Segwise

Automatically identifies and clusters players into distinct behavioral cohorts using machine learning without requiring manual rule definition. Analyzes player behavior patterns to discover profitable segments that would be difficult to identify through manual analysis.

Predicts which players are at risk of leaving the game before they churn, enabling proactive retention interventions. Uses historical player behavior to identify early warning signals of churn.

Seamlessly connects with major game engines (Unity, Unreal) and analytics platforms (Firebase) to automatically ingest player data without manual data pipeline setup. Eliminates friction in getting game data into the analytics system.

Analyzes player segments to identify which groups are most valuable and how to optimize pricing, offers, and monetization strategies for each cohort. Provides data-driven recommendations for maximizing revenue from different player types.

Creates and executes targeted engagement campaigns automatically based on player segment characteristics and predicted behaviors. Personalizes messaging, offers, and timing for different cohorts without manual campaign setup.

Predicts the total revenue each player will generate over their lifetime and identifies optimization opportunities to increase LTV. Helps studios understand player value distribution and focus resources on high-potential players.

Generates detailed reports and dashboards showing characteristics, behaviors, and metrics for each identified player cohort. Provides visual insights into how different segments behave and perform.

Continuously monitors and tracks player behavior in real-time, updating segment assignments and risk scores as players engage with the game. Enables dynamic, responsive analytics that reflect current player state.