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Customer churn prediction based on customer value and user evaluation emotions in online marketing

Huanan Mo

International Journal of Web Based Communities2025https://doi.org/10.1504/ijwbc.2025.145136article
ABDC C
Weight
0.37

What the paper says

In order to improve the accuracy and usefulness of the churn prediction model, the core elements of the research content were designed to include collecting data on customer purchase behaviour and reviews, quantifying and analysing customer value, analysing customer sentiment in reviews, and combining customer value factors and review sentiment factors in the model. The results of the study show that the model performs best on different indicators, and the area of the main characteristic curve is the largest, which is significantly higher than that of the traditional model. Its hit rate, coverage rate and improvement coefficient also perform well. At the same time, when the sample size increases, the improvement coefficient increases the most, reaching 0.41. In conclusion, the model performs well in customer churn prediction, and it can provide certain reference value for the research field of customer churn prediction.

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https://doi.org/https://doi.org/10.1504/ijwbc.2025.145136

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@article{huanan2025,
  title        = {{Customer churn prediction based on customer value and user evaluation emotions in online marketing}},
  author       = {Huanan Mo},
  journal      = {International Journal of Web Based Communities},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijwbc.2025.145136},
}

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Customer churn prediction based on customer value and user evaluation emotions in online marketing

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.