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Churn risk & prevention
Utilize predictive analytics to identify users at risk of disengaging or churning. Implement tailored retention strategies to maintain their interest and loyalty.
For:
Marketing specialist
Early identification of at-risk users
Predict which users will likely churn before they disengage completely.
Targeted retention strategies
Implement personalized campaigns to re-engage at-risk users.
Increased customer lifetime value
Retaining users longer by addressing their needs and concerns promptly.
Improved user experience
Enhance satisfaction by providing timely and relevant interactions
How it works
- Set up data collection
- Create a likelihood model
- Segment users based on likelihood scores
- Use these categories to create segments: high risk, medium risk, low risk
- Design and implement retention strategies for high risk, medium risk, low risk
- Monitor and adjust strategies.
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Features used
Metrics that move
- Reduction in customer churn rate
- Increase in customer lifetime value
- Enhanced engagement metrics through targeted retention strategies
- Improved predictive accuracy for identifying at-risk users
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