Anomaly Detection
Fload automatically monitors your metrics for unusual spikes and drops. When something stands out, you get an alert — so you don't have to stare at dashboards waiting for bad news.
How it works
The anomaly detector runs on your historical data daily. It uses a statistical decomposition approach:
- Decompose the time series into trend, seasonal, and residual components.
- Model the expected range using the trend and seasonal components.
- Compare the actual value to the expected range.
- Flag values that fall outside the expected bounds with sufficient confidence.
The system compares each data point against multiple time horizons:
- Yesterday vs. same day last week
- Yesterday vs. same day last month
- Yesterday vs. same day last year
- 7-day rolling average
- 30-day rolling average
Minimum requirement: 30 days of historical data for reliable detection. New apps may not have anomalies detected until enough history accumulates.
Anomaly types
| Type | Description |
|---|---|
| Surge | Metric significantly higher than expected |
| Decline | Metric significantly lower than expected |
Severity levels
| Severity | Meaning |
|---|---|
| Low | Mild deviation — worth watching |
| Medium | Notable deviation — review soon |
| High | Significant deviation — investigate today |
| Critical | Extreme deviation — immediate attention recommended |
Which metrics are monitored
The anomaly detector watches all major metrics:
- Revenue (proceeds, total revenue)
- Downloads (total downloads, units)
- Subscriptions (active subs, new trials)
- Engagement (sessions, active devices)
- Crashes
- Ad metrics (spend, installs, CPA) when ad connectors are active
Viewing anomalies
Go to Monitoring in the sidebar to see all detected anomalies. You can filter by:
- Status (new, viewed, acknowledged, dismissed)
- Severity (low, medium, high, critical)
- Type (surge, decline)
- App (asset)
- Metric
- Date range
Anomaly statuses
| Status | Meaning |
|---|---|
| New | Just detected, not yet reviewed |
| Viewed | You've opened it |
| Acknowledged | You've seen it and noted it |
| Dismissed | You've marked it as not worth acting on |
Understanding an anomaly
Each anomaly card shows:
- The metric and date
- Actual value vs. expected value
- Deviation percentage
- Trend and seasonal components
- Multi-scale comparisons (vs. last week, last month, etc.)
- AI-generated explanation
- Suggested actions
AI anomaly chat
You can ask the AI chat about anomalies directly: "Why did my revenue spike last Tuesday?" or "What caused the download drop this week?" The AI has access to your anomaly data and can correlate with other metrics to explain what happened.
Notification channels
Anomaly alerts can be sent to:
- Email (configured in notification preferences)
- Slack (when Slack integration is active)
- Discord (when Discord integration is active)
Configure notification preferences in Settings → Notifications.