Stefan Meinzer
Translating the determination of subjective customer perceptions from the health care sector to the service industry
The automotive industry is in the middle of a disruptive change in which a competitive differentiation based on the car as a product itself is not sufficient anymore. Customer centricity is one of the most important management goals in this industrial sector. The consequence is a shift from a product-focused company towards a service provider where the car is just one element to achieve the target of maximum customer satisfaction. Understanding subjective customer perceptions in this complex service environment is the resulting challenge.
In order to achieve the highest outcome of a medical treatment perceived by the patients, patient centricity is the core focus of the health care sector since years. The determination of perceived patient satisfaction has been well researched and various measurement approaches exist.
This work focuses on the knowledge transfer of perceived satisfaction determination from the health care sector to the automotive industry. A case study has been conducted that illustrates the managerial implications and recommendations for improvement of the established customer satisfaction determination in the automotive industry. Each service process of a car is generating a vast amount of data. This work shows how to make maximum use of this value by answering these two questions: 1. Can dissatisfied customers be classified before the customer service interaction ends based on data that is produced during a service visit? 2. Can the indicators for dissatisfaction be derived from service process data? Based on the knowledge derived in this work, new data-driven service and business models can be developed for the automotive industry to really achieve customer centricity.