Customer Perception towards Internet Selling Platforms through Opinion Mining

Abstract

Online selling applications are becoming popular day by day. Customers of these applications find them easy to use, convenient, reliable, and quick at fetching responses. The number of such applications are growing in number by each passing year. There is also growing competition to win customers from each of the operating applications. Sometimes customers get confused by the variety of offers given by these applications. This study has looked at the customer perceptions towards two popular online selling applications namely, OLX and Quikr through the lens of sentiment analysis. Sentiment analysis is a way to capture the sentiments of customers using various analytical software. This study has used Python to do the analysis. The results of the study point out that one of the applications is favored by customers because they have experienced good service through it compared to the other application. The results show that customers value good service at all times and they develop a trust towards the service provider providing better value for money. The managers of the online selling applications should make an effort towards giving confidence to the users about the ease of use of the apps, its reliability, safety and security features, etc. The economy is moving towards adopting more of collaborative consumption practices and the future for such applications looks very promising. The study is relevant in the current times because customer perceptions towards online selling service providers can contribute to the very survival of these kind of applications and hence it is necessary to capture the same.