3.7. Analytics
The Analytics page provides comprehensive insights into your server's ticket activity, staff performance, and user engagement. This feature allows you to track trends, identify peak activity times, and monitor support team efficiency.
Premium Feature: Analytics is a Premium-only feature. You must have an active Premium subscription to access this page. If you don't have Premium, you'll see an error message with a link to upgrade at /pricing.
Access Requirements
To view analytics, you must be a dashboard administrator for the server. Only dashboard administrators can access the Analytics page and view user statistics.
User Statistics
The User Statistics section allows you to search for and view detailed statistics for any user in your server. Simply enter a Discord User ID and click Search to view their analytics.
Searching for Users
To view a user's statistics:
Enter the Discord User ID in the search field. You can find a user's ID by enabling Developer Mode in Discord (User Settings → Advanced → Developer Mode), then right-clicking on the user and selecting "Copy ID".
Click the Search button or press Enter to retrieve the user's statistics.
The statistics will be displayed based on whether the user is identified as a staff member or a regular user.
Staff Member Statistics
If a user has answered tickets (sent messages in tickets they didn't open), they are identified as a staff member and the following statistics are displayed:
| Statistic | Description |
|---|---|
Tickets Answered (Total) | The total number of tickets this staff member has responded to (excluding tickets they opened themselves) |
Tickets Answered (7 Days) | The number of tickets answered in the last 7 days |
Tickets Answered (30 Days) | The number of tickets answered in the last 30 days |
Avg Response Time | The average time it takes for this staff member to respond to a ticket after it's opened. Calculated from ticket creation to the staff member's first message in that ticket. Displayed in hours and minutes. |
Peak Activity Hour | The hour of day (in UTC) when this staff member is most active responding to tickets. Only displayed if the user has activity data. |
Regular User Statistics
If a user has not answered any tickets (only opened tickets), they are identified as a regular user and the following statistics are displayed:
| Statistic | Description |
|---|---|
Tickets Opened (Total) | The total number of tickets this user has opened |
Tickets Opened (7 Days) | The number of tickets opened in the last 7 days |
Tickets Opened (30 Days) | The number of tickets opened in the last 30 days |
Tickets Closed | The total number of tickets this user has opened that have been closed |
Avg Ticket Duration | The average time from when a ticket was opened to when it was closed. Only calculated for closed tickets. Displayed in hours and minutes. Only shown if the user has closed tickets. |
Peak Opening Hour | The hour of day (in UTC) when this user most frequently opens tickets. Only displayed if the user has activity data. |
Note: The system automatically determines whether to show staff or user statistics based on whether the user has answered tickets. Users who have answered at least one ticket are treated as staff members and see staff statistics. Users who have only opened tickets see regular user statistics.
Server Statistics
The Server Statistics section provides an overview of your server's ticket activity and performance metrics. This data is automatically loaded when you visit the Analytics page.
Overview Statistics
The main overview cards display key metrics at a glance:
| Statistic | Description |
|---|---|
Total Tickets Ever | The total number of tickets that have ever been created in your server. This uses the ticket counter from your server's configuration, which matches the ticket numbering system used by the bot. |
Tickets (7 Days) | The number of tickets created in the last 7 days |
Tickets (30 Days) | The number of tickets created in the last 30 days |
Avg Response Time | The average time it takes for staff to respond to tickets across all tickets in your server. Calculated from ticket creation to the first staff response. Displayed in hours and minutes. |
Ticket Status
The Ticket Status section shows the current state of all tickets in your server:
| Status | Description |
|---|---|
Open | The number of tickets that are currently open and active |
Closed | The number of tickets that have been closed |
Claimed | The number of tickets that are currently claimed by a staff member |
Daily Breakdown
The Daily Breakdown section shows a visual representation of ticket activity over the last 5 days. Each day displays:
- The date (formatted as weekday, month, and day)
- A progress bar showing the relative number of tickets opened that day
- The exact count of tickets opened on that day
This helps you identify trends and see which days have the highest ticket volume.
Tickets by Category
The Tickets by Category section displays the distribution of tickets across different ticket categories/panels. This shows:
- The name of each ticket category/panel
- The total number of tickets created from that category
- Categories are sorted by ticket count (highest to lowest)
- Up to 10 categories are displayed
This helps you understand which types of tickets are most common and where your support resources are being utilized.
Peak Activity Hour
The Peak Activity Hour displays the hour of day (in UTC timezone) when the most tickets are opened. This is calculated based on ticket creation times from the last 30 days.
Note: All time-based statistics (Peak Activity Hour, Peak Opening Hour, Peak Activity Hour for staff) are displayed in UTC timezone for consistency across different server timezones. You may need to convert these times to your local timezone to understand when activity occurs in your region.
Understanding the Data
The Analytics page provides valuable insights that can help you:
Monitor Staff Performance
Track how many tickets each staff member handles and their average response times. This helps identify top performers and areas where additional training or support may be needed.
Identify Trends
Use the daily breakdown and category distribution to understand when tickets are most common and which types of support requests are most frequent. This can help with resource planning and scheduling.
Optimize Response Times
Monitor average response times to ensure your support team is meeting service level expectations. Use peak activity hours to schedule staff coverage during high-demand periods.
Track User Engagement
For regular users, see how many tickets they've opened and how long tickets typically remain open. This can help identify power users or users who may need additional support.
Analytics data is updated in real-time as tickets are created, responded to, and closed. All statistics are calculated based on actual ticket data stored in the system.