From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.
The rise of machine learning (almost sounds like "rise of the machines"?) and applications of statistical methods to marketing have changed the field forever. Machine learning is being used to optimize customer journeys which maximize their satisfaction and lifetime value. This course will give you the foundational tools which you can immediately apply to improve your company’s marketing strategy. You will learn how to use different techniques to predict customer churn and interpret its drivers, measure, and forecast customer lifetime value, and finally, build customer segments based on their product purchase patterns. You will use customer data from a telecom company to predict churn, construct a recency-frequency-monetary dataset from an online retailer for customer lifetime value prediction, and build customer segments from product purchase data from a grocery shop.
The rise of machine learning (almost sounds like "rise of the machines"?) and applications of statistical methods to marketing have changed the field forever. Machine learning is being used to optimize customer journeys which maximize their satisfaction and lifetime value. This course will give you the foundational tools which you can immediately apply to improve your company’s marketing strategy. You will learn how to use different techniques to predict customer churn and interpret its drivers, measure, and forecast customer lifetime value, and finally, build customer segments based on their product purchase patterns. You will use customer data from a telecom company to predict churn, construct a recency-frequency-monetary dataset from an online retailer for customer lifetime value prediction, and build customer segments from product purchase data from a grocery shop.
