Predicting the Sales Product Demand with Big ...

Predicting the Sales Product Demand with Big Mart Data Using Machine Learning Models

Author Name : Dr. J. Maria Arockia Dass, D. Vamsi Krishna, N. Umadevi, S.Vishnu Vardhan, M. Varun Deva Vara Prasad

ABSTRACT

Sales business can be made successful by predicting the sales in advance. Predicting market sales is the only way of quantitative measure of all potential deals by every people of the organizations selling the product in a given market. Sales prediction is important in business and it is the key factor of success in business. There are many advert ages of sales prediction. More success in the business can be achieved with the help of more accurate prediction of sales. Prediction helps in reducing inventory and to schedule customer’s orders. Today’s business handles huge repository of data. The volume of data is expected to grow further in an exponential manner. The measures are mandatory in order to accommodate process speed of transaction and to enhance the expected growth in data volume and customer behaviour. Prediction model can be accurately designed using Machine Learning algorithm to assess likely sales for many retailing organizations. The sales can be predicted based on a mixture of many features like previous sales information, information about shops, retail contenders etc., Machine Learning models like SVM and Random Forest is proposed to improves model performance. And these models show the performance levels higher than existing model. The accuracy will be improved comparing the other machine learning algorithms.

KEYWORDS: business, sales, successful, improves.