Segmentation of bank customers by expected benefits and attitudes

Author:

Machauer Achim,Morgner Sebastian

Abstract

Segmentation by demographic factors is widely used in bank marketing despite the fact that the correlation of such factors with the needs of customers is often weak. Segmentation by expected benefits and attitudes could enhance a bank’s ability to address the conflict between individual service and cost‐saving standardisation. Using cluster analysis segments were formed based on combinations of customer ratings for different attitudinal dimensions and benefits of bank service. The clusters generated in this way were superior in their homogeneity and profile to customer segments gained by referring to demographic differences. Additionally, four characteristic groups of customers were identified showing special preferences for and against information services and technology.

Publisher

Emerald

Subject

Marketing,Marketing

Reference29 articles.

1. Ajzen, I. and Fishbein, M. (1980), Understanding Attitudes and Predicting Social Change, Prentice‐Hall, Englewood Cliffs, NJ.

2. Beane, T.P. and Ennis, D.M. (1987), “Market segmentation: a review”, European Journal of Marketing, Vol. 21 No. 5, pp. 20‐42.

3. Boyd, W.L., Leonard, M. and White, C. (1994), “Customer preferences for financial services: an analysis”, International Journal of Bank Marketing, Vol. 12 No. 1, pp. 9‐15.

4. Burnett, J.J. and Chonko, L.B. (1984), “A segmental approach to ‘packaging’ bank products”, Journal of Retail Banking, Vol. 6 Nos 1/2, pp. 8‐17.

5. Calantone, R.J. and Sawyer, A.G. (1978), “The stability of benefit segments”, Journal of Marketing Research, Vol. 15, pp. 395‐404.

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