In the present scenario, every product based company need an analysis of the sales of the products sold across the various outlets located around the country or world. The business growth depends on the sales of the product to the customers with their satisfaction. In this way, every business distribution company needs the prediction to analyze the sales of the product across their showrooms. In this paper, the research study towards the analysis of the various data elements to predict the business outcome of a company is discussed with different machine learning models. Different attributes will play a key role to define the sales of the product that includes the factors of the customer or applicant, features of the product and the qualities of the managers in the store, who promote the product sales. The research to consider the important attributes, and the analysis of the data by exploring the data elements, the importance to impute the missing values plays a key role to increase the rate of perfect predictions and the model building using a different machine learning techniques for better accurate predictions are completely discussed in this paper that enhance to provide the better business sales predictions. This research study might be very much useful to the distribution companies, to consider the important key attributes that play a major role in the sales of their products.

Keywords : Prediction, Attributes and Business Outcome.