Anomaly Detection
AI-powered automatic detection of unusual patterns in your campaign performance with real-time alerts and actionable insights.
Intermediate10 min readUpdated 2025-01-02
Anomaly Detection uses AI to automatically monitor your campaigns and alert you when something unusual happens, helping you catch issues before they impact performance.
Overview
Navigate to Analytics > Anomalies to access the anomaly detection dashboard.
| Feature | Description |
|---|---|
| Automatic Monitoring | AI continuously analyzes your campaign data |
| Real-time Alerts | Instant notifications for critical issues |
| Severity Classification | Issues ranked by importance |
| Actionable Insights | Specific suggestions for each anomaly |
| Resolution Tracking | Monitor and close resolved issues |
How It Works
Statistical Analysis
The AI uses advanced statistical methods to detect anomalies:
| Method | Description |
|---|---|
| Z-Score Analysis | Measures how far a value deviates from the mean |
| Historical Comparison | Compares current data to past patterns |
| Trend Detection | Identifies sudden changes in trends |
| Threshold Monitoring | Alerts when metrics cross defined limits |
Detection Process
| Step | What Happens |
|---|---|
| 1 | AI collects your campaign metrics continuously |
| 2 | Data is compared against historical baselines |
| 3 | Statistical models identify significant deviations |
| 4 | Anomalies are classified by type and severity |
| 5 | Alerts are generated with suggested actions |
Anomaly Types
Spend Anomalies
| Type | Description | Example |
|---|---|---|
| Spend Spike | Unexpected increase in spending | Daily spend 200% above normal |
| Spend Drop | Unusual decrease in spending | Ads stopped delivering |
| Budget Depletion | Budget exhausted faster than expected | Monthly budget used in 2 weeks |
Performance Anomalies
| Type | Description | Example |
|---|---|---|
| CTR Drop | Click-through rate declining | CTR dropped from 2% to 0.5% |
| Conversion Decline | Fewer conversions than expected | Conversions down 50% week-over-week |
| ROAS Alert | Return on ad spend issues | ROAS fell below 1.0x |
| CPC Spike | Cost per click increasing | CPC doubled overnight |
Delivery Anomalies
| Type | Description | Example |
|---|---|---|
| Low Delivery | Ads not reaching expected audience | Impressions 80% below forecast |
| Frequency Spike | Same users seeing ads too often | Frequency jumped to 8+ |
| Reach Plateau | No new users being reached | Reach unchanged for 3 days |
Severity Levels
Critical (Red)
| Indicator | Action Required |
|---|---|
| Color | Red background/border |
| Icon | Alert triangle |
| Urgency | Immediate attention needed |
| Impact | Significant budget or performance risk |
Examples of critical anomalies:
- Spend exceeding budget by 50%+
- ROAS dropped below 0.5x
- Campaign stopped delivering entirely
- Conversion rate dropped to near zero
Warning (Amber)
| Indicator | Action Required |
|---|---|
| Color | Amber/yellow background |
| Icon | Warning icon |
| Urgency | Review within 24 hours |
| Impact | Potential performance issue |
Examples of warning anomalies:
- CTR declining steadily
- CPC increased by 30%+
- Frequency exceeding 4.0
- ROAS trending downward
Info (Blue)
| Indicator | Action Required |
|---|---|
| Color | Blue background |
| Icon | Info icon |
| Urgency | Awareness only |
| Impact | Minor or expected variation |
Examples of info anomalies:
- Weekend performance variation
- Seasonal pattern detected
- Minor metric fluctuation
- Expected budget pacing change
Anomaly Dashboard
Summary Cards
| Card | Shows |
|---|---|
| Total Anomalies | All detected anomalies |
| Active | Unresolved issues needing attention |
| Acknowledged | Issues you've reviewed |
| Resolved | Closed issues |
Filters
| Filter | Options |
|---|---|
| Severity | All, Critical, Warning, Info |
| Status | All, Active, Acknowledged, Resolved, Ignored |
| Type | Spend, Performance, Delivery |
| Campaign | Filter by specific campaign |
| Date Range | When anomaly was detected |
Anomaly List
Each anomaly card displays:
| Element | Description |
|---|---|
| Title | Short description of the issue |
