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Developing the profiles of supermarket customers through data mining

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  • Hokey Min

Abstract

To stay competitive, supermarkets need to develop a viable customer retention strategy. Since a key to the successful development of such a strategy rests with customer relationship management, supermarkets should identify the most profitable ways to build and maintain a loyal customer relationship. In an effort to help supermarkets understand their customers' shopping/patronage behaviour and the ways to retain valued customers, we propose data mining techniques. Using the examples of franchised supermarkets in the south-eastern United States, this paper illustrates the usefulness of the proposed data mining techniques for examining customer grocery shopping behaviour and developing the profiles of loyal patrons.

Suggested Citation

  • Hokey Min, 2006. "Developing the profiles of supermarket customers through data mining," The Service Industries Journal, Taylor & Francis Journals, vol. 26(7), pages 747-763, October.
    • Handle: RePEc:taf:servic:v:26:y:2006:i:7:p:747-763
    DOI: 10.1080/02642060600898252
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    Cited by:

    1. Smith, Lindsey Gail & Yifei, Maggie Ma & Widener, Michael & Farber, Steven, 2022. "Geographies of grocery shopping in major Canadian cities: evidence from large-scale mobile app data," OSF Preprints kjsdz, Center for Open Science.
    2. Meng, Ting & Florkowski, Wojciech J. & Sarpong, Daniel B. & Chinnan, Manjeet S. & Resurreccion, Anna V.A., 2014. "Consumer’s Food Shopping Choice in Ghana: Supermarket or Traditional Outlets?," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 17(A), pages 1-24, March.
    3. Law, Rob & Rong, Jia & Vu, Huy Quan & Li, Gang & Lee, Hee Andy, 2011. "Identifying changes and trends in Hong Kong outbound tourism," Tourism Management, Elsevier, vol. 32(5), pages 1106-1114.
    4. Lindsey G Smith & Maggie Yifei Ma & Michael J Widener & Steven Farber, 2023. "Geographies of grocery shopping in major Canadian cities: Evidence from large-scale mobile app data," Environment and Planning B, , vol. 50(3), pages 723-739, March.

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