A comparison of two multivariate analysis methods for segmenting users of alternative payment means

A comparison of two multivariate analysis methods for segmenting users of alternative payment means PurposeAlternative payment means have been expanding rapidly in recent years. The need to identify the segments of customers that are targetable for both financial and nonfinancial institutions is growing. The purpose of this paper is to use two different methods, discriminant analysis and decision trees, in order to compare the effectiveness of the two methods for segmentation and identify critical consumer characteristics which determine behavior and preference in relation to the use of payment means.Design/methodology/approachUsing data from 321 bank customers, decision tree and discriminant analysis methods are used, first to test the same set of variables differentiating the customers and then to compare the respective results and prediction ability of the two methods.FindingsResults show that discriminant analysis has a better model fit and segments the customers in a more effective way than the decision tree method. In addition, each method shows different variables to differentiate the customer groups.Research limitations/implicationsThe findings are limited to the sector and country of the study, as well as the convenience sample that has been used.Practical implicationsSuggestions for financial managers to better understand their customers’ behavior and target the right group are discussed.Originality/valueThis is the first attempt to compare decision trees and discriminant analysis as alternative segmentation methods for payment means. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Bank Marketing Emerald Publishing

A comparison of two multivariate analysis methods for segmenting users of alternative payment means

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Publisher
Emerald Group Publishing Limited
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0265-2323
D.O.I.
10.1108/IJBM-10-2016-0157
Publisher site
See Article on Publisher Site

Abstract

PurposeAlternative payment means have been expanding rapidly in recent years. The need to identify the segments of customers that are targetable for both financial and nonfinancial institutions is growing. The purpose of this paper is to use two different methods, discriminant analysis and decision trees, in order to compare the effectiveness of the two methods for segmentation and identify critical consumer characteristics which determine behavior and preference in relation to the use of payment means.Design/methodology/approachUsing data from 321 bank customers, decision tree and discriminant analysis methods are used, first to test the same set of variables differentiating the customers and then to compare the respective results and prediction ability of the two methods.FindingsResults show that discriminant analysis has a better model fit and segments the customers in a more effective way than the decision tree method. In addition, each method shows different variables to differentiate the customer groups.Research limitations/implicationsThe findings are limited to the sector and country of the study, as well as the convenience sample that has been used.Practical implicationsSuggestions for financial managers to better understand their customers’ behavior and target the right group are discussed.Originality/valueThis is the first attempt to compare decision trees and discriminant analysis as alternative segmentation methods for payment means.

Journal

International Journal of Bank MarketingEmerald Publishing

Published: Apr 3, 2018

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