A methodology to map customer complaints and measure customer satisfaction and loyalty
In this study, an analysis was conducted for the relationships between the main components of customer relationship management (CRM) and customer complaints in the domain of logistics and transport. Today, complaints and the handling of complaints play a pivotal role in customer relationships. Moreover, companies are reluctant to admit that they have difficulties with customers complaints, but as yet there appears to be no complete solution to this issue. To remedy this situation, customer complaints must be comprehensively collected and analysed. Issues must be classified, and timely solutions must be developed. In this paper, a conceptual framework is proposed including mathematical models, hypothesised relationships, perceived value and interactivity between customer, business and the system, as well as customer satisfaction analytics. The framework will address the relationship between customer satisfaction issues, loyalty and customer acquisition and estimate customer satisfaction and loyalty. For the purpose of analysis, this study uses both qualitative and quantitative approaches. For data collection, a survey questionnaire was distributed to 60 Fremantle Port logistics and transport customers. For the quantitative approach, linear and nonlinear modelling is adopted. Using the model, we are able to address the shortcomings of CRM technology, and tackle the issues of loyalty improvement and customer acquisition. Finally, based on nonlinear modelling and using a fuzzy inference system, namely the TakagiSugeno-type approach, we defined fuzzy rules, by means of which we ascertain the relationship between customer satisfaction and the main relevant variables.
customer satisfaction loyalty customer relationship management perceived value customer acquisition complaint management data envelopment analysis linear modelling adaptive neuro-fuzzy inference system (anfis)