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A music recommendation model shipped last month and repeat listening fell. Diagnose it.

Focus on identifying potential issues with the music recommendation model that could lead to decreased repeat listening. Start by analyzing the model's algorithm and data inputs—consider whether the recommendations are relevant and personalized enough for users. Explore user feedback and engagement metrics to determine if there was a change in user behavior or preferences since the model's launch. Additionally, evaluate the impact of external factors, such as changes in the music catalog or user interface, that might have influenced repeat listening. Conclude with actionable recommendations to address the identified issues and improve user retention.

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