Personal consumption behavior prediction method

Abstract

The invention discloses a personal consumption behavior prediction method. Firstly, personal consumption behavior characteristics and factors influencing consumption are analyzed and extracted. Meanwhile, on the basis of the diversity of factors influencing the consumption behavior, a multi-factor grey correlation degree model is constructed by combining a grey system model, the importance of different influence factors is calculated, main factors influencing the consumption behavior are selected, various influence factors of the consumption behavior can be fully considered, and the problem ofdimension leakage is solved; and on the other hand, a neural network and RFM model matching method is comprehensively used, so that the universality of personal consumption behavior prediction is improved, and the problem of large error of cross-industry personal consumption behavior prediction is solved.

Description

technical field [0001] The invention belongs to the field of analysis and prediction, and in particular relates to a personal consumption behavior prediction method. Background technique [0002] In the past, when researching on consumers' personal consumption behavior, more attention was paid to the consumer behavior itself. Through questionnaires, personal interviews and other forms, information such as demographic data and consumption intentions were collected, so as to be used in research and analysis of consumption. Consumers’ personal consumption behavior; With the development of the big data era, the style of network platforms and consumers’ personal consumption behavior have undergone certain changes, showing a more diversified trend, and the traditional research methods on consumer consumption behavior cannot meet the current needs Changes in consumer consumption habits require that it cannot become an important breakthrough in the prediction of future consumer cons...

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Problems solved by technology

[0002] In the past, when researching on consumers' personal consumption behavior, more attention was paid to the consumer behavior itself. Through questionnaires, personal interviews and other forms, information such as demographic data and consumption intentions were collected, so as to be used in research and analysis of consumption. Consumers’ personal consumption behavior; With the development of the big data era, the style of network platforms and consumers’ personal consumption behavior have undergone certain changes, showing a more diversified trend, and the traditional research methods on consumer consumption behavior cannot meet the current needs Changes in consumer consumption habits require that it cannot become an important breakthrough in the prediction of future consumer consumption behavior

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