Prioritizing Customers by using clustering technique; Case study of railway passenger transportation

Articles in Press

Document Type : Scientific - Research

Authors

1 Assistant Professor , School of Railway Engineering, Iran University of Science and Technology

2 School of Railway Engineering, IUST

Abstract

Today, the interaction of companies with customers in the form of customer relationship management (CRM) has changed significantly. Identifying the characteristics of different customers and allocating optimal resources to them according to their value for companies has become one of the main concerns in the field of customer relationship management. The aim of this research is to provide a suitable model for customer segmentation based on their value creation. In the proposed process of this research, which has been implemented in a passenger rail transport company, the data related to all passengers and customers of the company in a period of 4 years; From the beginning of 2014 to the end of 2017, and after determining the values of the indicators of the model that is R. F. M. (Recency; Frequency, and Monetary value) customers are clustered based on three criteria, using K-means clustering technique. Next, by weighting the criteria (RFM) based on the best-worst method and calculating the lifetime value, the existing clusters are prioritized and the key and valuable customers of the company are identified. Finally, suggestions for improving the Customer Relationship Management system is presented.

Keywords

Main Subjects

Quarterly Journal of Transportation Engineering

Articles in Press, Accepted Manuscript
Available Online from 20 August 2023

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History

  • Receive Date: 08 March 2023
  • Revise Date: 02 June 2023
  • Accept Date: 26 June 2023

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