In the context of a Professional Machine Learning Engineer's role in 'Translating business challenges into ML use cases', consider the following scenario: A retail company wants to reduce customer churn by predicting which customers are most likely to stop using their services. The company has a large amount of historical customer data but is concerned about the cost and scalability of implementing a machine learning solution. Given these constraints, what is the BEST approach for the engineer to take to create value for the business through machine learning? Choose the two most appropriate options.