Unveiling the Negative Customer Experience in Diagnostic Centers: A Data Mining Approach.

Abstract

This study aims to identify the negative customer experiences reflected in complaints against diagnostic centers using data mining tools. Analyzing customer complaints from a consumer complaints website, the Apriori algorithm was employed to uncover frequent patterns and identify key areas of concern. The frequency and distribution of terms used in complaints were also analyzed, and word clouds were generated to visualize the findings. The study revealed that major areas of unfavorable customer experience included delayed test reports, erroneous test results, difficulties scheduling appointments, staff incivility, subpar service, and medical negligence. These findings and the proposed model can guide diagnostic centers in incorporating data mining tools for customer experience analysis, enabling managers to proactively address issues and view complaints as opportunities for service improvement rather than legal liabilities.