Abstract
Enterprises have vast amounts of customer behavior data in the era of big data. How to take advantage of these data to evaluate custom forfeit risks effectively is a common issue faced by enterprises. Most of traditional customer churn predicting models ignore customer segmentation and misclassification cost, which reduces the rationality of model. Dealing with these deficiencies, we established a research model of customer churn based on customer segmentation and misclassification cost. We utilized this model to analyze customer behavior data of a telecom company. The results show that this model is better than those models without customer segmentation and misclassification cost in terms of the performance, accuracy and coverage of model.
Highlights
With the development of information management, the volume of data customer information and consumer behavior data owned by enterprise is increasing rapidly
Based on the limitations of previous model and the future research aspects, this paper proposes a research model of churn prediction based on customer segmentation and misclassification cost factor
In the context of big customer behavior data, a customer churn prediction based on customer segmentation and misclassification cost is developed
Summary
With the development of information management, the volume of data customer information and consumer behavior data owned by enterprise is increasing rapidly. Researcher proposed that distinguishing, perceiving and analyzing consumer behavior by data mining could optimize the deployment of business operations, but improve the efficiency of consumer management [1]-[3]. (2015) Research Model of Churn Prediction Based on Customer Segmentation and Misclassification Cost in the Context of Big Data. As the competitiveness of the enterprise market would be severely weakened by churn, most companies will apply churn prediction through data mining to improve customer maintenance. How to use vast amounts of customer data effectively and improve the performance of churn prediction model is concerned by companies. Based on the limitations of previous model and the future research aspects, this paper proposes a research model of churn prediction based on customer segmentation and misclassification cost factor. The proposed model will be applied to an actual customer management case of a telecommunications operation
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