Automobile aftermarket spare part sales volume prediction method and system

Abstract

The invention provides an automobile aftermarket spare part sales volume prediction method and system, and relates to the technical field of market prediction. The method comprises the steps: classifying Sku according to the characteristics of automobile aftermarket spare parts; setting different prediction algorithms for different types of Sku for prediction, and obtaining prediction results of each type of Sku; carrying out abnormal value interception processing on all the prediction results to obtain residual prediction results; and according to the residual prediction results, carrying out required level splitting to obtain the prediction result of each category of Sku at the level. According to the method, a set of Sku classification system is constructed aiming at the characteristics of the Sku attributes in the automobile accessory industry and the problem that the Sku cannot be effectively predicted at present, and meanwhile, different prediction algorithms are adopted for different classifications, so that the adaptability is higher, and the future sales volume can be predicted more accurately.

Description

technical field [0001] The invention relates to the technical field of market forecasting, in particular to a method and system for realizing sales forecasting of spare parts in the automotive aftermarket. Background technique [0002] The automobile aftermarket refers to various services surrounding the use of the automobile after the sale of the automobile; in the automobile aftermarket, the market competition in the auto parts industry is becoming increasingly fierce, and Sku (stock inventory unit, extended to the abbreviation of the unified product number, each product Each corresponds to a unique Sku number) There are many types, in order to be able to stock up efficiently and reasonably, it is necessary to reasonably predict the future demand, so as to assist the replenishment personnel to replenish the stock. [0003] At present, there are common problems in the prediction system of auto parts on the market, including: (1) there is no effective prediction of Sku, but ...

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Problems solved by technology

[0003] At present, there are common problems in the prediction system of auto parts on the market, including: (1) there is no effective prediction of Sku, but a static safety stock is simply set; (2) there is no effective classification of Sku, Since different types of Sku may use different prediction algorithms, the prediction accuracy of the prediction system for different auto parts is quite different

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