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Data-driven marketing strategy and consumer behavior prediction model construction

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DOI: 10.23977/infse.2024.050210 | Downloads: 1 | Views: 49

Author(s)

Lirong Wan 1, Jiayong Xu 1,2

Affiliation(s)

1 The Graduate University of Mongolia (GUM), Ulaanbaatar, 14200, Mongolia
2 Beijing Polwision Technology Development Co., Ltd., Beijing, 100101, China

Corresponding Author

Jiayong Xu

ABSTRACT

With the advent of the era of big data, the data-driven marketing strategy has gradually become the key to enterprise competition. This paper first introduces the basic concepts of data-driven marketing and its importance, and then details how to build a consumer behavior prediction model. In the process of model building, we used various machine learning and data analysis techniques, including data mining, feature engineering, model selection and optimization, and more. Through example analysis, we show how to use these models to guide the development of marketing strategies, and explore the challenges and prospects of the model in practical application. This paper aims to provide useful reference and guidance for enterprises in the era of data-driven marketing.

KEYWORDS

Data-driven marketing; consumer behavior prediction; machine learning; data mining

CITE THIS PAPER

Lirong Wan, Jiayong Xu, Data-driven marketing strategy and consumer behavior prediction model construction. Information Systems and Economics (2024) Vol. 5: 73-79. DOI: http://dx.doi.org/10.23977/infse.2024.050210.

REFERENCES

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[5] Huang Ming, Chen Ting, Zhu Zhihong. Research on the impact of data-driven marketing strategies on consumer purchasing decisions [J]. Economic longitude, 2019 (17): 100-102.

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