Predicting and Preventing Churn with Customer Health Scoring

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Ed Powers is a Principal Consultant at Service Excellence Partners, where he helps companies take an enterprise-wide approach to addressing churn. He’s previously led customer success at simPRO, a field service management software company, and InteiliSecure, a managed security services provider. Through his consulting work, he can help with customer success assessment, financial modeling, CS team training, and statistical analysis.

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Questions covered in this guide:

What is a customer health score?

What is it used for?

Why is predictive accuracy important?

How does adopting a more analytical approach help you move from reactive to proactive to preventative when it comes to churn?

What types of data can go into health scores?

What’s a lightweight way for early-stage companies to get started?

When do you need to get more sophisticated in your approach?

<pWhat would the steps be to build a more sophisticated, regression-based model?

How many variables should you include?

What tech tools do you need to run the analysis and operationalize the score?

Who’s responsible for developing and updating the customer health score?

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