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A data mining approach for segmentation-based importance-performance analysis (SOM–BPNN–IPA): a new framework for developing customer retention strategies

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  • Seyed Hosseini
  • Alireza Ziaei Bideh

Abstract

Importance-performance analysis (IPA) is a simple but effective means of assisting practitioners in prioritizing service attributes when attempting to enhance service quality and customer satisfaction. The purpose of this study was to demonstrate how IPA can be used with market segmentation to develop customer retention strategies for different market segments. For this purpose, a new framework have been proposed that uses self-organizing maps for customers’ segmentation and back-propagation neural network (BPNN) for implicity drive the importance of service attributes based on their effect on customers’ loyalty in each segment. Then, individual IPA matrixes are developed for each market segment. Also, an example case is presented to demonstrate the implementation and application of the proposed framework. The results of the proposed framework compared with a conventional BPNN-IPA approach indicated that it can increase reliability and applicability of IPA results. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Seyed Hosseini & Alireza Ziaei Bideh, 2014. "A data mining approach for segmentation-based importance-performance analysis (SOM–BPNN–IPA): a new framework for developing customer retention strategies," Service Business, Springer;Pan-Pacific Business Association, vol. 8(2), pages 295-312, June.
  • Handle: RePEc:spr:svcbiz:v:8:y:2014:i:2:p:295-312
    DOI: 10.1007/s11628-013-0197-7
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    Cited by:

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    2. Vera L. Miguéis & Ana S. Camanho & José Borges, 2017. "Predicting direct marketing response in banking: comparison of class imbalance methods," Service Business, Springer;Pan-Pacific Business Association, vol. 11(4), pages 831-849, December.
    3. Jiacong Wu & Yu Wang & Ru Zhang & Jing Cai, 2018. "An Approach to Discovering Product/Service Improvement Priorities: Using Dynamic Importance-Performance Analysis," Sustainability, MDPI, vol. 10(10), pages 1-26, October.

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