AHT — Average handle time
Average handle time is the time an agent actively spends on a question: reading it, finding the context, answering it and logging whatever needs logging. It excludes waits, which is why it is the metric that best approximates what a given support volume costs in hours.
What is average handle time?
Average handle time is the time an agent actively spends on a question: reading it, finding the context, answering it and logging whatever needs logging. It excludes waits, which is why it is the metric that best approximates what a given support volume costs in hours.
Also: AHT · handling time
What the tool measures and what it actually costs
Almost every tool times from opening the conversation to sending the reply. That leaves out two expensive things: the stretch spent hunting for the fact on another screen, and the cost of getting concentration back after the interruption, estimated at ten to twenty minutes. A ticket logged as four minutes usually costs between twelve and twenty.
Why it matters
What changes in a SaaS
It is the multiplier in the sum. Team cost per hour times average handle time times volume gives the real cost of support, which is the figure you use to decide whether to hire, automate or document. Without it, the only figure in play is the tool licence, which is usually less than 10% of the total.
Average handle time in detail
Why driving it down at all costs is a bad idea
It is the easiest metric to game: you lower it by answering shorter and worse. When it becomes a target on its own, reopens go up, first contact resolution goes down, and total cost rises even as the number improves.
Where the real saving is
In the context hunt, not in the writing. Having the plan, the usage and the billing of whoever is asking on the same screen takes out most of the time the metric never times.
How Intake handles it
Questions about average handle time
How do you calculate the real cost of a ticket?
Hourly cost of the profile answering, multiplied by the real handling time, including the context hunt and the interruption. For a €30,000 gross profile and fifteen real minutes per ticket, that comes to about €5.75 per question.
Does average handle time include waits?
No. It measures active time only. Waits belong to resolution time, which is the metric that covers the whole process.
Related terms
A term on its own is only half understood. These come up in the same conversation.
Resolution time
Resolution time is how long passes between a question arriving and it being resolved and closed. Unlike first response time, it measures the whole process, including waits on the customer and escalations to other teams.
FCR — First contact resolution
First contact resolution is the percentage of questions resolved in the first interaction, without the customer having to write again and without the conversation passing to another person. It is the metric that best summarises whether the team has what it needs to answer within reach.
Contact rate
Contact rate is how many support questions a business generates relative to its size: normally tickets per customer per month, or per hundred active customers. It is the metric that says whether support will scale with the business or suffocate it.
Support agent
A support agent is the person who handles incoming customer questions: reads them, finds the context needed to answer, resolves them or escalates them to whoever should take over. It is a reactive job by definition, and the work is measured in response time, resolution and satisfaction.
CES — Customer effort
CES measures how much effort it took the customer to get their problem solved. It is asked with a statement along the lines of "the company made it easy for me" and an agreement scale, and it starts from a specific idea: reducing friction retains people better than trying to delight them.
Deflection rate
Deflection rate is the percentage of questions resolved without a person getting involved, either because the customer found the answer themselves or because an automated agent closed it. It is the metric used to justify any investment in self-service or in AI.
