A Survey on Feature Fatigue Analysis Using Machine Learning Approaches for Online Products

Abstract

On recent days, the leading manufacturers are very keen in online business processing; the products are brought into heavy competitive online market. To be successful in the online market, the manufacturers launch the new products with many features to compete with other manufacturers’ products. The online customers are also interested in choosing the products with more attractive features, but the customers face problems in the features of the product by using it. Here, the term “feature fatigue” refers to the concept of customers’ dissatisfaction. In the real market, the products with maximum attractive features are preferred by the customers in the initial stage. Later, the customers realize that some of the features are inconsistent which results in dissatisfaction on the product. Moreover, this dissatisfactory of the customers on the product majorly affects the goodwill and growth of the manufacturer. Many researchers have contributed several techniques to overcome the concept of feature fatigue. In this paper, the most significant feature fatigue analysis methods are discussed as a review to elevate the feature fatigue.