| Severity Badge | Color-coded severity level |
| Campaign | Affected campaign name |
| Metric | Which metric is affected |
| Deviation | How far from expected (%) |
| Detected At | When the anomaly was found |
| Suggested Actions | AI recommendations |
Managing Anomalies
Acknowledge
| Action | Effect |
|---|---|
| Click | "Acknowledge" button |
| Status | Changes to "Acknowledged" |
| Purpose | Indicates you've seen the issue |
| Monitoring | Continues tracking |
Use acknowledge when:
- You've reviewed the anomaly
- Investigation is in progress
- No immediate action needed
Resolve
| Action | Effect |
|---|---|
| Click | "Resolve" button |
| Status | Changes to "Resolved" |
| Purpose | Marks issue as fixed |
| Monitoring | Archived for reference |
Use resolve when:
- Root cause has been fixed
- Performance has returned to normal
- Issue was a false positive you verified
Ignore
| Action | Effect |
|---|---|
| Click | "Ignore" button |
| Status | Changes to "Ignored" |
| Purpose | Dismisses false positives |
| Monitoring | Similar anomalies may still trigger |
Use ignore when:
- Expected variation (e.g., holiday)
- Known business change
- False positive detected
View Campaign
Click to navigate directly to the affected campaign for investigation.
Summary & Insights
Trend Analysis
The summary shows your anomaly trend:
| Trend | Meaning |
|---|---|
| Improving | Fewer anomalies over time |
| Stable | Consistent anomaly rate |
| Worsening | Increasing anomalies |
Top Affected Campaigns
See which campaigns have the most issues:
| Column | Description |
|---|---|
| Campaign Name | Name of affected campaign |
| Anomaly Count | Number of anomalies |
| Most Common Type | Predominant issue type |
Distribution Charts
| Chart | Shows |
|---|---|
| By Severity | Critical vs Warning vs Info |
| By Type | Spend vs Performance vs Delivery |
| By Status | Active vs Resolved |
Best Practices
Daily Monitoring
| Action | Benefit |
|---|---|
| Check anomalies daily | Catch issues early |
| Prioritize critical alerts | Protect budget and performance |
| Review trends weekly | Identify patterns |
Response Strategy
| Severity | Response Time |
|---|---|
| Critical | Within 1 hour |
| Warning | Within 24 hours |
| Info | Weekly review |
False Positive Management
| Situation | Action |
|---|---|
| Expected seasonal change | Ignore with note |
| Known business event | Acknowledge |
| True issue confirmed | Investigate and resolve |
Integration Tips
- Combine with Realtime Monitoring for live tracking
- Use Predictions to anticipate issues
- Review Creative Intelligence for fatigue-related anomalies
Recap
Anomaly Detection provides:
- Automatic Monitoring - AI watches your campaigns 24/7
- Smart Classification - Issues ranked by severity
- Actionable Alerts - Specific suggestions for each issue
- Workflow Management - Track issue resolution
- Trend Analysis - Understand patterns over time
Enable anomaly detection to catch issues before they impact your bottom line.
Key Takeaways
- 1Automatic detection of unusual campaign patterns
- 2Real-time alerts for critical issues
- 3AI-powered analysis using statistical methods
- 4Actionable suggestions for each anomaly
- 5Track and manage anomaly resolution
Frequently Asked Questions
How quickly are anomalies detected?
Anomalies are typically detected within minutes of occurring. The AI continuously monitors your campaign data and triggers alerts as soon as significant deviations are identified.
Can I customize anomaly thresholds?
Currently, thresholds are automatically calculated based on your historical data. The AI adapts to your specific patterns and sets appropriate sensitivity levels.
What causes false positives?
False positives can occur during known events like sales, holidays, or business changes. Use the Ignore function for expected variations. The AI learns from your feedback over time.
Do resolved anomalies affect future detection?
Yes, resolved anomalies help train the AI. When you confirm true issues or dismiss false positives, the system becomes more accurate for your specific patterns.
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