Sales prediction method and system

Abstract

The invention discloses a sales prediction method and system, and relates to the field of sales prediction, and the method comprises the steps: obtaining a predicted category and corresponding time information; obtaining corresponding feature data according to the predicted category and the corresponding time information; and inputting the feature data into a preset model combination correspondingto the predicted category, and predicting the sales volume of the predicted category in the time corresponding to the time information. According to the invention, the system is directly adopted to replace manpower to predict the sales volume, so that the capability requirement on purchasing personnel is reduced; and a computer system is adopted for prediction, so that the dimensions and the datavolume considered during prediction are greatly increased, and a foundation is laid for accurate prediction. In addition, the sales volume is predicted by using a multi-model combination, and the precision is greatly improved compared with prediction by using only one model. And each category has a corresponding preset model combination, so that the matching degree is better, and the prediction result of each category is further improved.

Description

technical field [0001] The invention relates to the field of sales forecast, in particular to a sales forecast method and system. Background technique [0002] When formulating business goals, retail enterprises need to estimate sales for a period of time in the future, that is, sales forecast; when managing inventory, they need to estimate sales for a period of time in the future, that is, sales forecast. [0003] The existing sales or sales forecast is mainly based on simple weighted calculations based on the historical data of the same period and the average value of recent data to obtain the forecast value for a period of time in the future, and subjective adjustments are made in combination with the experience and judgment of business personnel. [0004] The data dimension used in this prediction method is relatively single, and the accuracy of the prediction results is low. Due to the low forecasting accuracy, the formulation of business goals is not scientific enough...

AI Technical Summary

Problems solved by technology

[0004] The data dimension used in this prediction method is relatively single, and the accuracy of the prediction results is low

Due to the low prediction accuracy, the formulation of business goals is not scientific enough. In terms of inventory management, the low prediction accuracy will lead to a backlog of unsalable products or out-of-stock products, which will eventually cause losses to the enterprise.

[0005] At the same time, the existing methods rely too much on the experience and judgment of enterprise procurement personnel, which requires high procurement experience and judgment.

Moreover, the number of products sold by enterprises is generally more than 10,000, and procurement cannot accurately estimate the sales volume for each product one by one.

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