Demand Forecasting For Retail Demand With Online Platform

Online platforms have become popular for shopping any product now-a-days. The offers and discounts available with these platforms are attracting more and more people to buy products from online options. It may be a platform like amazon, flip kart or personalized product selling website like croma , reliance digital for electronic products and nykaa fashion, myntra etc for fashion related stuff. The brands like Hitachi, Phillips, Sony have their online stores where they offer bigger discounts on their products to attract customer for hassle free purchases. Moreover they spend hefty amount of money behind automation of decision support systems which include accurate prediction of demand of particular products. In this research, demand of particular electronic products is forecasted. Quantitative demand forecasting needs various categorised data like season, holidays, promotional expenses done because of constant variations in demand, seasonal changes and changing trends of market. The process needs data from online electronics store which is available thru Kaggle and data.world websites. Use of forecasting models like Modified ARIMA (AutoRegressive Integrated Moving Average) to predict product demand that performs more accurate results in comparison to the existing state of art technique.