CUSTOMER SEGMENTATION USING RFM ANALYSIS AND CLUSTERING ALGORITHMS IN EXPRESS DELIVERY INDUSTRY

Tuncay Özcan ()
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Tuncay Özcan: Istanbul Technical University

Eurasian Business & Economics Journal, 2023, vol. 32, issue 32, 47-56

Abstract: As in every sector, one of the most important issues in the express delivery industry is to get to know the customers. Understanding customer preferences and identifying loyal and churn customers provides significant competitive advantages for companies. At this point, customer segmentation based on RFM analysis is widely used. RFM analysis segments customers using recency (R), frequency (F) and monetary (M) attributes. In this study, customer segmentation is presented with a case study with the actual data taken from an express delivery company.  For this purpose, firstly, k-means and fuzzy c-means algorithms are used for customer segmentation based on RFM analysis. Then, Silhoutte and Dunn indices are calculated to evaluate the clustering quality and to determine the best number of clusters. Finally, on the basis of the obtained cluster centers, strategic analysis is carried out and churn and loyal customers are determined.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eas:buseco:v:32:y:2023:i:32:p:47-56

DOI: 10.17740/eas.econ.2023-V32-04

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