Business Impact

  • Preventing loss of customer groups

  • Acceleration of business growth with intuitive recommendations

  • 2.7x improvement over the existing model

Customer Key Facts

  • Country : United States
  • Industry : Insurance

Problem Context

The customer, an American insurance company and the largest provider of supplemental insurance in the US, wanted to identify the customer groups that have a higher chance of churning and better understand the reasons behind it.


  • Low volume of data
  • Highly dependent on data for analysis
  • Imbalanced dataset

Technologies Used

Apache Zeppelin
Cloud Spanner
Cloud Compute Engine
Dmlc XGBoost

Identifying customer groups that are likely to churn and the potential reasons behind it


Quantiphi created a model that outperformed the client’s existing model to identify customer groups that are at a high risk of churning out. 

The model suggested reasons for the churn.


  • High retention of customer groups with creation of action list. This helped ascertain the reasons behind increasing rates of churn.
  • Boost in business growth through specially curated instinctive recommendations.
  • 2.7x improvement over the client’s existing model.

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