Engagement Analytics
Understand how users interact with your website and correlate engagement with performance.
VitalSentinel tracks user engagement metrics and correlates them with performance data, helping you understand how site speed affects user behavior.
How It Works
When engagement tracking is enabled (default), the RUM script captures:
- Scroll behavior - How far users scroll down the page
- Click interactions - User clicks and rage clicks
- Time on page - Active engagement time
- Form interactions - Form abandonment and completion
Dashboard Overview
Navigate to Domain → RUM → Engagement to see:
Engagement Metrics
| Metric | Description |
|---|---|
| Scroll Depth | How far users scroll (25%, 50%, 75%, 90%, 100%) |
| Clicks per Session | Average number of clicks per visit |
| Bounce Rate | Percentage of single-page sessions |
| Rage Click Rate | Percentage of sessions with frustrated clicking |
| Form Abandonment | Percentage of forms started but not completed |
| Avg. Time on Page | Mean time spent on pages |
Scroll Depth Breakdown
See what percentage of users reach each scroll milestone:
| Depth | Meaning |
|---|---|
| 25% | Scrolled past the fold |
| 50% | Halfway down the page |
| 75% | Read most of the content |
| 90% | Near the bottom |
| 100% | Reached the end |
Performance Correlation
The engagement dashboard shows how performance metrics affect user behavior:
Correlation Chart
Compare any performance metric against engagement:
Performance Metrics:
- LCP (Largest Contentful Paint)
- CLS (Cumulative Layout Shift)
- INP (Interaction to Next Paint)
- FCP (First Contentful Paint)
- TTFB (Time to First Byte)
Engagement Metrics:
- Scroll depth
- Time on page
- Bounce rate
- Click rate
Understanding Correlation
The chart shows:
- X-axis - Performance metric values (e.g., LCP in ms)
- Y-axis - Engagement metric values
- Trend line - Overall relationship
Typical patterns:
- Slower LCP → Higher bounce rate
- Better INP → More clicks per session
- Lower TTFB → Longer time on page
Rage Click Detection
Rage clicks are detected when users click rapidly in frustration:
- 3+ clicks within 1 second
- Within a 100px area
High rage click rates indicate:
- Broken links or buttons
- Slow-responding UI elements
- Confusing interface design
Finding Rage Click Sources
- Filter by high rage click rate
- Check which pages have issues
- Review click targets
- Fix unresponsive elements
Form Analytics
Track form interaction:
| Metric | Description |
|---|---|
| Forms Started | Users who began filling a form |
| Forms Completed | Users who submitted successfully |
| Abandonment Rate | Percentage who left without submitting |
Reducing Form Abandonment
- Simplify form fields
- Add progress indicators
- Improve form validation
- Optimize form load time
Filtering Data
Filter engagement data by:
- Date range - Custom time periods
- Page URL - Specific pages
- Device type - Desktop, mobile, tablet
- Browser - Chrome, Firefox, Safari, etc.
Use Cases
Measuring Content Engagement
Track scroll depth to understand:
- Is content engaging enough?
- Do users read full articles?
- Where do users drop off?
Improving Conversion
Correlate performance with actions:
- Faster pages = more sign-ups?
- Page speed affecting purchases?
- Performance impact on engagement?
Identifying UX Issues
Find problems via:
- High rage click rates
- Low scroll depth despite long content
- High form abandonment
- Low time on page
Best Practices
Set Engagement Goals
Define targets for:
- Minimum scroll depth for key pages
- Maximum acceptable bounce rate
- Target time on page
Monitor Trends
Watch for changes:
- Engagement drops after deployments
- Seasonal patterns
- Device-specific issues
Correlate with Performance
Use correlation data to:
- Justify performance improvements
- Quantify speed impact on business
- Prioritize optimization work