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USE CASE

Healthcare Customer Churn Prediction

Objective

Customer churn is a challenge faced by all organizations. The customer churn prediction solution, a robust solution as the problem involves complex data over time and interactions between different customer behaviours that can be difficult for people to identify. The AI solution can look at a variety of data, including new data sources, and at relatively complex interactions between behaviours and compared to individual history to determine risk. The solution can also be used to recommend the best offer that will most likely retain a valuable customer. In addition, it can identify the reasons why a customer is at risk and allow the institution to act against those areas for the individual customer.

Outcome

With aid of this solution, one can accurately predict churn and direct its retention effort to those customers who have a higher risk of discontinuing. The company also has access to what drives churn and, with this information, can lower the churn rate by improving the customer experience.

Business Value

H2O.ai, created an application that has a live updating dashboard of customer churn predictions. The application also provides visualizations of historic percent of customer churn per state and historic churn by monthly bill amounts

can examine likelihood to churn for a specific customer. The solution also enables identification and area dos improvement where customer service could be lacking.

H2O's AI and Data Approaches

This solution is powered by the H2O AI Cloud Driverless AI AutoML, H2O-3, and H2O.ai Wave. The data science approaches include genetic algorithm, advanced feature engineering, regression algorithms, GLM, GBM, XGBoost, ensemble stacking, and various machine learning interpretability algorithms.

 

Resources

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