Ticket SLAs

You can click on the Switch Chart option to switch the graphical view of the reports, the following are the graphs available for you to view:

• SLA by Day of the Week: This report shows how many tickets meet or exceed their SLA deadlines on specific days. It aggregates data for each day, such as all Mondays, Tuesdays, etc., within the selected date range. This helps identify patterns where ticket performance may vary based on the day.
• SLA by Hour: This report provides a breakdown of ticket performance with SLAs by hour. For example, it shows how many tickets exceeded their SLA at 6 AM, 12 PM, etc. 
• Tickets Meeting or Exceeding SLA: This compares the percentage of tickets meeting or exceeding their SLA deadlines. Adding the two together should equal 100%, representing the full spectrum of ticket performance against SLAs.

These different views allow you to customize the report based on the aspect of SLA performance you require to analyze.

When you apply a filter, it narrows down the ability to sort through tickets based on specific criteria using the options provided in a filter tool. This helps agents or managers focus on particular sets of tickets, making it easier to manage and analyze them.

The following are the Filter options:

• Date Range: You can filter tickets based on a predefined period such as Today, One Week, Two Week, Three Week, One Month".
• Custom Dates: Offers flexibility to choose specific start and end dates for filtering tickets. This is useful when analyzing tickets created or updated during a particular time frame. You can select up to 60 days.
• Agent Teams: Filters tickets based on specific teams of agents, allowing you to see only the tickets handled by a particular group (e.g., Technical Support, Customer Service, etc.).
• Agents: Filters tickets assigned to or created by individual agents. This helps track the workload or performance of specific agents.
• Components: Allows filtering by specific components, such as different services or products within the system. It is helpful for larger organizations dealing with multiple offerings.
• Labels: Filters tickets based on custom labels or tags applied to tickets. These labels could represent different categories or specific issues (For example, urgent, billing, or bug).
• Priorities: Filter tickets by priority levels (For example, low, medium, high, or critical). Helps agents focus on the most urgent or important tickets.
• Ticket Types: Filters by the type of ticket, such as "Bug," "Feature Request," "Incident," or "Service Request." This helps categorize and manage different types of issues.
• Time to Resolve (Hours): Allows filtering based on how long it took (or is expected to take) to resolve a ticket. This helps track tickets nearing or exceeding service level agreements (SLAs).

These filters help improve efficiency by providing a customized view of the tickets based on your specific criteria.

The Ticket SLA report features multiple columns that present key data attributes and metrics.  These fields provide valuable insights into ticket performance to SLAs, enabling managers and teams to assess effectiveness, identify trends, and make data-driven improvements. The following table provides detailed descriptions of each column. 

The report provides both Table and Graph options, and you can choose how to view the data using a toggle button next to the Data Range. The toggle button allows you to easily switch between these views, depending on how you prefer to analyze the data.

The available view options are:

• Graph: Displays the data visually using graphs (e.g., bar charts, line graphs), allowing you to quickly identify trends and patterns in ticket updates, comments, resolutions, and other key metrics.
• Graph and Table: Shows both the graphical representation and the detailed table simultaneously. This option helps you compare the visual trends with the exact numerical data, providing a complete report view.
• Table: Displays the data in a tabular format, listing the values for each field (e.g., updates, comments, tickets resolved) in rows and columns. This option is useful for viewing detailed figures and performing data analysis.