Determining customer satisfaction elements in retailing after-sales services have been well explored; however, the increasing competition in this area demands the investigation of actual instrumentality of these elements on satisfaction of customers. In the present research, we have proposed a framework for assessing the instrumentality of after-sales services on customer satisfaction. Kano model and SERVQUAL framework were used to categorize customer satisfaction elements. In addition, in order to address behavioral dissimilarities among customers, RFM clustering technique was used for analysing 243,180 customers of automobile after-sales services. Accordingly, dissatisfaction decrement index and satisfaction increment index were measured for every cluster separately. We identified a group of 21 quality elements and demonstrated the instrumentality and quality of these quality elements on customer satisfaction. RFM clustering technique is applied to address customer dissimilarities and we demonstrated the preferences and desires of customers in each cluster. While some papers have already identified the influential factors of after-sales services on customer satisfaction, this is for the first time that the instrumentality of after-sales services is being identified. Accordingly, this study demonstrates how different after-sales services quality elements affect customer satisfaction. Therefore, the results of this study can help companies to allocate their resources more efficiently.