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SYSTEMS AND METHODS FOR PREDICTING SUBSCRIBER CHURN IN RENEWALS OF SUBSCRIPTION PRODUCTS AND FOR AUTOMATICALLY SUPPORTING SUBSCRIBER-SUBSCRIPTION PROVIDER RELATIONSHIP DEVELOPMENT TO AVOID SUBSCRIBER CHURN
SYSTEMS AND METHODS FOR PREDICTING SUBSCRIBER CHURN IN RENEWALS OF SUBSCRIPTION PRODUCTS AND FOR AUTOMATICALLY SUPPORTING SUBSCRIBER-SUBSCRIPTION PROVIDER RELATIONSHIP DEVELOPMENT TO AVOID SUBSCRIBER CHURN
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机译:用于预测订阅产品的续订用户流失的系统和方法,并自动支持订户订阅提供商关系开发,以避免用户流失
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摘要
In an illustrative embodiment, systems and methods for predicting subscriber churn include machine learning algorithm(s) for classifying the subscriber's decision to stay with the present subscription provider or to switch (churn) to a new provider. The machine learning algorithms may include a logistic regression/neural network for modeling churn propensity in subscribers. The churn risk analysis systems and methods may identify a group of subscribers most likely to churn. Further, the churn risk analysis systems and methods may identify a group of subscribers least likely to churn. The identified subscribers may be presented to a representative of the subscription provider, for example through a user interface.
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