Analytics & Insights

Track test performance, identify trends, and make data-driven decisions about your testing strategy with BugBrain’s analytics dashboard.

What Can You Track?

Test Execution Metrics

Total tests run
Pass/fail rates
Average execution time
Tests run over time

Quality Trends

Pass rate trends
Flaky test detection
Failure patterns
Coverage gaps

Team Activity

Tests created per member
Execution activity
Most active projects
Collaboration metrics

Usage Statistics

Quota consumption
Feature usage
Integration activity
Cost tracking

Accessing Analytics

Dashboard View:

Go to any project
Click “Analytics” in the sidebar
View project-specific metrics

Organization View:

Click organization name
Select “Analytics”
View org-wide metrics

Key Metrics

Pass Rate

What it shows: Percentage of tests that pass

Formula: (Passed Tests / Total Tests) × 100

What’s good:

95%+ - Excellent
85-95% - Good
75-85% - Needs attention
<75% - Critical issues

Tip: A suddenly dropping pass rate often indicates new bugs or environmental issues. Investigate quickly!

Execution Time

What it shows: How long tests take to run

Metrics:

Average execution time
Min/max times
Time by test priority
Trends over time

What to watch:

Increasing times (performance degradation)
Very long tests (timeout candidates)
Inconsistent times (flaky tests)

Flaky Tests

What it shows: Tests that pass/fail inconsistently

Detection: Test passes some runs, fails others with same code

Why it matters:

Unreliable tests waste time
Hide real bugs
Reduce confidence in suite

Action: Investigate and fix flaky tests immediately

Test Coverage

What it shows: How much of your app is tested

Metrics:

Pages with tests
Flows with tests
Features with tests
Critical paths covered

Goal: 100% coverage of critical user journeys

Visualization Types

Line Charts

Best for: Trends over time

Pass rate by day/week/month
Execution count trends
Duration trends

Bar Charts

Best for: Comparisons

Tests by priority
Pass/fail by project
Execution by team member

Pie Charts

Best for: Distributions

Test status breakdown
Priority distribution
Tag distribution

Heatmaps

Best for: Patterns

Failure frequency by test
Execution times by day/hour
Activity by team member

Date Ranges

Filter analytics by time period:

Last 7 days - Recent activity
Last 30 days - Monthly view
Last 90 days - Quarterly trends
Custom range - Specific period

Filtering Options

Drill down into specific data:

By Priority:

Critical tests only
High priority
All priorities

By Tag:

smoke tests
regression
api tests
Custom tags

By Status:

Passed tests
Failed tests
All tests

By Team Member:

Tests created by person
Tests run by person
Activity per person

Reports

Daily Report

Automated daily summary:

Tests run yesterday
Pass/fail rate
New failures
Flaky test alerts

Configure: Settings → Notifications → Daily Reports

Weekly Report

Comprehensive weekly analysis:

Week-over-week trends
Top failures
Coverage improvements
Team activity summary

Delivery: Email on Monday mornings

Monthly Report

Executive summary:

Monthly metrics
Quality trends
Usage statistics
Recommendations

Audience: Management and stakeholders

💡

Pro Tip: Schedule reports to arrive when you need them. Many teams like Monday morning weekly reports to plan the week.

Key Insights

Test Health Score

Overall quality indicator (0-100):

Components:

Pass rate (40%)
Flakiness (30%)
Coverage (20%)
Execution speed (10%)

Score Ranges:

90-100: Excellent
75-89: Good
60-74: Needs work
<60: Critical

Failure Analysis

Identify why tests fail:

Common Causes:

Element not found (40%)
Timeout (25%)
Assertion failed (20%)
Network error (10%)
Other (5%)

Action: Focus fixes on top causes

Slowest Tests

Tests taking longest to execute:

Why it matters:

Slow tests delay feedback
Increase CI/CD time
Cost more to run

Action: Optimize or break into smaller tests

Most Flaky Tests

Tests failing inconsistently:

Metric: Flakiness rate = (Inconsistent runs / Total runs) × 100

Threshold: >10% is considered flaky

Action: Fix or remove flaky tests

Team Analytics

Member Activity

Track individual contributions:

Tests created
Tests run
Executions initiated
Discovery sessions

Use case: Performance reviews, workload balance

Collaboration Metrics

Measure team effectiveness:

Shared tests
Team response to failures
Knowledge sharing
Cross-project work

Project Ownership

See who owns what:

Primary maintainers per project
Test creation by project
Activity levels

Usage Analytics

Quota Tracking

Monitor plan limits:

AI generations used/remaining
Discovery sessions used/remaining
Team members vs limit
Days until reset

Alerts: Get notified at 80%, 90%, 100% usage

Feature Adoption

See which features teams use:

Most used features
Unused features
Feature usage trends
ROI indicators

Integration Activity

Track integration usage:

Notifications sent
Issues created
Webhook calls
Integration errors

Cost Analytics

Execution Costs

Track testing expenses:

Cost per execution
Monthly testing costs
Cost by project
Cost optimization opportunities

AI Usage Costs

Monitor AI spending:

Test generation costs
AI chat usage
Discovery analysis costs
Budget vs actual

ROI Metrics

Measure testing value:

Bugs found per dollar
Time saved vs manual testing
False positive rate
Developer time freed up

Export Options

Download analytics data:

Formats:

CSV - Spreadsheet data
PDF - Visual reports
JSON - API integration
Images - Charts and graphs

Use cases:

Share with stakeholders
Present in meetings
Import to other tools
Archive records

API Access

Access analytics programmatically:

GET /api/analytics/metrics
GET /api/analytics/trends
GET /api/analytics/reports

Use cases:

Custom dashboards
Integration with BI tools
Automated reporting
Data warehouse sync

[Pro plan feature]

Best Practices

💡

1. Check Daily Review key metrics each morning to catch issues early

2. Set Baselines Establish normal ranges for your metrics

3. Investigate Anomalies Sudden changes deserve immediate attention

4. Share Insights Distribute reports to relevant stakeholders

5. Act on Data Analytics are useless if you don’t act on findings

6. Track Improvements Measure impact of changes to testing strategy

Common Patterns

Declining Pass Rate

Pattern: Pass rate drops over time

Causes:

New bugs introduced
Environmental instability
Test maintenance neglected

Action: Prioritize bug fixes and test updates

Increasing Execution Time

Pattern: Tests take longer each week

Causes:

Application performance degradation
More complex tests added
Browser/environment slowdown

Action: Optimize tests and investigate app performance

Spike in Flaky Tests

Pattern: Sudden increase in inconsistent tests

Causes:

Infrastructure changes
New dynamic UI elements
Timing issues introduced

Action: Review recent changes and add stability

Troubleshooting

Metrics not updating?

Check that tests are running
Verify execution history exists
Wait for daily aggregation (runs at 2 AM)
Clear browser cache

Wrong data showing?

Verify date range selection
Check applied filters
Ensure timezone is correct
Refresh the page

Can’t export reports?

Check your plan includes export
Verify file permissions
Try different format
Contact support if persistent

Next Steps

Test Plans Team Management