SOLUTIONS POWERED BY AI
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The Challenge.

  • Customer acquisition is much more expensive than customer retention.
  • Customer churn is an important metric to keep track of in insurance companies.
  • Clients exhibit different behavior, making it difficult to accurately predict churn without using advanced analytics.
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The Solution.

  • Designed and built a Machine Learning model to predict the probability of churning for customers on a monthly basis.
  • Created KPIs to capture each client’s service frequency and churn risk over time. ​
  • Divided customers into three churn segments to better customize interactions.
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The Results.

  • Increased customer retention by identifying high-risk clients and putting retention policies in place.
  • Improved customer experience by customizing interactions with different churn segments depending on the risk.
  • Improved understanding of optimal times to call clients within their subscription cycle.
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