This document is a comprehensive guide on how to handle customer loss using Dataiku's predictive analytics. It explains the difference between subscription and non-subscription customer loss and provides a seven-step process for addressing customer loss estimation. These steps include understanding the business, collecting data, preparing and enriching the data, forecasting, visualizing, iterating, and implementing it. The guide also emphasizes the importance of having a well-rounded team, targeting the right audience and making preventing customer loss an orderly process. Introduces the concept of uplift modeling to optimize marketing campaigns and maximize ROI.

What will you learn when you read this document?

• How predictive analytics can help address customer loss
• What are the basic steps to running a successful customer loss forecasting project?
• How to optimize your marketing campaigns using Uplift modeling
• What are common pitfalls to avoid in a customer loss modeling project?
• How can a cross-functional team contribute to effective loss prediction and prevention?”