Integrating customer clustering and QFD to improve and develop services: a case study

Neda Lalvand and Mohammad Saleh Owlia

International Journal of Business Innovation and Research, 2024, vol. 35, issue 2, 219-237

Abstract: To be successful in today's dynamic marketplace, organisations must communicate with customers in order to improve their customer knowledge, such as customer demands and desires, opinions and needs. Current study employs a combination of QFD and customer clustering for the purpose of improving and developing mobile services in order to better meet customer demands and improve the organisation's performance. The current research model was implemented at the Mobile Telecommunications Company (MCI), of Iran and the corresponding data were collected through the distribution of questionnaires and interviews with experts. Customer clustering was performed using the K-means algorithm. Subsequently, a house of quality matrix was created for each cluster. Finally, recommendations were made to the organisation's managers regarding the procedures for improving mobile services. Additionally, the priorities and quality of MCI services were compared to those of a competitor company.

Keywords: customer clustering; quality function development; QFD; mobile phone services; data mining. (search for similar items in EconPapers)
Date: 2024
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