> ## Documentation Index
> Fetch the complete documentation index at: https://docs.backstack.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Metrics & Analytics
> Track tool usage, performance, and adoption across your organization
# Metrics & Analytics
Backstack provides comprehensive metrics and analytics to help you understand how your organization uses AI tools, track performance, and optimize your AI infrastructure.
## Overview
The Analytics dashboard gives you visibility into:
* **Tool Execution** - Which tools are being used and how often
* **Performance** - Execution times and success rates
* **User Activity** - Who is using which tools and workspaces
* **Client Distribution** - Which AI clients are connecting
* **Trends Over Time** - Usage patterns and growth
Metrics are available to organization admins and owners. Members can see metrics for their own activity.
## Key Metrics
### Tool Execution Metrics
**Total Executions:**
* Number of times tools have been called
* Breakdown by tool name
* Success vs failure counts
* Execution frequency over time
**Most Used Tools:**
* Ranking of tools by execution count
* Percentage of total tool usage
* Trends (increasing or decreasing usage)
* Comparison across workspaces
**Execution Success Rate:**
* Percentage of successful tool calls
* Failure reasons and error patterns
* Tools with highest failure rates
* Opportunities for configuration improvements
### Performance Metrics
**Execution Time:**
* Average execution time per tool
* Min, max, and median execution times
* Slow tool identification
* Performance trends over time
**Response Latency:**
* Time from request to first response
* AI provider response times
* End-to-end conversation latency
* Performance by workspace and time of day
**Resource Usage:**
* Number of active AI conversations
* Documents indexed and searched
* Desktop devices connected
* Storage consumption
### User Activity Metrics
**Active Users:**
* Daily active users (DAU)
* Weekly active users (WAU)
* Monthly active users (MAU)
* User growth trends
**User Engagement:**
* Tools used per user
* Conversations per user
* Documents shared per user
* Average session duration
**Top Users:**
* Users with most tool executions
* Power users and early adopters
* Users needing additional training
* User adoption by department or team
### Workspace Metrics
**Workspace Activity:**
* Tool executions by workspace
* Active members per workspace
* Documents shared to each workspace
* Most active workspaces
**Workspace Adoption:**
* Percentage of users per workspace
* Workspace creation trends
* Workspace size distribution
* Underutilized workspaces
### Client Distribution
**AI Client Usage:**
* Claude Desktop vs VS Code vs Cursor, etc.
* Client versions in use
* Platform distribution (Windows, macOS, Linux)
* Client adoption trends
**Connection Health:**
* Active connections
* Connection failures and errors
* Average uptime per client type
* Authentication success rates
## Viewing Analytics
### Accessing the Dashboard
1. Navigate to **Organization** → **Analytics**
2. View the default dashboard with key metrics
3. Use date range selector to adjust timeframe
4. Apply filters to drill down into specific metrics
### Time Range Selection
Choose the period to analyze:
**Preset Ranges:**
* Last 24 Hours
* Last 7 Days
* Last 30 Days
* Last 90 Days
* All Time
**Custom Range:**
* Select specific start and end dates
* Compare different time periods
* Analyze seasonal patterns
* Measure before/after changes
### Filtering Options
**By Workspace:**
* Select one or multiple workspaces
* Compare workspace performance
* Identify workspace-specific patterns
* Optimize per-workspace tool allocation
**By Tool:**
* Focus on specific tools
* Track tool adoption over time
* Identify underutilized tools
* Plan tool retirement or promotion
**By User:**
* Individual user analytics
* User cohort comparison
* Training effectiveness measurement
* Power user identification
**By Client:**
* Claude Desktop activity
* VS Code extension usage
* Cursor integration metrics
* Compare client effectiveness
## Analytics Views
### Executive Dashboard
High-level overview for leadership:
**Key Performance Indicators (KPIs):**
* Total tool executions this month
* Active users this week
* Average success rate
* Month-over-month growth
**Trend Graphs:**
* Daily tool execution volume
* User adoption curve
* Tool success rate over time
* Resource consumption trends
**Top Lists:**
* Top 10 most-used tools
* Top 10 active users
* Top 5 workspaces by activity
* Most common failure reasons
### Tool Analytics
Deep dive into tool usage:
**Tool Performance Table:**
| Tool Name | Executions | Success Rate | Avg Time | Last Used |
| ------------- | ---------- | ------------ | -------- | ---------- |
| GitHub Server | 1,245 | 98.2% | 450ms | 2 mins ago |
| Filesystem | 892 | 95.8% | 120ms | 5 mins ago |
| Brave Search | 567 | 99.1% | 890ms | 1 hour ago |
**Execution Timeline:**
* Line graph showing executions over time
* Identify peak usage hours
* Spot usage anomalies
* Plan capacity based on patterns
**Error Analysis:**
* Common error messages
* Tools with highest failure rates
* Root cause patterns
* Suggested fixes
### User Analytics
Understand how your team uses AI:
**User Activity Heatmap:**
* Usage by day of week and hour
* Identify peak times
* Optimize support coverage
* Plan maintenance windows
**Adoption Funnel:**
1. Users invited to organization
2. Users who completed first login
3. Users who executed first tool
4. Users active in last 7 days
5. Power users (daily usage)
**User Segmentation:**
* Active, inactive, and dormant users
* Users by department or role
* Early adopters vs late majority
* Training needs by segment
### Workspace Analytics
Optimize workspace organization:
**Workspace Comparison:**
* Side-by-side workspace metrics
* Identify best-performing workspaces
* Replicate success patterns
* Consolidate underutilized workspaces
**Member Activity:**
* Active vs inactive members per workspace
* Member contribution distribution
