Intelligent sales prediction using ARIMA techniques

Abstract

ARIMA model is revolutionizing its applications in every sector of life including computer vision, text and speech analysis, gaming, cyber security and has become a foremost contributor in physical world. This work is aimed at developing an intelligent deep learning model that entails incorporation of both decision analysis and future predictions. In the past many machine learning models have influenced the purpose of such sales prediction for business organizations as there evolved a rapid requisite for analyzing colossal volumes of data in bringing out efficient predictive patterns in sales. In this work, we examined the notion of sales data and estimation. The various techniques and measures for sales predictions are described and in accordance with an accurate performance evaluation. Using that, an appropriate predictive model is proposed for the sales trend forecast. The results are capitulated with reference to precision and reliability of proficient approaches acquired for prediction. Considering the customers' intuition, nature of target audience and their purchasing patterns, this deep learning model helps to perk up future sales prediction and marketing overcoming the pits and falls of the conventional approaches.