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Customer churn

As explained in Delivering Machine Learning Projects: From design to deployment

Customer churn is the ending or loss of a customer's relationship with a business.

Customer churn is the loss of a customer relationship. For a business trying to retain customers, identifying people at high risk of churning can help target interventions before they leave. section 3.5

Bike retailer pre-sales opportunity

A bike retailer wants to retain customers and increase their spending rather than invest in acquiring new ones. A proposed application would use customer data to identify churn risk and suggest interventions. Before committing to delivery, record insufficient customer behavior history as a project risk: past data cleansing may have left too little history. section 3.5

How Delivering Machine Learning Projects: From design to deployment covers it

How deep it goes
Describes identifying at-risk customers and suggesting interventions, but gives no churn formula, model design, or evaluation procedure.
Examples
Uses a bike retailer’s retention proposal and a risk register entry about insufficient customer behavior history.
What you can do after
Evaluate/understand it as a potential data application and flag insufficient customer history as a delivery risk.
How it connects
Links customer churn to customer retention, customer behavior history, and project risk management.

Also explained in

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Delivering Machine Learning Projects: From design to deployment. The section links point to the parts of the book it draws on.