case study

Churn Prediction


Business Impacts


Improvement in model accuracy


Uplift achieved from existing baseline Risk Score Model

Customer Key Facts

  • Location : North America
  • Industry : Insurance

Problem Context

The customer is an American insurance company that provides financial protection to more than 50 million people worldwide. Their financial planning and analysis teams create projections on customer churn at a quarterly level albeit without any statistical understanding. They wanted to maximize their ability to predict groups with a high probability of churn and identify the key reasons that influence the probability of churn.



  • Identifying the right set of control groups
  • Sparse and missing attributes within the data
  • Different churn models had to be created for different demographic levels and quarters

Technologies Used

Google Cloud Compute Engine

Google Cloud Compute Engine

Google Cloud Storage

Google Cloud Storage

Google's BigQuery

Google's BigQuery



Developing a One-Stop Platform to Identify Customer Groups Likely to Churn


Quantiphi developed a churn prediction model and Tableau dashboard that enabled the business to better mitigate churn by developing a sound understanding of the factors responsible.


  • Accurate prediction led to better targeting of customer groups
  • Dashboard was leveraged to democratize model results among both analyst and business user groups to highlight key factors

Thank you for reaching out to us!

Our experts will be in touch with you shortly.

In the meantime, explore our insightful blogs and case studies.

Something went wrong!

Please try it again.