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Customer data mining for lifestyle segmentation
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DOI：10.1016/j.eswa.2012.02.133.png)
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摘要
En 中文
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. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
Retailing
Clustering
Segmentation
Lifestyle
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期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
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