Act as a [data scientist specializing in real estate analytics] with [5+ years of experience] in customer behavior prediction. Your task is to analyze a dataset containing [property transaction history], [customer demographics], and [interaction logs] from a real estate platform. Develop a predictive model to identify customers at risk of churn (stopping their engagement with the platform). Include features such as [time since last interaction], [number of property views], and [average time spent on listings]. Provide recommendations on how the platform can implement [personalized retention strategies], such as [targeted email campaigns] or [discounts on premium features], based on the predicted churn risk. Use [Python] and [scikit-learn] for model development, and ensure the solution is scalable for [real-time predictions].