Customer data mining for lifestyle segmentation
نویسندگان
چکیده
A good relationship between companies and customers is a crucial factor of competitiveness. Market segmentation is a key issue for companies to develop and maintain loyal relationships with customers as well as to promote the increase of company sales. This paper proposes a method for market segmentation in retailing based on customers’ lifestyle, supported by information extracted from a large transactional database. A set of typical shopping baskets are mined from the database, using a variable clustering algorithm, and these are used to infer customers lifestyle. Customers are assigned to a lifestyle segment based on their purchases history. This study is done in collaboration with an European retailing company. 2012 Elsevier Ltd. All rights reserved.
منابع مشابه
Integrating AHP and data mining for effective retailer segmentation based on retailer lifetime value
Data mining techniques have been used widely in the area of customer relationship management (CRM). In this study, we have applied data mining techniques to address a problem in business-to-business (B2B) setting. In a manufacturer-retailer-consumer chain, a manufacturer should improve its relationship with retailers to continue its business. Segmentation is a useful tool for identifying groups...
متن کاملCombining data mining and group decision making in retailer segmentation based on LRFMP variables
Data mining is a powerful tool for firms to extract knowledge from their customers’ transaction data. One of the useful applications of data mining is segmentation. Segmentation is an effective tool for managers to make right marketing strategies for right customer segments. In this study we have segmented retailers of a hygienic manufacture. Nowadays all manufactures do understand that for st...
متن کاملCustomer Behavior Mining Framework (CBMF) using clustering and classification techniques
The present study proposes a Customer Behavior Mining Framework on the basis of data mining techniques in a telecom company. This framework takes into account the customers’ behavior patterns and predicts the way they may act in the future. Firstly, clustering technique is used to implement portfolio analysis and previous customers are divided based on socio-demographic features using k</em...
متن کاملA Hybrid Data Mining Model for Intelligent Customer Segmentation: The Case of Banking Industry
Customer segmentation is a prerequisite to all three phases of customer relationship management which consists of customer acquisition, customer retention and customer development. Input variables which are used in clustering techniques determine which phase of customer relationship management it is dealing with. As a result this paper aims at a review on the input variables used in customer se...
متن کاملAn Intergrated Data Mining and Survival Analysis Model for Customer Segmentation
More and more literatures have researched the application of data mining technology in customer segmentation, and achieved sound effects. One of the key purposes of customer segmentation is customer retention. But the application of single data mining technology mentioned in previous literatures is unable to identify customer churn trend for adopting different actions on customer retention. Thi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Expert Syst. Appl.
دوره 39 شماره
صفحات -
تاریخ انتشار 2012