GA4 Reporting and Data Analysis

Overview

GA4 provides standard reports for common metrics and Explorations for advanced analysis, segmentation, and custom reporting.

When to Use This Skill

Invoke this skill when:

• Analyzing website or app performance in GA4
• Creating custom reports and explorations
• Building funnel analysis for conversion paths
• Analyzing user paths and behavior flow
• Creating cohort analyses for retention
• Segmenting users for comparison
• Extracting insights from GA4 data
• Building custom exploration reports
• Analyzing e-commerce performance
• Creating user lifetime value reports
• Working with custom dimensions in reports
• Analyzing traffic sources and campaigns
• Building attribution reports
• Analyzing audience overlap

Core Capabilities

Standard Reports

Path: Reports (left navigation)

Report Categories:

1. Realtime

   • Active users (last 30 minutes)
   • Real-time events
   • Current conversions
   • Traffic sources

2. Life Cycle Reports:

   Acquisition:

   • User acquisition (first touch)
   • Traffic acquisition (session level)
   • Channels, sources, campaigns

   Engagement:

   • Events (all event activity)
   • Conversions (key events)
   • Pages and screens
   • Landing pages

   Monetization:

   • E-commerce purchases
   • Publisher ads (AdSense)
   • In-app purchases
   • Revenue metrics

   Retention:

   • User engagement over time
   • Cohort analysis
   • User retention
   • Lifetime value

3. User Reports:

   Demographics:

   • Age, gender (requires Google Signals)
   • Country, city, language

   Tech:

   • Browser, device, OS
   • Screen resolution
   • App version

Customizing Standard Reports:

• Add secondary dimensions
• Apply filters
• Change date range
• Compare date periods
• Download as CSV/PDF

Explorations

Path: Explore (left navigation)

Exploration Types:

1. Free Form Exploration

Purpose: Flexible custom reports with drag-and-drop interface

Key Components:

• Dimensions: User attributes (country, device, etc.)
• Metrics: Quantitative measures (users, sessions, revenue)
• Rows: Primary dimension
• Columns: Secondary dimension (optional)
• Values: Metrics to display
• Filters: Limit data shown
• Segments: Compare user groups

Example Use:

• Create custom traffic source report
• Analyze product performance
• Build custom conversion report

2. Funnel Exploration

Purpose: Analyze conversion funnels and drop-off points

Setup:

1. Add steps:

   • Step 1: page_view (homepage)
   • Step 2: view_item
   • Step 3: add_to_cart
   • Step 4: begin_checkout
   • Step 5: purchase

2. Configure:

   • Funnel type: Closed (must complete steps in order) or Open
   • Step conditions: Event + parameter filters

3. Analyze:

   • Completion rate for each step
   • Drop-off percentage
   • Elapsed time between steps

Example Insights:

• 60% drop-off from cart to checkout
• Average 2 minutes from view to purchase
• Mobile users drop off more at checkout

3. Path Exploration

Purpose: Visualize user journeys and navigation paths

Types:

• Starting point: Paths beginning with specific event/page
• Ending point: Paths ending with specific event/page
• Path exploration: See all paths

Setup:

1. Choose starting or ending point
2. Select event or page
3. View visualization:
   • Node size = traffic volume
   • Arrows = path direction
   • Numbers = user count

Example Insights:

• Most common path to checkout
• Where users go after homepage
• Navigation patterns before purchase

4. Segment Overlap

Purpose: Compare and analyze audience overlap

Setup:

1. Add 2-3 segments
2. View Venn diagram showing:
   • Unique users in each segment
   • Overlapping users
   • Total reach

Example:

• Compare "Purchasers" vs "Newsletter Subscribers"
• Find overlap between mobile and desktop users
• Analyze "High Value" vs "Frequent Visitors"

5. Cohort Exploration

Purpose: Analyze user retention over time

Setup:

1. Cohort: User grouping (by acquisition date)
2. Cohort granularity: Daily, weekly, monthly
3. Metrics: Sessions, revenue, events per user
4. Time period: Days/weeks/months since cohort start

Example Insights:

• Week 1 retention: 40%
• Week 4 retention: 15%
• Revenue per cohort over 8 weeks

6. User Exploration

Purpose: Analyze individual user behavior

Setup:

1. Add user identifier (user_pseudo_id or user_id)
2. View user details:
   • All events fired
   • Event parameters
   • Device, location
   • Session timeline

Use Cases:

• Debug specific user issues
• Understand power user behavior
• Investigate unusual patterns

7. User Lifetime

Purpose: Analyze user value over lifetime

Setup:

1. Dimensions: Acquisition source, campaign, etc.
2. Metrics: Lifetime value, revenue, sessions
3. Time period: Lifetime duration

Example Insights:

• Organic users: $125 LTV
• Paid users: $85 LTV
• Average lifetime: 180 days

Segments

Creating Segments:

Path: Explorations → Create new segment

Segment Types:

• User segment: Users matching conditions
• Session segment: Sessions matching conditions
• Event segment: Events matching conditions

Conditions:

• Demographics (country, age, gender)
• Technology (device, browser)
• Acquisition (source, medium, campaign)
• Behavior (events, conversions)
• E-commerce (purchasers, revenue)
• Custom dimensions/metrics

Example Segments:

High-Value Purchasers:

Users where:
- totalRevenue > 500
- purchaseCount >= 3

Mobile Converters:

Sessions where:
- deviceCategory = mobile
- keyEvent: purchase

Engaged Users:

Users where:
- sessionCount >= 5
- avgEngagementTime > 120 seconds

Comparisons

Purpose: Compare metrics across dimensions or segments

Creating Comparison:

1. In report, click Add comparison
2. Choose dimension or segment
3. Select values to compare

Example:

• Compare desktop vs mobile
• Compare US vs UK traffic
• Compare this month vs last month

Visualization:

• Side-by-side metrics
• Color-coded lines in charts
• Percentage differences

Report Customization

Adding Dimensions:

• Click "+" in dimension row
• Select from available dimensions
• Custom dimensions appear if configured

Changing Date Range:

• Top-right date selector
• Preset ranges (Last 7 days, Last 30 days)
• Custom ranges
• Date comparisons

Applying Filters:

• Click "Add filter"
• Choose dimension
• Set condition (equals, contains, etc.)
• Enter value

Saving Reports:

• Explorations auto-save
• Share link to Exploration with team
• Export as PDF or Google Sheets

Key Metrics

User Metrics:

• Total Users: All users in period
• New Users: First-time visitors
• Active Users: Users with engagement
• DAU/WAU/MAU: Daily/Weekly/Monthly active users

Engagement Metrics:

• Sessions: Count of sessions
• Average Engagement Time: Time actively engaged
• Engagement Rate: % of engaged sessions
• Events per Session: Average event count

Conversion Metrics:

• Conversions: Key event count
• Conversion Rate: % of sessions with conversion
• Total Revenue: Sum of revenue
• ARPPU: Average revenue per paying user

E-commerce Metrics:

• Purchase Revenue: Revenue from purchases
• Transactions: Purchase event count
• Average Purchase Revenue: Revenue per transaction
• Items Viewed/Added/Purchased: Counts

Attribution

Path: Advertising → Attribution

Models:

• Data-driven: ML-based credit assignment
• Last click: Full credit to last interaction
• First click: Full credit to first interaction
• Linear: Equal credit to all touchpoints
• Time decay: More credit to recent interactions
• Position-based: More credit to first and last

Comparing Models:

• View conversions by channel under different models
• Understand impact of attribution choice
• Optimize marketing spend

Analysis Tips

Finding Insights:

1. Start broad:

   • Review standard reports
   • Identify anomalies or trends

2. Drill down:

   • Add secondary dimensions
   • Apply filters for specific segments

3. Use Explorations:

   • Build funnel for conversion paths
   • Create cohorts for retention analysis
   • Segment users for comparison

4. Export and share:

   • Download reports
   • Share Exploration links
   • Schedule email reports (Looker Studio)

Common Analyses:

Conversion Funnel:

• Identify drop-off points
• Optimize low-performing steps
• A/B test improvements

Traffic Source Performance:

• Which sources drive most conversions?
• Cost per acquisition by channel
• ROI by campaign

User Retention:

• What % return after first visit?
• How long do users remain active?
• Which acquisition sources have best retention?

Product Performance:

• Which products viewed most?
• What's conversion rate by product?
• Which products have highest revenue?

Integration with Other Skills

• ga4-setup - Initial property setup for reporting
• ga4-custom-dimensions - Using custom dimensions in reports
• ga4-audiences - Building audiences from analysis
• ga4-bigquery - Advanced analysis beyond GA4 UI
• ga4-data-management - Data retention and filters
• ga4-user-tracking - User ID in reports and segments

References

• references/standard-reports-guide.md - Complete standard reports reference
• references/explorations-complete.md - All exploration types with examples
• references/segments-guide.md - Creating and using segments
• references/analysis-patterns.md - Common analysis workflows

Quick Reference

Exploration Types:

• Free Form: Custom flexible reports
• Funnel: Conversion path analysis
• Path: User journey visualization
• Segment Overlap: Audience comparison
• Cohort: Retention analysis
• User: Individual user behavior
• User Lifetime: LTV analysis

Segment Scopes:

• User: Users matching conditions
• Session: Sessions matching conditions
• Event: Events matching conditions

Report Limits:

• Explorations: 200 per property
• Shared Explorations: 50 per user
• Segments: 100 per Exploration