This chapter covers
- Identifying customers who are about to churn
- How to handle imbalanced data in your analysis
- How the XGBoost algorithm works
- Additional practice in using S3 and SageMaker
Carlos takes it personally when a customer stops ordering from his company. He’s the Head of Operations for a commercial bakery that sells high-quality bread and other baked goods to restaurants and hotels. Most of his customers have used his bakery for a long time, but he still regularly loses customers to his competitors. To help retain customers, Carlos calls those who have stopped using his bakery. He hears a similar story from each of these customers: they like his bread, but it’s expensive and cuts into their desired profit margins, so they try bread from another, less expensive bakery. After this trial, his customers conclude that the quality of their meals would still be acceptable even if they served a lower quality bread.
Churn is the term used when you lose a customer. It’s a good word for Carlos’s situation because it indicates that a customer probably hasn’t stopped ordering bread; they’re just ordering it from someone else.