Tickets dataset is used when you are looking to analyze the response, resolution, volumes, performance and other characteristics of a ticket. This dataset contains information on every ticket and the aggregation of data helps you understand the overall ticket characteristics.
In the Tickets dataset, every row on the data table stores information of a single ticket, uniquely identified by Ticket ID. After each data sync, this row gets updated based on the current information of the ticket.
For example, Say a ticket (Ticket ID: 45) is created in HappyFox Help Desk today:
The row associated with this ticket in the Tickets dataset would be similar to this,
Later during the day, let's suppose that the tickets get moved to another category and gets changed to another status. So when the data sync happens the next day, the same row associated with this ticket on the Tickets dataset would be something like this,
Thus, the row in the tickets dataset gets updated based on the current state of the ticket.
The Tickets dataset allows the users to choose from a list of the following field categories.
- Ticket Properties (Assignee, category, status, priority etc)
- Ticket Performance (Agent reply count, Average response count etc)
- Ticket Events (First agent reply at, First Closed at etc)
- Ticket Lifecycle (Time in X status, Time in Y Category etc)
- Ticket Activity (Moved to category, Moved to Status etc)
- Ticket Custom fields
- Contact (Name, organization etc)
Some of the common use cases for Tickets dataset are:
- Total Number of Tickets by Priority, Status, and Source
- Average First Response time across a group of tickets
- Average Resolution Time for tickets.
- Responded vs Unresponded Tickets.