Abstract

Improving Customer Experience (CX) is a strategic priority for organisations. This study develops and evaluates a Process Mining framework that extracts operational performance metrics and interpretable insights from event logs to support evidence-based decisions for optimizing CX. The framework encompasses the discovery of visual process models, cycle time measurement, analysis of operational flows and frequencies, identification of recurring bottlenecks, and evaluation of model accuracy. Applied to three datasets (Sepsis Events, BPI Challenge, and Hospital Billing), the results showed strong model accuracy, ranging from 88% for BPI Challenge to 100% for Hospital Billing. Additionally, the analysis uncovered efficiency variations, with cycle times spanning 19.4 hours to 149.2 days, and flagged notable delays, such as over 700 hours in administrative duties. These findings affirm the framework’s ability to offer in-depth insights, helping organisations identify key obstacles and take purposeful steps to elevate service quality and customer contentment.