Mapping dimensions of customer experience using big data analytics to enhance customer relationship management strategies: a case study in the B2B context

Abstract

This paper investigates the role of customer emotions in predicting referral intention and repurchase behavior. A combined qualitative and quantitative research approach was implemented to extract sentiment from written customer reviews that serve as input for the regression analysis.

The results show that a combination of qualitative and quantitative customer data might reveal underlying dimensions of customer satisfaction in contrast with the usage of uni-dimensional constructs like Net Promoter Score to measure customer satisfaction.

Furthermore, the outcomes show that combining customer relationship management strategies with the implementation of a customer-centric culture can be beneficial for strengthening customer relationships, increased firm performance and reduced churn rates.