A Systematic Review on Machine Learning Algorithms for Customer Satisfaction Classification in Various Fields

Abstract

Purpose: A variety of soft approaches have already been considered in relation to the growth of marketing. Problems related to customer satisfaction and retention have been studied earlier. The application of business intelligence, artificial intelligence, and data mining has a great impact on the development of business organizations. Customers are increasing day by day in every field, which is complicating the method of finding their satisfaction level. To find the best method to solve these complexities, advanced machine learning approaches can be used. This paper discusses a detailed literature survey of various approaches used to identify customer satisfaction and retention using customer logs in various fields.

Design/Methodology/Approach: The details collected for this review paper were obtained by analysing and comparing different research articles from recognized resources.

Objective: To find a research gap and appropriate solutions for customer satisfaction accuracy using machine learning approaches.

Results/ Findings: Review of this paper gives a proper understanding of customer satisfaction in various domains using machine-learning approaches

Originality/Value: The review of this paper gives an analysis of machine learning algorithms for customer satisfaction in various fields and suggests the importance of new classification models.

Type of Paper: Literature Review.