Ticket closing delay

Overview

The Ticket closing delay report shows the average time taken by support Agents to close Tickets. This report helps you understand Agent performance and the average time required to close Tickets.

Where to Find

Go to Support → Reports → Ticket Closing Delay

Ticket Closing Delay
How It Works

The report displays a graph with the following types of data:

  • Average Closing Delay (Days) – Shows the typical number of days tickets take to close in this period.
  • Tickets Closed Count – Total tickets closed in this period.
  • Longest Closing Delay (Days) – Shows the longest time taken to close a ticket in this period.

You can select a predefined duration or choose a custom date range. You can also apply custom filters to generate more specific results.

Filtering the Report
You can generate the report for different time periods, such as:

  • Last 30 days
  • This week
  • Last quarter
  • Custom date range

You can also use the custom filter to narrow the report based on Ticket fields.
For example, you can filter Tickets by:

  • Category
  • Priority
  • Status
  • Other default or custom fields

The custom filter allows you to set multiple conditions to get more precise results.

Notes / Tips
  • Delay is measured from ticket creation to closing, not from last reply. A ticket that sat untouched for days before an agent even looked at it will show a high closing delay even if the actual resolution work was quick — pair this report with First Response Delay to tell the two apart.
  • Only tickets closed within the selected date range are counted, regardless of when they were created. A ticket opened in June but closed in July will appear in the July report, not June’s.
  • A single old/stuck ticket can skew the average. Check the “Longest Closing Delay” figure alongside the average — if it’s far higher than the average, one or two outliers (e.g., a ticket left open for weeks) may be distorting the picture. Filter by status/category to isolate them if needed.
  • Lower isn’t always better in isolation. A very low average closing delay combined with a low ticket count may just mean few tickets were closed, not that resolution is fast — cross-check against ticket volume for context.
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