Research on E-commerce Demand Forecast Based on Big data Algorithm and AI

Abstract

With the growth of the Internet, the field of e-commerce has gradually developed into an important field in people's lives. Nowadays, e-commerce brands bring consumers a huge convenience and efficient consumption mode, while operating costs are lower compared to the real economy. People's daily consumption and shopping have gradually transformed from traditional trading models to online trading activities conducted through electronic trading. A large number of merchants have established their own e-commerce platforms to provide high-quality services and make people's daily lives more convenient. With the growth of AI, the use of massive user consumption data, combined with advanced algorithms such as data mining (DM) and deep learning, accurately analyzes user purchase, return, and other behaviors, thereby upgrading the experience of e-commerce platforms to attract more customers and purchases. Currently, e-commerce Big data can be used in precision marketing, supply chain, logistics warehousing, payment security, e-commerce finance and other fields; In the future, e-commerce Big data will be closely combined with AI and VR/AR to promote the digitalization of traditional industries and pay more attention to data security and personal privacy. Based on Big data algorithm and AI, this paper analyzes e-commerce demand forecasting.