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Increase LTV and Decrease User Drop-off With Predictive Churn

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Predictive Churn


An average app loses 77% of its active daily users in the first 3 days


95% of new, opt-in app users churn within the first 90 days

Kochava Predictive Churn Modeling helps brands determine the likelihood a user will churn based on a proprietary algorithm. Kochava links your users to behaviors and characteristics shown most related to churn or conversion, giving them a statisically reliable churn score.

Analyze trends

Analyze trends in customer behavior correlated across audiences, behavioral events, messages, and campaigns.

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Increase ROI

Identify low-quality users more likely to churn, and reengage them to prevent drop-off, increase ROI, and optimize marketing spend.

Boost retention

Increase retention by leveraging detailed insights into behavior to lower churn rate. Engage current users more effectively and tailor future marketing efforts by excluding those who exhibit behaviors similar to past users.


Kochava’s predictive churn scores provide 90% accuracy

(13% above the average modeling system)

Grow user engagement

Leverage each churn score to reengage users at risk with relevant messaging through owned media. Grow user engagement and drive them further down the funnel to increase user lifetime value (LTV).

Automatically segment audiences

Automatically segment audiences according to churn-likelihood scores and syndicate “Medium-high” and/or “High” likelihood segments to activate with your most trusted reengagement partners for focused targeting campaigns to drive retention.


Learn more about predictive churn modeling and ways to apply this intelligence technology to your analytics suite.

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1Heslop, Brent. “By 2030, Each Person Will Own 15 Connected Devices — Here’s What That Means for Your Business and Content,” MarTech Advisor. 4 Mar 2019. Accessed 4 April 2020.