<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Analysing the data generated by the daily operations of enterprises through data mining technology can effectively predict customer loyalty and help enterprise leaders make correct decisions. Therefore, this paper classifies and analyses churn and loyalty of e-commerce customers, and by combining the application foundation of data mining technology in e-commerce customer loyalty prediction, a prediction model of e-commerce customer loyalty based on data mining is constructed. In this model, the local abnormal factor algorithm is used to eliminate the data for cleaning, the XGBoost algorithm is improved by adding penalty coefficient, and the prediction effect of the model is evaluated and compared according to the values of Accuracy, Precision, Recall and F. The results show that the model has high accuracy in predicting customer loyalty, which can accurately extract attributes of users and characteristic information of commodities.</p>
</abstract>

Analysing the data generated by the daily operations of enterprises through data mining technology can effectively predict customer loyalty and help enterprise leaders make correct decisions. Therefore, this paper classifies and analyses churn and loyalty of e-commerce customers, and by combining the application foundation of data mining technology in e-commerce customer loyalty prediction, a prediction model of e-commerce customer loyalty based on data mining is constructed. In this model, the local abnormal factor algorithm is used to eliminate the data for cleaning, the XGBoost algorithm is improved by adding penalty coefficient, and the prediction effect of the model is evaluated and compared according to the values of Accuracy, Precision, Recall and F. The results show that the model has high accuracy in predicting customer loyalty, which can accurately extract attributes of users and characteristic information of commodities.

Research on loyalty prediction of e-commerce customer based on data mining

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Research on loyalty prediction of e-commerce customer based on data mining"}

Analysing the data generated by the daily operations of enterprises through data mining technology can effectively predict customer loyalty and help enterprise...

Research on loyalty prediction of e-commerce customer based on data mining

Online veröffentlicht: 05. Sept. 2022

Seitenbereich: 721 - 732

Eingereicht: 12. Apr. 2022

Akzeptiert: 24. Mai 2022

DOI: https://doi.org/10.2478/amns.2022.1.00020

Schlüsselwörter
Data mining, e-commerce, customer loyalty, XGBoost algorithm

© 2023 Xujie Qin, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on loyalty prediction of e-commerce customer based on data mining

Online veröffentlicht: 05. Sept. 2022

Seitenbereich: 721 - 732

Eingereicht: 12. Apr. 2022

Akzeptiert: 24. Mai 2022

DOI: https://doi.org/10.2478/amns.2022.1.00020

SchlüsselwörterData mining, e-commerce, customer loyalty, XGBoost algorithm

© 2023 Xujie Qin, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Data mining, e-commerce, customer loyalty, XGBoost algorithm