Customer data mining for lifestyle segmentation

• Type: Article in International Scientific Journal
• Date: 2012

Authors

Vera L. Miguéis (Author) FEUP; A. S. Camanho (Author) FEUP; João Falcão e Cunha (Author) FEUP

Journal

Title: Expert Systems with Applications

Vol. 39 No. 3

Pages: 9359-9366

ISSN: 0957-4174

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 26 Citations

ISI Web of Science

Scopus - 43 Citations

INSPEC

COMPENDEX

Scientific classification

FOS: Social sciences > Economics and Business

Other information

Authenticus ID: P-002-7TE

DOI: 10.1016/j.eswa.2012.02.133

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8