Customer complaints monitoring with customer review data analytics: An integrated method of sentiment and statistical process control analyses. (August 2021) - Kim, Juram; Lim, Chiehyeon
Abstract: This study presents a data-driven method to monitor customer complaints for efficient service quality management. Recognising the value of customer reviews as a pool of 'voice of the customer', we propose an integrated method of sentiment and statistical process control analyses. The use of customer review data for statistical process control analysis extends the scope of research and application from the supplier perspective to customer-centric service quality management. The sentiment analysis enables systematic identification of a customer satisfaction score from customer review data while the statistical process control chart analysis allows early detection of significant customer complaints and prevents service failures. The integration of two analyses makes it possible to monitor customer complaints at acceptable time and cost. We applied and validated the proposed method using a mobile game service, offering a guideline for its implementation and customisation. The proposed method is expected to be used as an effective tool for customer complaints monitoring over time, which enables responsive and preventive quality management.