IOP Conference Series Materials Science and Engineering · 2020 · 22 citations · 7 references
BusinessBusiness AnalyticsData ScienceBig Data AnalyticsData AnalyticsPredictive AnalyticsChurn AnalysisChurn ManagementCustomer Behavior AnalyticsCustomer Churn PredictionCustomer SegmentationSegmentation StrategyChurn AnalyticsChurn DetectionChurn ModelingChurn Prediction In TelecommunicationsCustomer Churn ModelingPiecewise RegressionPrediction ModelsUser Segmentation
Abstract Customer churn will cause huge losses to the communication company and has become a real problem. The article uses big data analysis technology to analyse user characteristics of churn customer historical information data, establish a churn prediction model, find users with a higher risk of churn in advance, develop targeted strategies, and carry out a series of retention activities to retrieve them. The paper presents a strategy of user segmentation and piecewise regression to find the highly relevant fields and divide the customers into different groups based on these fields, and then use regression analysis to establish the prediction models for different groups. Online test shows that the model can effectively identify most of the lost customers, effectively reduce the user off-network rate, and improve efficiency and effectiveness than traditional methods.
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Customer churn prediction in telecommunication industry using data certainty
Adnan Amin, Feras Al‐Obeidat, Babar Shah et al. · Journal of Business Research · 2018 · 247 citations