Convolutional Neural Network Model for Measuring Customer Satisfaction Based on Facial Expressions

Abstract

Customer satisfaction shows how well the product or service of an organization meets customer expectations. Customers' facial expressions can show their satisfaction with the services provided. Convolution Neural Network (CNN) is a type of neural network algorithm that can be used to recognize an object in an image. CNN utilizes the convolution process to determine and distinguish an object in the image from other objects such as to recognize various facial expressions. This study aims to measure customer satisfaction by utilizing the CNN model by recognizing any changes in facial expressions. From the results of the CNN model training, an accuracy of 90.57% was obtained. Furthermore, the formed model is implemented into a web-based system that records facial expressions and performs a classification (satisfied or dissatisfied) on any detected facial changes. The most dominant expression is the result of measuring customer satisfaction.