Predicting customer churn from valuable B2B customers in the logistics industry: a case study

This study uncovers the effect of the length, recency, frequency, monetary, and profit (LRFMP) customer value model in a logistics company to predict customer churn. This unique context has useful business implications compared to the main stream customer churn studies where individual customers (ra...

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Bibliographic Details
Published in:Information systems and e-business management 2015-08, Vol.13 (3), p.475-494
Main Authors: Chen, Kuanchin, Hu, Ya-Han, Hsieh, Yi-Cheng
Format: Article
Language:English
Subjects:
Brand loyalty
Business
Business and Management
Business to business commerce
Case studies
Competition
Customer services
Electronic commerce
Information systems
Information Systems Applications (incl.Internet)
International
IT in Business
Logistics
Management
Management science
Mathematical models
Original Article
Streams
Studies
Turnover
Value analysis
Variables
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Summary:This study uncovers the effect of the length, recency, frequency, monetary, and profit (LRFMP) customer value model in a logistics company to predict customer churn. This unique context has useful business implications compared to the main stream customer churn studies where individual customers (rather than business customers) are the main focus. Our results show the five LRFMP variables had a varying effect on customer churn. Specifically length, recency and monetary variables had a significant effect on churn, while the frequency variable only became a top predictor when the variability of the first three variables was limited. The profit variable had never become a significant predictor. Certain other behavioral variables (such as time between transactions) also had an effect on churn. The resulting set of predictors of churn expands the original LRFMP and RFM models with additional insights. Managerial implications were provided.
ISSN:1617-9846
1617-9854
DOI:10.1007/s10257-014-0264-1