Support Metrics
Average Resolution Time
Definition
Average resolution time (ART) is the mean time it takes to fully resolve a support request, measured from when it is first received to when it is marked as solved.
In depth
Average resolution time (ART) measures how long it takes, on average, to fully resolve a support request, from the moment it arrives to the moment it is marked as solved. Where first response time captures the wait for a first reply, resolution time captures the wait for the actual fix.
The calculation is a simple mean: add up the resolution time of every ticket over a period and divide by the number of tickets resolved. If 500 tickets take 2,000 hours between them, the average resolution time is 4 hours. Teams usually track it by channel and by ticket type, because a billing query and a technical fault sit on very different timescales.
Because it spans the whole life of a ticket, ART is sensitive to everything that happens along the way, from how quickly the first agent picks it up to how many times it is handed between people. That makes it a good barometer of overall support health, best read next to first response time.
What counts in resolution time?
The main decision is where the clock starts and stops, and whether it pauses. Most teams start it when the request is received and stop it when the ticket is marked resolved, but they pause it while waiting on the customer, so a slow reply from the customer's side does not count against the team. As with other time metrics, measuring in business hours keeps overnight and weekend gaps from skewing the average.
It is also worth separating resolution time from handle time. Resolution time is the customer's total wait; handle time is only the minutes an agent spends actively working the ticket. A case can have a short handle time and a long resolution time if it spends hours sitting in a queue.
What's a good average resolution time?
There is no benchmark that fits every team, because resolution time depends so heavily on how complex your tickets are. A password reset and a data-migration issue belong to different worlds, and averaging them hides as much as it reveals.
The most useful comparison is your own history. Break the average down by ticket type, watch each trend over time, and focus on the categories where time is being lost to waiting or repeated handoffs. Resolving routine questions instantly with self-service is one of the most direct ways to bring the overall average down, because it removes the simplest cases from the queue entirely.
Average Resolution Time = Total Resolution Time for All Tickets / Number of Resolved Tickets
Why it matters
Example
A support team resolves 500 tickets in a month. Add up the time each one took from arrival to resolution, say 2,000 hours in total, and divide by 500. The average resolution time is 4 hours. Tracking that figure over time shows whether changes to staffing, tooling, or documentation are actually speeding things up.
How Resolve247 helps
Reduce resolution time with Resolve247
AIChatbot resolves up to 82% of questions the instant they are asked, so those cases are solved in seconds rather than hours. For tickets that reach your team, ResponseAssistant drafts the reply for them, cutting response time by up to 70% and moving each case towards resolution faster.
30 day free trial, no cc required!
Related terms
Frequently asked questions
How is average resolution time calculated?
Add up the total time taken to resolve every ticket over a period, from first received to marked solved, then divide by the number of resolved tickets. Many teams also report it in business hours so time outside working hours does not distort the figure.
What is the difference between resolution time and handle time?
Resolution time is the full elapsed time until the customer's issue is solved, including any waiting. Handle time is narrower: it counts only the time an agent actively spends working on the ticket. One measures the customer's wait, the other measures agent effort.
What is a good average resolution time?
It varies widely by the complexity of your tickets and your industry, so there is no universal target. The most useful benchmark is your own trend: watch the average fall as you remove bottlenecks and let automation handle routine cases.
How can you reduce average resolution time?
Resolve routine questions instantly with self-service, give agents the context and draft answers they need up front, and fix the process handoffs that leave tickets waiting. Reviewing your slowest tickets usually shows where the time actually goes.