Identify and retain users at risk of churn by predicting user behavior over the first 3 weeks after installation.
Churn Predictions categorize users into groups based on churn probability >95%, 75-95%, 50-75%, and <50%, enabling targeted retention and re-engagement strategies such as personalized push notifications and incentives. The model incorporates the 3 sigma rule, ensuring an accuracy rate exceeding 90%.
In a quest to find the best possible optimization strategy, Yandex Games ran an A/B test to compare two methods: a traditional one, optimizing based on the users’ behavior in the app within the first few minutes, and one based on the topLTV parameter.
The predictive model attracted more engaged users without changing their cost — an incredible result that helped Yandex Games refine its marketing strategy and increase user engagement.
Tailor your marketing campaigns to attract even more users with higher long-term value based on topLTV parameters.
Use churn predictions to identify when and why users might leave a game and minimize those risks.
Optimize your monetization strategy by observing highest-paying users and identifying the channels they came from.
Segment customers based on their spending habits and personalize your marketing campaigns for high-value customers.
Forecast demand for certain products and optimize your inventory and marketing efforts based on customer preferences.
Identify users who abandon their shopping carts and implement targeted strategies like personalized reminders or discounts.
Determine the optimal pricing strategy for subscription-based apps based on LTV data and adjust pricing tiers.
Personalize content recommendations for your topLTV customers to grow user satisfaction and subscription duration.
Identify patterns that precede user cancellations and implement proactive measures to reduce churn.