tomevault-io Analytics Review Skill
Analyze website performance with Pirsch using the Overview-Drill Down-Insights pattern.
Phase 1: OVERVIEW (High-Level Metrics)
List Available Domains
mcp__pirsch__pirsch_list_domains({})
Get Cached Overview
Quick snapshot of key metrics:
mcp__pirsch__pirsch_overview({
domainId: "<domain-id>"
})
Get Detailed Totals
mcp__pirsch__pirsch_total({
domainId: "<domain-id>",
from: "2025-01-01",
to: "2025-01-31"
})
Returns:
- Visitors
- Views
- Sessions
- Bounces
- Bounce rate
- Conversion rate
Get Growth Metrics
mcp__pirsch__pirsch_growth({
domainId: "<domain-id>",
from: "2025-01-01",
to: "2025-01-31"
})
Check Real-Time Activity
mcp__pirsch__pirsch_active({
domainId: "<domain-id>",
seconds: 600 // Last 10 minutes
})
Phase 2: DRILL DOWN (Detailed Analysis)
Visitor Time Series
mcp__pirsch__pirsch_visitors({
domainId: "<domain-id>",
from: "2025-01-01",
to: "2025-01-31",
scale: "day" // day, week, month
})
Top Pages
mcp__pirsch__pirsch_pages({
domainId: "<domain-id>",
from: "2025-01-01",
to: "2025-01-31",
limit: 20,
includeAvgTimeOnPage: true
})
Traffic Sources (Referrers)
mcp__pirsch__pirsch_referrers({
domainId: "<domain-id>",
from: "2025-01-01",
to: "2025-01-31",
limit: 20
})
UTM Campaign Analysis
// By source
mcp__pirsch__pirsch_utm({
domainId: "<domain-id>",
from: "2025-01-01",
to: "2025-01-31",
dimension: "source"
})
// By medium
mcp__pirsch__pirsch_utm({
domainId: "<domain-id>",
dimension: "medium"
})
// By campaign
mcp__pirsch__pirsch_utm({
domainId: "<domain-id>",
dimension: "campaign"
})
Phase 3: INSIGHTS (Comparative Analysis)
Period Comparison
Compare two time periods:
mcp__pirsch__pirsch_compare({
domainId: "<domain-id>",
from: "2025-01-01",
to: "2025-01-31",
compareFrom: "2024-12-01",
compareTo: "2024-12-31",
scale: "day"
})
Returns:
- Visitor trends for both periods
- Delta values (absolute change)
- Growth percentages
Report Formatting
Dashboard Summary
## Website Analytics Dashboard
verygoodplugins.com | January 2025
### Key Metrics
| Metric | Value | vs Last Month |
|--------|-------|---------------|
| Visitors | 12,450 | +21.7% |
| Pageviews | 45,230 | +17.6% |
| Bounce Rate | 42.3% | -2.8pp |
| Avg Duration | 2m 34s | +16.7% |
### Top Pages
1. /pricing - 4,230 views
2. /features - 3,890 views
3. /blog/getting-started - 2,450 views
4. /docs/api - 1,890 views
5. /about - 1,230 views
### Top Referrers
1. google.com - 5,230 visitors
2. twitter.com - 1,890 visitors
3. github.com - 1,450 visitors
4. reddit.com - 890 visitors
### UTM Sources
1. newsletter - 2,340 visitors
2. twitter-organic - 1,230 visitors
3. google-ads - 890 visitors
Trend Analysis
## Weekly Trend Analysis
Week 1: 2,890 visitors
Week 2: 3,120 visitors (+8%)
Week 3: 3,450 visitors (+11%)
Week 4: 3,780 visitors (+10%)
Overall trend: Steady growth, averaging +9.7% week-over-week
Common Analysis Scenarios
Traffic Spike Investigation
- Get daily visitors to identify the spike date
- Check referrers for that date range
- Check UTM sources for campaign attribution
- Review top pages to see what content drove traffic
Campaign Performance
- Filter by UTM campaign name
- Compare visitors, bounce rate, and time on site
- Check which pages campaign traffic landed on
- Compare to organic traffic for baseline
Content Performance
- Get top pages by views
- Check average time on page
- Identify high-bounce pages for optimization
- Find underperforming content
Best Practices
Do
- Start with overview before drilling down
- Use appropriate date ranges for context
- Compare periods of equal length
- Look at trends, not just absolute numbers
- Consider seasonality in comparisons
Don't
- Draw conclusions from single data points
- Ignore context (holidays, launches, etc.)
- Compare weekends to weekdays
- Forget to check mobile vs desktop
- Overlook bounce rate on landing pages
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