Author(s)

Jiahui Wang ¹, Anni Ye ¹

Affiliation(s)

¹ School of Mathematics, Hangzhou Normal University, Hangzhou, Zhejiang, 310000, China

Corresponding Author

Jiahui Wang

ABSTRACT

This paper studies the sales strategy of target customers of electric vehicles, and establishes customer mining models for three brands of electric vehicles, so that the sales department can make scientific decisions and realize the rapid development of the enterprise. Firstly, we deal with the main characteristics of the three brands and group the predicted target customers according to different experience brands; Secondly, based on xgboost algorithm, we establish customer mining models for three brands with customer purchase intention as the objective function. The results show that the prediction accuracy of the model for the purchase behavior of three brand target customers reaches 96.83%, 97.21% and 95.00% respectively.

KEYWORDS

Data Cleaning, Customer Mining Model, XGboost Algorithm

CITE THIS PAPER

Jiahui Wang, Anni Ye, Sales Strategy Model of Electric Vehicle Target Customers Based on XGBoost Algorithm. Tourism Management and Technology Economy (2021) 4: 40-43. DOI: http://dx.doi.org/10.23977/tmte.2021.040207.

REFERENCES

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[4] Yang Guijun, Xu Xue, Zhao Fuqiang. User score prediction model based on xgboost algorithm and its application [J]. Data analysis and knowledge discovery, 2019, 3 (01): 118-1

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