Churn prevention

Catch defecting customers before they become inactive and drive them to continue using the app.

Product growth manager
GrowthOS level:

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 -  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


Join the waitlist

Over 150 internet businesses are on our. Join them, and after your trial period, receive $500 in credits.