Importance-performance analysis (IPA) is a simple marketing tool commonly used to identify the main strengths and weaknesses of a value proposition. This study proposes 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 tool which is as simple and intuitive as the original IPA, but more precise and reliable than the solutions proposed thus far. Methodology 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, we 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: We acknowledge that only one dataset has been used. Our goal is merely to demonstrate a revised approach to importance-performance analysis. Originality/value of paper First, we assert the need for an explicit distinction between the use of IPA for customer acquisition versus customer retention purposes. These two cases refer to distinct moments in the customer relationship life cycle and thus require separate analyses. We then propose a specific method for customer retention IPA. On this basis, we generate two priority charts: one for the purpose of maximizing customer satisfaction and one for the purpose of minimizing customer dissatisfaction.