> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ticketcord.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Analytics & Reports

> Understand your support performance with analytics and reports

Track your support team's performance, understand ticket trends, and optimize your operations with TicketCord's analytics.

<Info>
  Analytics dashboard is available on **Basic** plan and above.
</Info>

## Analytics Overview

The analytics dashboard provides insights into:

<CardGroup cols={2}>
  <Card title="Ticket Volume" icon="chart-line">
    Track ticket creation and resolution trends
  </Card>

  <Card title="Response Times" icon="clock">
    Monitor how quickly tickets are handled
  </Card>

  <Card title="Staff Performance" icon="users">
    See individual and team metrics
  </Card>

  <Card title="AI Insights" icon="robot">
    Track AI feature usage and effectiveness
  </Card>
</CardGroup>

## Ticket Analytics

### Volume Metrics

| Metric             | Description                    |
| ------------------ | ------------------------------ |
| **Total Tickets**  | All-time ticket count          |
| **New Tickets**    | Tickets created in period      |
| **Closed Tickets** | Tickets resolved in period     |
| **Open Tickets**   | Currently active tickets       |
| **Backlog**        | Open tickets older than X days |

### Trend Charts

View ticket volume over time:

* Daily, weekly, monthly views
* Compare periods (this week vs last week)
* Identify peak hours and days
* Spot trends and anomalies

### Resolution Metrics

| Metric                   | Description                  |
| ------------------------ | ---------------------------- |
| **First Response Time**  | Time to first staff reply    |
| **Resolution Time**      | Time from open to close      |
| **Reopen Rate**          | % of tickets reopened        |
| **One-Touch Resolution** | % resolved in first response |

## Staff Performance

### Individual Metrics

Track each staff member's performance:

| Metric                   | Description                   |
| ------------------------ | ----------------------------- |
| **Tickets Handled**      | Total tickets assigned/closed |
| **Avg. Response Time**   | Average time to respond       |
| **Avg. Resolution Time** | Average time to resolve       |
| **Satisfaction Score**   | Rating from feedback          |
| **Activity Hours**       | When they're most active      |

### Team Overview

* Leaderboard by tickets handled
* Comparison charts
* Workload distribution
* Coverage gaps

### Performance Trends

* Week-over-week changes
* Improvement tracking
* Identify training needs
* Recognize top performers

## Category Analytics

### By Ticket Category

* Volume per category
* Resolution time per category
* Most common issues
* Trending categories

### Tags Analysis

* Most used tags
* Tag combinations
* Resolution by tag
* Tag trends

## AI Analytics

<Info>
  AI analytics available on **Pro** and **Enterprise** plans.
</Info>

### Knowledge Base Performance

| Metric                   | Description                  |
| ------------------------ | ---------------------------- |
| **Suggestions Made**     | AI responses offered         |
| **Suggestions Accepted** | User clicked/used suggestion |
| **Accuracy Rate**        | % of helpful suggestions     |
| **Escalation Rate**      | % needing human help         |

### Auto-Routing Analytics

* Tickets auto-routed
* Routing accuracy
* Category predictions
* Routing time saved

### AI Token Usage

Track your AI consumption:

| Metric               | Description                      |
| -------------------- | -------------------------------- |
| **Tokens Used**      | Current period usage             |
| **Tokens Remaining** | Available until reset            |
| **Usage Trend**      | Daily/weekly consumption         |
| **By Feature**       | KB, routing, detection breakdown |

## Custom Reports

### Creating Reports

<Steps>
  <Step title="Choose Metrics">
    Select which metrics to include
  </Step>

  <Step title="Set Date Range">
    Define the reporting period
  </Step>

  <Step title="Apply Filters">
    Filter by category, staff, priority
  </Step>

  <Step title="Generate Report">
    View or export the report
  </Step>
</Steps>

### Export Options

| Format   | Best For                         |
| -------- | -------------------------------- |
| **PDF**  | Sharing with stakeholders        |
| **CSV**  | Further analysis in spreadsheets |
| **JSON** | Integration with other tools     |

### Scheduled Reports

<Info>
  Scheduled reports are an **Enterprise** feature.
</Info>

Automatically receive reports via email:

1. Go to Analytics → Scheduled Reports
2. Click **Create Schedule**
3. Configure report content
4. Set frequency (daily, weekly, monthly)
5. Add recipients
6. Save schedule

## Dashboard Widgets

Customize your dashboard with widgets:

| Widget                | Shows                   |
| --------------------- | ----------------------- |
| **Quick Stats**       | Key metrics at a glance |
| **Ticket Trend**      | Volume chart            |
| **Staff Leaderboard** | Top performers          |
| **Recent Activity**   | Latest events           |
| **AI Usage Meter**    | Token consumption       |
| **SLA Status**        | Compliance overview     |

### Arranging Widgets

* Drag to reorder
* Resize widgets
* Hide unused widgets
* Add custom widgets

## Interpreting Data

### What Good Looks Like

| Metric          | Good        | Needs Attention |
| --------------- | ----------- | --------------- |
| First Response  | \< 1 hour   | > 4 hours       |
| Resolution Time | \< 24 hours | > 48 hours      |
| Reopen Rate     | \< 10%      | > 20%           |
| AI Accuracy     | > 70%       | \< 50%          |

### Taking Action

Based on analytics, consider:

* **High volume hours**: Schedule more staff
* **Long resolution times**: Review processes
* **Low AI accuracy**: Improve knowledge base
* **Overloaded staff**: Redistribute workload

## Privacy & Data

Analytics are based on your ticket data:

* Only you can see your analytics
* No data shared between organizations
* Aggregated metrics don't expose PII
* Data retention follows your plan

<Card title="Need Help?" icon="headset" href="https://ticketcord.net/discord">
  Questions about analytics? Join our Discord
</Card>