Churn prediction and customer retention strategies for OTT platforms using a hybrid AI model

User retention is of utmost importance for new platforms in the extremely competitive OTT sector. The present paper describes an end-to-end system predicting user churn from text review data and offering actionable retention recommendations enabled by generative AI. Utilizing data web-scraped from OTT websites on the Play Store, the system applies high-level NLP, sentiment analysis, and deep learning architectures (LSTM, CNN-BiLSTM) to predict the level of churn risk. A dynamic dashboard presents insights, and retention recommendations are dynamically generated. Optional plug-and-play modules, such as an API-based movie recommendation assistant and a hybrid recommendation engine, augment user engagement. This domain-aware, scalable solution makes churn prediction a proactive customer loyalty system.