The business outcomes in this era is significantly influenced by customer reviews, feedbacks and their behavior. The objective of current research is to evaluate the relationship between product sales and online sentiment using sentiment analysis along with machine learning techniques. The research performs NLP to classify and analyze trends in consumer feedback for amazon. The sentiment scores are evaluated using TextBlob. The sentiment distribution plots are used to visualize sentiment scores. The predictive power of review is evaluated using logistic regression along with other regression models. The product performance is found to be correlated with F-1 scores and high accuracy is attained for different regression models. The research findings have shown that with the monitoring of review sentiment the business can get significant competitive advantage and this facilitates to list products accordingly. The results emphasize the usage of sentiment analysis in developing of e- commerce businesses.