Establishing the Relationship Between Key Performance Indicators in Automated Customer Support Services and the Factors that Drive Customer Satisfaction

Due to the rapid development in automations, there is a growing need to improve automated customer support services (ACSS) in its performance to meet customer expectations and satisfactions. However, current objective performance measurements relevant to customer satisfaction are lacking and contradicting when considered with other target measurements in existing ACSS implementation frameworks to provide quantitatively accurate performance assessments of these platforms. The research aims to identify and align the key performance indicators (KPIs) of ACSS through literature review to achieve objective methods of performance measurement. To validate the framework, an ACSS prototype is developed, and data is collected for the KPIs. It is identified that the strong and weak ACSS factors in relation to customer satisfaction are data privacy protection, customer care, customer knowledge, sales and marketing tracking systems, information aggregation, AI training, and knowledge management. Further studies are to provide new measurements and explore the relationships with customer loyalty.