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Churn prevention
Catch defecting customers before they become inactive and drive them to continue using the app.
For:
Product growth manager
GrowthOS level:
Marketing
Automate churn prevention with AI
Use an AI scoring model to predict if the app user is likely to stop using the app.
Increase your customer LTV
Many users go dark after their first few app sessions - identify the risky ones and ensure they keep returning for more.
How it works
- Install Intempt SDK to start tracking events in your app
- Create a predictive churn score - select a goal for users who installed the app and stopped using it after a week
- Use the predictive score to create a “High churn segment”
- Create a journey with re-engagement communication sequences that will be served to users who have a high probability of defecting
- View journey analytics and check your conversion goal - Â if users enrolled in the journey made their next order
Features used
- Predictive scoring
- Journeys
- Segments
- Events
Metrics that move
- Average screens per visit
- Daily active users
- Monthly active users
- Customer churn rate
- Net promoter score
- Customer satisfaction score
- Customer retention cost
- Customer health score
Guides - get started
Template
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