Identifying Buying Patterns From Consumer Purchase History Using Big Data and Cloud Computing

Abstract

The consumer buying process refers to the procedures taken by a buyer when making a purchase. There are patterns that customers follow before they make purchases that can be described as consumer behavior. When making decisions, businesses and engineers turn to big data for the valuable insights it contains. Edge computing, although presenting processing issues, has aided in the evolution of big data by offering computational, networking, and storage capability. The process consists of identifying needs and wants, conducting research, evaluating options, and making a purchase, followed by evaluating the purchase. This is a considered major problem in the prediction history. To overcome these issues, here comes a framework of predicting customer purchasing using big data analytics (PCP-BDA) to determine the purpose of every customer becoming aware of the need or desire for a product and ends with the purchase transaction.