An Application of a Rule-Based Method for Identifying the Factor Structure in Customer Satisfaction on a Beverage Dataset

The analysis of customer satisfaction datasets has shown that product-related features fall into three categories (basic, performance, and excitement), which affect overall satisfaction differently. Ahmad et al [1] proposed a rule-based method that can be used to analyze the characteristics of customer satisfaction data features. The inputs for these rules are derived by using a probabilistic feature selection technique. In this paper, we apply this method to a beverage quality dataset to understand the contribution of various input to the quality of a beverage.