Research on Marketing Prediction Model Based on Markov Prediction
Author(s) -
Haiying Chen,
Haiyan Chen,
Wei Zhang,
Chaodan Yang,
Hongxiu Cui
Publication year - 2021
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1155/2021/4535181
Subject(s) - markov chain , computer science , markov model , product (mathematics) , variable (mathematics) , order (exchange) , markov process , econometrics , operations research , marketing , management science , machine learning , economics , statistics , mathematics , business , finance , mathematical analysis , geometry
Many activities in modern business marketing management are random and repetitive. The marketing effect is constantly influenced by a variety of factors such as changing market supply and demand, customers’ purchase intentions, and national financial policy. As a result, Markov analysis can be used to analyze the status and trend of some variables, that is, to predict the future status and trend of a variable based on its current status and trend, in order to forecast possible changes in the future and take appropriate countermeasures. The mathematical model of product marketing prediction is presented in this paper by establishing the probability matrix of product state transition and analyzing and calculating with the Markov chain, resulting in a practical and reliable theoretical basis for economic prediction. After using the Markov analysis method, a suitable mathematical model can be created based on market investigation and statistics, which is extremely useful for making reasonable predictions about the market’s future development trend and improving marketing effectiveness.
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