Research on Optimization of Taobao Product Sales Forecast Based on ARIMA model

DOI

10.2991/978-94-6463-488-4_4How to use a DOI?

Keywords

E-commerce; sales; ARIMA; machine learning algorithms; forecast

Abstract

Accurate sales forecast is of great guiding significance for online e-commerce. First of all, merchants can make corresponding marketing strategies and inventory plans in advance according to the predicted sales volume of goods, so as to meet the needs of consumers and achieve profits, while avoiding the stock shortage or backlog of goods, so as to improve operational efficiency and customer satisfaction, and help merchants better understand consumer demand and market trends. By analyzing historical sales data and consumer reviews, merchants can tap into consumers’ shopping habits and preferences, as well as hot items and trends in the market. This information is very important for merchants to formulate marketing strategies and adjust product positioning, which can help merchants better meet market needs and consumer expectations.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Chengyang Li
PY  - 2024
DA  - 2024/08/29
TI  - Research on Optimization of Taobao Product Sales Forecast Based on ARIMA model
BT  - Proceedings of the 2024 2nd International Conference on Digital Economy and Management Science (CDEMS 2024)
PB  - Atlantis Press
SP  - 27
EP  - 37
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-488-4_4
DO  - 10.2991/978-94-6463-488-4_4
ID  - Li2024
ER  -