* Collaboration patterns
* Optimal workspace size
**Tool Assignment:**
* Which tools are assigned to which workspaces
* Tool utilization per workspace
* Unused tool assignments
* Opportunities to share tools across workspaces
## Use Cases
### Capacity Planning
**Monitor growth trends:**
* Track daily/weekly execution volume
* Predict future resource needs
* Plan infrastructure scaling
* Budget for AI provider costs
**Example:**
* Current: 10,000 tool executions/day
* Growth rate: 15% month-over-month
* Projected need in 6 months: 20,000/day
* Action: Plan capacity increase or optimize usage
### Tool Optimization
**Identify underperforming tools:**
* Tools with low success rates
* Tools taking too long to execute
* Tools with configuration issues
* Tools not being used despite availability
**Example:**
* PostgreSQL server shows 60% failure rate
* Investigation reveals missing environment variables
* Fix: Update DATABASE\_URL for all instances
* Result: Success rate improves to 98%
### User Training
**Measure adoption and effectiveness:**
* Which users need training
* Which tools users struggle with
* Training program effectiveness
* Knowledge gaps by team
**Example:**
* New users execute 80% fewer tools than experienced users
* Action: Create onboarding program
* Measure: Track new user adoption rate
* Result: New users reach productivity 50% faster
### Cost Management
**Track AI provider costs:**
* Total tool executions (proxy for AI costs)
* Breakdown by workspace and user
* Identify cost optimization opportunities
* Set usage budgets and alerts
**Example:**
* Development workspace uses 60% of tool executions
* Analysis shows inefficient workflow
* Action: Optimize development scripts
* Result: 30% reduction in executions
### Security Monitoring
**Detect unusual patterns:**
* Spike in tool executions from single user
* Unusual tool access patterns
* Off-hours activity
* Execution patterns violating policies
**Example:**
* User executes 1000 file deletion tools in 5 minutes
* Alert triggers for investigation
* Discovery: User was testing script, not malicious
* Action: Add rate limiting to prevent accidents
## Exporting Analytics
### Download Reports
Export metrics for offline analysis:
1. Select metrics and filters
2. Choose date range
3. Click **Export**
4. Select format:
* **CSV** - For spreadsheet analysis
* **PDF** - For presentations and reports
* **JSON** - For programmatic processing
**Export Contents:**
* Raw metric data
* Aggregated statistics
* Time-series data
* Filter parameters applied
### Scheduled Reports
Automate report generation:
1. Navigate to **Analytics** → **Scheduled Reports**
2. Click **Create Schedule**
3. Configure:
* Report type (Executive, Tool, User, Workspace)
* Metrics to include
* Frequency (daily, weekly, monthly)
* Recipients
* Format
4. Save schedule
Reports are generated and delivered automatically.
### API Access
For advanced analytics:
* Export data via GraphQL API
* Build custom dashboards
* Integrate with business intelligence tools
* Create real-time monitoring
See API documentation for endpoints and authentication.
## Best Practices
### Regular Review
**Daily:**
* Check tool execution volume
* Monitor error rates
* Review security alerts
**Weekly:**
* User activity trends
* Tool adoption progress
* Top user and workspace analysis
**Monthly:**
* Executive dashboard review
* Capacity planning check
* Cost analysis
* Training needs assessment
**Quarterly:**
* Long-term trend analysis
* Tool portfolio review
* User satisfaction measurement
* Strategic planning based on metrics
### Actionable Insights
**Don't just collect data - act on it:**
* **High failure rate?** → Investigate configuration
* **Low adoption?** → Improve training or tool selection
* **Spike in usage?** → Plan capacity increase
* **Unused tool?** → Remove or promote to right users
* **Power user identified?** → Make them a champion
### Benchmarking
**Compare across dimensions:**
* Workspace A vs Workspace B
* This month vs last month
* Your org vs industry averages (if available)
* Tool X vs Tool Y effectiveness
### Goal Setting
**Use metrics to track progress toward goals:**
**Example Goals:**
* Increase active users by 20% this quarter
* Achieve 95% tool success rate
* Reduce average execution time by 30%
* Reach 100% user adoption by year-end
Track metrics against goals monthly and adjust strategies.
## Troubleshooting
### Metrics Not Updating
**Problem:** Dashboard shows stale data
**Solutions:**
* Refresh the page
* Check date range includes current time
* Verify you have permission to view metrics
* Wait a few minutes for metrics aggregation
* Contact support if data is >1 hour old
### Missing Data
**Problem:** Expected metrics don't appear
**Solutions:**
* Verify events occurred during selected date range
* Check filters aren't excluding data
* Ensure tools were actually executed (check activity logs)
* Confirm workspace/user has activity
### Performance Issues
**Problem:** Analytics dashboard loads slowly
**Solutions:**
* Reduce date range
* Apply more specific filters
* Export data for offline analysis
* Use preset views instead of custom
* Contact support for large datasets
### Export Fails
**Problem:** Report export doesn't complete
**Solutions:**
* Reduce date range or metric scope
* Try different format
* Check browser allows downloads
* Use scheduled reports for large exports
* Contact support for assistance
## Privacy Considerations
**What's tracked:**
* Tool execution counts and timing
* User activity patterns
* Workspace usage statistics
* Success/failure rates
**What's NOT tracked:**
* Conversation content or message text
* Personal data in tool parameters
* Document contents
* API keys or credentials
Metrics are aggregated and anonymized where appropriate to protect user privacy while providing useful insights.
## Next Steps
View detailed event logs for individual actions
Set up policies and track policy violations
Manage tools and optimize based on metrics
Organize teams and compare workspace performance