We’ve developed two new metrics to help solve the problem of Average Handle Time (AHT).
Many ticketing systems and WFM tools rely on measuring time from open to close as their average handle time. This is flawed in that, for asychronous channels like chat or email, the time is inflated greatly by time spent waiting for a response. In the majority of these cases, agents are able to move onto other work, i.e. they are not actually sat waiting, which means by using this AHT you are going to inflate your staffing requirements.
Dialpad WFM's unique metrics "average conversation time (ACT)" and "average interaction time (AIT)", provide more realistic insight into the time agents spend on each ticket.
📹 Watch our 3min explainer
What is "Average conversation time (ACT)"?
Average conversation time (ACT) measures the total amount of dedicated time an agent spent on the ticket, removing waiting or idle time.
How to use ACT for performance reporting:
This metric provides insight into how much work goes into closing each ticket. Tracking this data can help you to understand both the difficulty of the queries you're receiving as well as the skill level of your agents.
An increasing ACT would suggest that tickets are becoming harder or that agents require more training. Whereas a decreasing ACT may indicate that agent's are ramping up or becoming more efficient.
How is it calculated?
When we build the activity timeline, we group together interactions that happen on the same ticket within a reasonable time* of each other into ‘ticket sessions’.
Once the ticket is closed, we add together all of the ticket sessions to produce the conversation time.
The average conversation time is made by getting the average of all closed tickets on that activity for the period viewed in the performance page, e.g. day, week.
✍️ Example:
Ben exchanges 3 messages with a customer on live chat. The customer then stops responding. These 3 messages form 1 ticket session that lasted 300s.
The customer responds again after work and the 2 more messages are sent, then the conversation is closed. These 2 messages form another ticket session that lasted 240s.
There are now 2 ticket sessions on this ticket, from open to close. These are added together to produce a conversation time of 540s.
300s + 240s = 540 seconds
How to use ACT for forecasting:
An average of this metric can be used as the "average conversation time" input in your queues to refine your staffing forecasts.
Best practice:
Go to your performance page and select all your teams, or the teams that work on this queue.
Select 'week' view
Select 'by activity' in the breakdown table and filter to the relevant activities linked to this queue.
Take note of the ACT across the last 4 - 12 weeks, depending on your preference.
Create an average of these numbers and enter that in the relevant queue.
What is "Average interaction time (AIT)"?
Average interaction time (AIT) measures the average time it takes for an agent to do each interaction. An interaction can be sending a response to a customer, or changing the status of a ticket.
How is it calculated?
For AIT, we look at all of the times agents were scheduled on a particular activity and divide the working time by the number of interactions they did in that time.
✍️ Example:
Ben is scheduled on 💬 Chat for 2h 30m on Monday. In that time he interacted with tickets 50 times. His AIT is 108 seconds for this day.
2h 30m = 5400 seconds. 5400 ÷ 50 = 108 seconds
How to use AIT for performance reporting:
This metric helps you to understand productivity at an interaction level, measuring the time spent on each touchpoint within a conversation.
This is most useful for asynchronous channels, like messaging or email, where a conversation is made up of multiple touch points.
AIT can also be used to improve the quality of your performance timelines.
Read this guide for more information
How to use AIT for forecasting:
If you are a Dixa or Intercom user, you have the option to create your forecasts based on each message within a conversation. AIT can be used as the "average interaction time" input in your queues to refine your staffing forecasts. We recommend using an average of the last 30 days to 3 months.
Best practice:
Go to your performance page and select all your teams, or the teams that work on this queue.
Select 'week' view
Select 'by activity' in the breakdown table and filter to the relevant activities linked to this queue.
Take note of the AIT across the last 4 - 12 weeks, depending on your preference.
Create an average of these numbers and enter that in the relevant queue.
When can I get my team’s AIT and ACT?
Dialpad WFM will be able to produce AIT and ACT as soon as your Intercom is connected and your team are onboard and using schedules.
We can provide guidance based on our other customer’s averages to help you get going as you onboard. You can then refine your queue settings as your data matures.