Multi-Signal Anomaly Detection
Our detection engine monitors dozens of signals simultaneously — download velocity, rating changes, review volume spikes, revenue shifts, ranking jumps, and ad spend surges. Statistical models learn the normal patterns for each title and alert you only when something genuinely unusual happens. No false-alarm fatigue from simple threshold alerts — our models understand seasonality, day-of-week patterns, and category-specific baselines to surface only the anomalies that matter.
Configurable Alerts & Watchlists
Set up alerts for the titles and metrics you care about. Monitor your own portfolio for early warning signs of churn or breakout success. Track competitors for strategic intelligence. Watch entire categories for emerging trends. Alerts are delivered via email, Slack, or in-platform notifications with full context — what changed, by how much, and how it compares to historical norms. Configure sensitivity thresholds to match your team's tolerance for noise.
Root Cause Analysis & Event Correlation
An anomaly is only useful if you understand why it happened. Our engine automatically correlates detected anomalies with potential causes — app updates, price changes, ad campaign launches, competitor actions, seasonal events, and viral social content. The root cause panel shows a timeline of events alongside the metric change, helping you move from detection to explanation to action in minutes instead of days.
Real-Time Monitoring
Continuous scanning of 250K+ titles for statistically significant metric changes.
Smart Alerts, Not Noise
ML models that understand seasonality and baselines — you only hear about what truly matters.
Root Cause Correlation
Automatic event matching tells you why an anomaly happened, not just that it did.