Machine Learning for Marketing in Python

In this chapter, you will explore the basics of machine learning methods used in marketing. You will learn about different types of machine learning, data preparation steps, and will run several end to end models to understand their power.

In this chapter you will learn churn prediction fundamentals, then fit logistic regression and decision tree models to predict churn. Finally, you will explore the results and extract insights on what are the drivers of the churn.

In this chapter, you will learn the basics of Customer Lifetime Value (CLV) and its different calculation methodologies. You will harness this knowledge to build customer level purchase features to predict next month's transactions using linear regression.

This final chapter dives into customer segmentation based on product purchase history. You will explore two different models that provide insights into purchasing patterns of customers and group them into well separated and interpretable customer segments.