Customer Churn Prediction using Machine Learning: Subcription Renewal on OTT Platforms

Dr RAMA DEVI ODUGU, Sai Krishna Pothini, Mulpuru Prasanna Kumari, Sowjanya. V, Uppalapati Naga Sai Charan
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引用次数: 1

Abstract

The goal of predicting subscriptions for OTT (Over-The-Top) platforms using machine learning is to devise a model which can accurately predict whether a customer will continue using this platform or not. This information is important for OTT companies to understand and optimize their marketing and retention efforts. Relevant data, such as customer demographics and viewing habits, is collected and analyzed to train the model. This process involves cleaning the data, selecting important features, and training a machine learningmodel. The model is then tested and validated using performance metrics. In short, this problem requires a comprehensive understanding of customer behavior and the use of machine learning to predict subscription decisions. The results can provide valuable insights for OTT companies to improve their customer understanding and retention efforts.
使用机器学习预测客户流失:OTT平台的订阅续订
使用机器学习预测OTT (over - top)平台订阅的目标是设计一个模型,该模型可以准确预测客户是否会继续使用该平台。这些信息对于OTT公司理解和优化他们的营销和留存工作非常重要。相关数据,如客户人口统计和观看习惯,被收集和分析,以训练模型。这个过程包括清理数据、选择重要特征和训练机器学习模型。然后使用性能指标对模型进行测试和验证。简而言之,这个问题需要全面了解客户行为,并使用机器学习来预测订阅决策。研究结果可以为OTT公司提供有价值的见解,以提高他们对客户的理解和保留努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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