DATA ANALYSIS ON CUSTOMER REVIEW.

Now-a-days, e-commerce websites have million of products ,each having hundreds of reviews. While buying any product, a customer spends a major time in reading its reviews and getting feedback from the past customers. This is an integral part of the ecommerce experience since the customers takes its decision solely based on others' opinions. The problem is that majority of reviews are not proper which compromise the genuine buyer?s ratings. These reviews can mislead the customer to degraded shopping experience. This is where the customer review analytics comes into picture. We examine the reviews on online shopping like amazon by various data mining methods. We analyze the available reviews of the product till date to give the buyer better and proper rating at a time of purchasing the product. This will also give the feature specific ratings which also help customer to analyze the two different products. We also analyze the reviews for identifying the person?s perspective towards the product. For the development of this project, .Net Framework architecture, SQL server and some data mining algorithms for processing and classification of data will be used. The data in the link provided by the user, is scraped, pre-processed and classified. The scraping will be done with the help of web scraper. Once the scraped data is obtained, it will be preprocessed and classified with the help of data mining methods. The result of the classification process generated is then provided to user. This result will then tell the user about the ratings of the product based on reviews. The algorithm used in the project will provide accuracy on the amount of precise and correct data. This would help customers in confidently buying a product. Moreover, e-commerce platforms would be benefited by increased customer retention. Since there is shift from traditional buying to the web based purchasing our solution fits rightly in the market.