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

Authors: Neda Lalvand; Mohammad Saleh Owlia

Addresses: Industrial Engineering Department, Yazd University, Yazd, Iran ' Industrial Engineering Department, Yazd University, Yazd, Iran

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.

DOI: 10.1504/IJBIR.2024.141619

International Journal of Business Innovation and Research, 2024 Vol.35 No.2, pp.219 - 237

Received: 22 Jun 2021
Accepted: 07 Oct 2021
Published online: 27 Sep 2024 *

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