Opinion Mining and Client Feedback Mining for Quality Improvement

Abstract

As E-Commerce growing rapidly, now a day’s customers reviews about product has become most crucial for development of the business. The opinion mining is most crucial in ecommerce websites, furthermore advantageous with client’s feedback. The current research work mainly focuses on the client engagement review analysis. In this paper we concentrated on mining reviews from clients who are seeking consulting services from the IT industries, which enables the companies to understand the data patterns and identify some Key Performance Indicators and develop accordingly. The Client feedback mining allows the user to allow Clients to convey what they think and feel about the services. This opinion or review about the product will help purchaser to get an idea regarding the product, and the seller regarding required improvements or updates, hence opinion mining plays a major role in ecommerce. We also concentrated on the sentimental analysis that means a reviewer can write about the product positively or negatively, it depends on many parameters such as emotions they want to express, opinion of the product they purchased, received time, package and condition they received the product. It clearly gives an idea to the seller and purchaser about demand, supply and quality improvement. Key Performance Indicator is measured based on metrics that business organizations track in order to measure their progress towards goal within marketing networks. We designed a mathematical model and executed for results. We discussed different algorithms based on opinion mining and we implemented cloud based practical implementation of a simulated model for understanding of results and given graphical analysis along with result analysis