Consumer consumption behavior oriented time-lapse data analysis model establishment method

Abstract

The invention discloses a consumer consumption behavior oriented time-lapse data analysis model establishment method. Through establishing a time-lapse based algorithm model, the consumption data are subjected to quantification analysis in combination with the forgetting curve characteristics of people, so that the interests and tendency of consumer consumption in a long-term range can be obtained, meanwhile, the group consumer preference and the individual classification preference can be subjected to comprehensive analysis, so that the drift and drift rate of consumption tendency can be subjected to quantizable prediction. Through the establishment and implementation of the establishment method of the analysis model, the interests and tendency of consumer consumption can be subjected to effective and reasonable analysis, which helps businessmen to make effective responses and adjustments on future market strategies better so as to enhance the market competitiveness.

Description

technical field [0001] The method for establishing a time-lapse data analysis model oriented to user consumption behavior in the present invention is mainly to model and analyze user consumption data, and to infer the user's long-term consumption interest and trend through the establishment method of the analysis model based on time-lapse , the realization of this model involves data trend modeling, forgetting curve analysis, statistical algorithms and other fields. Through the establishment and realization of the establishment method of this analysis model, the interest and trend of user consumption can be effectively and reasonably analyzed, and there is It is beneficial for merchants to better respond and adjust effectively to future market strategies to enhance market competitiveness. Background technique [0002] At present, the competition in the retail industry is fierce. With the rapid development of Internet e-commerce, the traditional retail industry is gradually p...

AI Technical Summary

Problems solved by technology

[0003] 1. For the index analysis of the data itself, it can only reflect the index matching situation reflected by the data itself. There is no standard method for establishing an analysis model based on time-lapse, and it is impossible to conduct an effective analysis and prediction of consumer interest and tendency

[0004] 2. The traditional analysis is based on the analysis of time dimension blocks, and there is no method for establishing a continuous analysis model

[0005] 3. There is no comprehensive analysis combined with the characteristics of the person's own forgetting curve, but only the index analysis through the data itself

The practical reference value of the analysis results is not great

[0006] 4. There is no standard method for establishing a standard analysis model for the tendency of long-term consumption interests, the degree of standardization and referenceability are very low, and the analysis results do not have practical application value

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