The core and purpose of business operation is to make profits. The key to profitability lies in improving the sales revenue of the company, as well as discovering potential users, retaining lost users, and maintaining important users. Therefore, the forecast of sales and the early warning of user loss are very important for enterprise supply chain management and Customer-oriented operations are of great guiding significance. The purpose of this paper is to study the sales forecast method of private enterprises based on BP neural network. This paper summarizes the influencing factors that affect the sales of enterprises, combined with the BP neural network model, analyzes and designs the sales forecast model of private enterprises based on the BP neural network. Using statistical methods and the combination of qualitative and quantitative methods, through targeted analysis, it solves the problem of determining the influencing factors of private enterprise sales and data processing in the process of verifying and applying the private enterprise sales forecasting model based on BP neural network. The experimental results show that the mean MSE of BP neural network is 4.78, and the effect of predicting the sales of private enterprises is good.

Chenjie Ouyang. Sales Forecast Method of Private Enterprises Based on BP Neural Network. International Journal of Neural Network (2022), Vol. 3, Issue 3: 9-16. https://doi.org/10.38007/NN.2022.030302.

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