Rejuvenating importance‐performance analysis

Abstract

Purpose

Importance‐performance analysis (IPA) is a simple marketing tool commonly used to identify the main strengths and weaknesses of a value proposition. The purpose of this paper is to propose a revision of traditional IPA prompted by intuitions arising from the three‐factor theory of customer satisfaction. The ultimate goal is to propose a decision support method, which is as simple and intuitive as the original IPA, but more precise and reliable than the solutions proposed thus far.

Design/methodology/approach

In order to estimate indirect measures of attribute importance, the study uses the coefficients of a multiple regression with overall satisfaction ratings as the dependent variable. Additional calculations are then introduced in order to manage non‐linear effects.

Findings

Using empirical data from a survey among 5,209 customers of a European bank, the authors show how the proposed method can be more accurate than other solutions, especially as disregarding non‐linear effects can prompt sub‐optimal marketing decisions.

Research limitations/implications

While the procedure in this study is applicable to any service business, the paper does not claim external validity for the numerical results of the empirical application: the authors acknowledge that only one dataset has been used. The authors' goal is merely to demonstrate a revised approach to IPA.

Originality/value

First, the authors assert the need for an explicit distinction between the use of IPA for customer acquisition vs customer retention purposes. These two cases refer to distinct moments in the customer relationship life cycle and thus require separate analyses. The authors then propose a specific method for customer retention IPA. On this basis, they generate two priority charts: one for the purpose of maximizing customer satisfaction and one for the purpose of minimizing customer dissatisfaction.

Citation

Arbore, A. and Busacca, B. (2011), "Rejuvenating importance‐performance analysis", Journal of Service Management, Vol. 22 No. 3, pp. 409-429. https://doi.org/10.1108/09564231111136890