Churn IntelligenceCuoral is an AI agent for silent churn that autonomously detects disengagement patterns, predicts customer risk in real-time, learns from behavioral signals, and tells you exactly why customers leave - so you can stop it before it happens.
Key FeaturesPowered by AI and behavioral science, our platform gives you the insights and early warnings you need to retain more customers.
Identify customers at risk of churning before they leave. Our AI analyzes behavioral patterns, engagement drops, and usage trends to detect silent churn signals.
Every customer gets a dynamic risk score based on hundreds of behavioral signals. Track engagement, feature adoption, and sentiment to predict churn probability.
Get instant alerts when customers encounter errors, bugs, or UX friction. Our system monitors every interaction to identify pain points.
Comprehensive health scores combining product usage, support sentiment, payment history, and engagement metrics.
Visualize complete customer journeys from signup to present. Identify drop-off points and patterns that correlate with churn.
Actionable dashboards showing churn forecasts, cohort analysis, retention trends, and revenue impact for data-driven decisions.
How It WorksOur intelligent system works 24/7 to protect your revenue
Cuoral tracks every customer interaction, feature usage, support ticket, and behavioral signal across your product in real-time.
Machine learning algorithms identify patterns and anomalies that indicate churn risk, comparing each customer against historical data.
Customers receive dynamic risk scores and your team gets instant alerts when accounts enter high-risk states.
Armed with insights, engage at-risk customers with targeted campaigns, support outreach, or product improvements.
It is the practice of combining customer activity, account context, and outcomes to understand who may need attention and why. It turns separate usage, support, and engagement signals into information a team can investigate and act on.
Potential indicators include declining activity, reduced use of important features, repeated unresolved support issues, lower engagement, or changes around payment and renewal. The right indicators depend on the product and customer segment.
No. A score estimates risk from available signals; it is not certainty. Teams should inspect the underlying context and use scores to prioritize human review rather than make consequential decisions automatically.
