Satisfação do consumidor e árvore de decisão: um estudo empírico

Abstract

Obtaining data and studying consumer satisfaction are important for optimizing processes, developing and improving new products, as well as optimizing the use of resources for any organization. In this context, companies have developed several ways to collect data, such as satisfaction data collection devices in physical stores. With this data, it is possible to use forms of visualization, grouping and combinations of data, making use of statistical methods to provide inputs to measure consumer satisfaction and identify Promoters and Detractors. Thus, the objective of this work is to determine the consumer satisfaction variables that are most likely to point out the occurrence of a Promoter-type customer. After analyzing and processing data, using statistical software, a decision tree was created, composed of the most significant categories that are associated with the dependent variable of dissatisfied consumers. It was found that the Attributes, Areas and Product Availability variables were, in this hierarchical order, the most relevant for the probability of obtaining Promoter type customers.