Measuring Customer Satisfaction With the University Front Line Services Using Association Rules

Abstract

Customer satisfaction and quality services are among the global issues plaguing organizations. This study aimed at finding words/word patterns on comments and/or feedback from Facebook pages on the services provided by the frontline services of PSU-Urdaneta City campus to measure customer satisfaction by utilizing linguistics-based pattern recognition approach. This study employed association rules using the frequent-pattern growth (FP-growth), which adopts a divide-and-conquer strategy for finding frequent item sets. Meaningful patterns of negative comments on the services provided by some of the offices implying unsatisfactory customer service were revealed. However, there were also positive and satisfactory customer services provided by various offices as evidenced by positive comments addressed to the quality of rendered services. The result implies that sentiment analysis and word association can be utilized to measure customer satisfaction and serve as a tool to enrich and improve the frontline services provided by the institution to their clientele.