Abstract: “Amazon Big Data”, conducts a thorough analysis on the e-commerce industry using big data and how certain trends can affect the functioning of the organizations delving in the field. With the growth of e-commerce, there has been a significant rise of the online consumers’ footprint. Companies such as Amazon, Flipkart and other e-commercial platforms have accrued huge chunks of consumer information, especially since the start of the pandemic. In this industry, reviews and ratings given to a product play a crucial role in determining the sentiments of the customers associated towards making the final purchase. Such factors account for the brand’s sales and image. In today’s landscape, a careful customer goes through the ratings of the product, its reviews which serve as a medium of screening. In a tie between two similar products, customers purchase a product with higher ratings and better reviews. Therefore, this leads us to the development of an ideal rating metric that is significant for the sales of the product. Moreover, become a tool for product differentiation. This manuscript is a method to standardize the ratings of customers and preserve the sanctity of the data. We discuss models which are an amalgamation of customer ratings, their respective reviews and a sentiment scored derived from the same review. These models also help us define customer clusters with different personalities based on their reviews and ratings. In addition to this, customer segmentation is a future scope to deep dive into the sales data and understand the financial behavior of a customer.
Keywords: Curve Fitting Model, Google Cloud Platform, text analytics
