The performance distribution graphs focus on the agent/group performance metrics such as first response time, average response time and resolution time. The time taken is calculated based on the business hour that applies to each ticket. For example, 24 hours equals 1 day if you have 24x7 support, and 4 days if you have a 6x5 hour workday.
First response/Average response/Resolution time buckets
| First response time | Average response time | Resolution time | |
| Definition of metrics | Time taken by the agent to send the first response on a ticket | Average time taken by the agent to respond to the ticket requester | Time taken by the agent to resolve a ticket |
| Tickets included | Tickets whose first responses were sent during the selected period | Tickets whose responses were sent during the selected period | Tickets that were resolved in the selected time period |
| Time ranges | 10 time buckets ranging from <15 minutes to 48+ hours | 10 time buckets ranging from <15 minutes to 48+ hours |
10 time buckets ranging from <5 hours to 700+ hours |
You will be able to deep dive into each bucket by clicking on the corresponding bars. For example, by clicking on the 48+ bucket, you will see the tickets with avg response time greater than 48 hrs. This lets you find out why it took so long for your agents to respond to them.
You can filter this graph based on various ticket properties including agent and group. This helps you understand which agent/group is able to respond to and resolve maximum tickets quickly and which agent/group takes too long.
Average first response and response time trend
This graph shows the daily/weekly/monthly/quarterly/yearly trend of avg first response time and avg response time. When you hover over a data point, you can see the average time taken to send all the first responses in that time period and the average of average time taken to send any response to a requester in that time period.
You can identify the problem areas in the trend graph and deep dive using the time bucket graphs above. For example, if you are viewing the weekly trend and see that the avg response time in a particular week is too high, you can select only that week in the filter and see the time bucket graph. This will show you the number of tickets responded in the specific week and the duration of the agents' response. You can easily identify the tickets with high response time and act on them immediately.
Average resolution time trend
This graph shows the daily/weekly/monthly/quarterly/yearly trend of avg resolution time. When you hover over a data point, you can see the average time taken to resolve tickets in that time period.
You can identify problem areas in the trend graph and deep dive using the time bucket graphs above. For example, if you are viewing the daily trend and see that the avg resolution time in a particular day is too high, you can select that day alone in the filter and see the time bucket graph. This will show you the number of tickets resolved in that week and how long the agents took to resolve them. You can easily identify the tickets with the high resolution time and act on them immediately.
The performance distribution graphs focus on the agent/group performance metrics like first response time, average response time and resolution time. The time taken is calculated based on the business hour that applies to each ticket. For example, 24 hrs means 1 day if you have a 24X7 support and 4 days if you have a 6 hrs X 5 days work day.
First response/Average response/Resolution time buckets
| First response time | Average response time | Resolution time | |
| Definition of metrics | The time taken by the agent to send the first response on a ticket | The average time taken by the agent to respond to the ticket requester | The time taken by the agent to resolve a ticket |
| Tickets included | Tickets whose first responses were sent during the selected period | Tickets whose responses were sent during the selected period | Tickets that were resolved in the selected time period |
| Time ranges | 10-time buckets ranging from <15 minutes to 48+ hours |
10-time buckets ranging from <15 minutes to 48+ hours |
10-time buckets ranging from <5 hours to 700+ hours |
You will be able to deep dive into each bucket by clicking on the corresponding bars. For example, by clicking on the 48+ bucket, you will see the tickets with avg response time greater than 48 hrs. This lets you find out why it took so long for your agents to respond to them.
You can filter this graph based on various ticket properties including agent and group. This helps you understand which agent/group is able to respond to and resolve maximum tickets quickly and which agent/group takes too long.
Average first response and response time trend
This graph shows the daily/weekly/monthly/quarterly/yearly trend of avg first response time and avg response time. When you hover over a data point, you can see the average time taken to send all the first responses in that time period and the average of average time taken to send any response to a requester in that time period.
You can identify the problem areas in the trend graph and deep dive using the time bucket graphs above. For example, if you are viewing the weekly trend and see that the avg response time in a particular week is too high, you can select only that week in the filter and see the time bucket graph. This will show you the number of tickets responded in the specific week and the duration of the agents' response. You can easily identify the tickets with high response time and act on them immediately.
Average resolution time trend
This graph shows the daily/weekly/monthly/quarterly/yearly trend of avg resolution time. When you hover over a data point, you can see the average time taken to resolve tickets in that time period.
You can identify problem areas in the trend graph and deep dive using the time bucket graphs above. For example, if you are viewing the daily trend and see that the avg resolution time in a particular day is too high, you can select that day alone in the filter and see the time bucket graph. This will show you the number of tickets resolved in that week and how long the agents took to resolve them. You can easily identify the tickets with the high resolution time and act on them immediately.