Customer Satisfaction Analysis Using Social Media Feedback

Abstract

Customer Opinions are a great source of finding the popularity of product in the market. The social media networks are becoming an essential part of our lives. People use these to share their thoughts and feelings. A great amount of data in the form of tweets and statuses is present online which expresses the sentiments of people regarding consumer products which can be utilized to analyze customer trends, likes and dislikes. Companies and Organizations spends millions in attaining the Customer Feedback of their products. Experts estimate that Fortune 500 companies are losing $12 billion per year in value because they do not exploit Customer Feedback data present online. Our Project performs sentiment analysis using twitter data. It classifies tweets into Positive, Negative and Neutral by applying Sentiment Analysis and Natural Language Processing Techniques. Our project could help enterprise decision-makers to improve brand equity, increase revenue, and reduce operational costs. It can be used to identify the Customer Value Segment and it can also detect the Customer Loyalty regarding the various products. It can categorize the immense responses on the media/internet and produce useful results.