Fighting Churn with Data

6 Relationships between customer behaviors

This chapter covers

• Analyzing relationships between pairs of metrics
• Calculating matrices of correlation coefficients
• Calculating averages of correlated metric scores
• Segmenting customers using averages of metrics
• Discovering metric groups with clustering

For most products and services, analyzing whether individual metrics are related to churn is the beginning but not the end of using your data to reduce churn. This chapter teaches you how to address a common problem: having an overabundance of data available for fighting churn. In the age of big data, some companies collect a lot about their customers. That should make it easier to fight churn with data, right? Not quite.

Many customer behaviors ...