The Internet has revolutionalized the way we buy products. In the online marketplace, people cannot feel and touch products the same way we do in physical stores. This increases the importance of methods to evaluate the products before purchase. In the retail e-commerce world, gathering customer feedback is key since customers need to rely largely on product reviews to make up their minds for better decision making on purchase.
In this project, we analyze customer sentiment using data from online reviews of electronic products on major e-commerce website Amazon. The focus is on using Natural Language Processing (NLP) techniques on the textual data, learning more about what constitutes a satisfied customer review.