One significant problem that businesses face is customer attrition. It has become crucial for corporate operations and growth to prevent customer churn and work to keep clients. It is challenging to effectively estimate customer turnover because the majority of the existing projections use a single prediction model. Concentrating on the results of predictions of the models of machine learning, this study proposes a combination of estimating model for customer turnover and performs practical research on the model's efficacy. The combined prediction model outperforms the single customer churn prediction model in terms of accuracy and predictive impact, according to the findings of the predictions. It can also more naturally express the fundamental traits of the churn consumers.
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Customer Churn Prediction using Machine Learning
Semantic Scholar · Computer Science · 2023
Abstract
One significant problem that businesses face is customer attrition. It has become crucial for corporate operations and growth to prevent customer churn and work to keep clients. It is challenging to effectively estimate customer turnover because the majority of the existing projections use a single prediction model. Concentrating on the results of predictions of the models of machine learning, this study proposes a combination of estimating model for customer turnover and performs practical research on the model's efficacy. The combined prediction model outperforms the single customer churn prediction model in terms of accuracy and predictive impact, according to the findings of the predictions. It can also more naturally express the fundamental traits of the churn consumers.