Study for the Prediction of E-Commerce Business Market Growth using Machine Learning Algorithm

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Abstract
Learning is a key to perform ideas adequately. Machine Learning empowers IT organizations to identify the patterns on the basis of currently available algorithms and data frames to cultivate acceptable solution concepts. Online business market and customer retention is a relation like the two sides of a coin. It is a nonlinear relationship. Prediction of Business growth is a very sensitive issue of E-Commerce market with its future existence. Online venders of business market manage their inventories on virtual prediction bases for full filling the basic need of demand-supply chain of customers. Authorizing traditional ways and analysis methods are not ensuring the rate of reliability of the sales prediction. To produce more precise predictions and analysis, we use ML algorithm. In this paper, we utilized the selling data set of an E-commerce company and segregated it, in different quarters then calculating the sale income per quarter. After that we divided the dataset in the proportion of 70% and 30% for Training data set and Testing data set. By applying machine learning algorithm, we will be predicting income of next quarters as well as analysis the maximally sold commodities with their frequencies of purchase per quarter. Then provide analysis results and prediction of customer's purchase patterns to the business organization to make a strategy to take a competitive advantage by sustaining and accumulating for their goods management and planning for inventories.