Prediction Model of Physical Goods Sales based on Time Series Analysis

Abstract

With the advent of the era of big data, most online historical consumption data are collected and simply stored in the cloud, but they are not receiving enough attention. This paper takes "online sales of physical goods" as the research object, uses "time series analysis related theory and sales prediction theory" to study and analyze "data from January 2020 to December 2021", and finally uses EViews software, using ARMA model for modeling and prediction. Establishing a mathematical model to effectively analyze and predict the "online physical goods sales ability", to a certain extent, has a practical guiding significance for e-commerce enterprises to make the optimal business decisions.