MSc > 2014
Authors:
Abstarct: Today, customer is considered as the main key of success or unsuccess a company. Therefore the study of the customers’ behavior has been regarded by marketing researchers during recent decades. The analysis of the customers’ loyalty, satisfaction and preferences are the most important issues in this area that researchers try to analysis of them by using different tools and methods. This study in terms of objective is applied research, in terms of methodology is survey research and in terms of subject, is marketing research. The purpose of this research is the customers’ segmentation using data mining techniques and the prediction of their behavior using dynamic C-means algorithm. For this purpose, the purchase data of 3000 Samsung mobile phone users has received and then this data has considered by Matlab 2008a after writing C-means algorithm. The results show that dynamic technique presents more real segmentations than static technique. Moreover the analysis of behaviors during a time period shows that customers are tendered to the price of the mobile phones. Traits such as the quality of the camera and processor and the number of sim cards and RAM are the reasons of change in the customers’ segmentations.
Keywords:
#Customer behavior #Dynamic data mining #Clustering #FCM Link
Keeping place: Central Library of Shahrood University
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Keeping place: Central Library of Shahrood University
Visitor: