Sales Forecast for Amazon Sales Based on Different Statistics Methodologies

Abstract

Accurate sales forecast plays an important role in reducing costs and improving customer service levels, especially for B2C e-commerce. This paper tries to forecast future sales at Amazon based on historical sales data. Firstly, it proposes three possible forecasting approaches according to the historical data pattern, that is Winters’ exponential smoothing, time-series decomposition and ARIMA. Secondly, it specifies three relatively accurate and suitable approaches. Then, a sensitivity analysis will be conducted on the three methods, considering the suitability of the forecast methods will be judged by whether or not they produce random residuals. Finally the three methods will be implemented to forecast Amazon’s quarterly sales in 2014. The result can help Amazon well manage its future operation especially for the season sales at Christmas.