How is the Handle time metric calculated in the Messaging tickets dataset?

Question

In the Messaging tickets dataset, how is the Handle time metric being calculated?

Answer

The Handle time metric is the time agents spend interacting with an end user on a messaging ticket. The metric is measured per ticket.

The handle time of a ticket is an aggregation of the time between the start/restart and pause events (mentioned below) with at least one agent message sent.

The timer starts or restarts when:

The agent is first assigned to the ticket. (Start)

The end user sends a response, reopening the ticket. (Restart)

The agent sends a message to a Pending, On-hold, or Solved ticket. (Restart)

The timer pauses when:

The ticket is submitted as Pending, On-hold, or Solved.

The ticket is unassigned from the agent or re-assigned to another group or agent.

The ticket is deleted.

The agent’s capacity is released automatically after 10 minutes of no messages from the end user.

If an agent sends a message to a Pending/On-hold/Solved ticket, the few seconds involved in sending the message counts toward the Handle time metric. If an end user sends a message to a Pending/On-hold/Solved ticket, the few seconds involved in sending the message also counts toward the Handle time metric. The end user’s message counts because it reopens the ticket, restarting the timer. However, because the agent is not available at the moment, the timer pauses when the message is received.

Consider the following example:

At 9:00 AM, an agent is assigned to a ticket.
At 9:05 AM, the agent responds to the ticket.
At 9:06 AM, the agent solves the ticket.

At 9:06, the handle time for that ticket is calculated as being 6 minutes. Prior to 9:06, the handle time couldn’t have been calculated because not all the required steps had been completed yet (start event, agent message, and pause/end event).

If the agent didn’t respond and instead simply solved the ticket, no handle time would be calculated because no agent reply was sent.

For more information, see these articles:

Metrics and attributes for Zendesk messaging

Analyzing your messaging tickets