Sentiment analysis mainly focuses on subjectivity and polarity detection. Today consumers make buying decision based on the customer's review that is available in some of the online shopping sites like shopclues, fabfurnish, pepperfry, flipkart etc. There are also some of the specific websites which discuss about positive and negative facts of those products that comes to market like reevoo, buzzillions, bizarte, amazon etc. Hence this type of analysis are socially very needed for sellers to undergo market analysis, branding, product penetration, market segmentation and so on. Here, the proposed paper classifies the most identified features using supervised learning method Naïve Bayes and determined their positive, negative and neutral polarity distribution.