Leverage historical customer data to predict future customer lifetime value (CLV) and segment customers for targeted marketing efforts.
Task: generate a summary of a video. Input: [video title], [video transcript], [length of summary: e.g., 100 words, 200 words] Instruction: summarize the video transcript, focusing on the main topics and key takeaways. The summary should be concise and informative, providing a clear overview of the video's content. Adhere to the specified length constraint.
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This prompt is part of the premium pack "Advanced marketing analytics toolkit".
Identify and analyze the key factors that drive customer lifetime value (CLV) and propose actionable strategies to enhance customer retention and long-term revenue.
Develop a comprehensive framework for predicting user churn in products and outline proactive, data-driven prevention strategies for different risk levels.
Generate a structured outline for developing a churn prediction model, including data sources, methodology, and key metrics.
