What Is Resolution Time in Customer Support

Replying fast is nice, but what the customer really wants is for their problem to be solved. That's where resolution time comes in: the metric that measures how long your team takes from the moment a case opens until it's fully closed. If first response time is the front door, resolution time is the whole experience.

In 2026, with customers used to instant service and one-click brand comparisons, a long resolution time turns into frustration, reopened tickets, and churn. Let's break down what it is, how to calculate it, and what you can do to improve it without sacrificing quality.

Definition: what resolution time is

Resolution time (also time to resolution, or TTR) is the total period between when a request is opened and when it's definitively closed. It includes everything: replies, waits, internal escalations, and back-and-forth with the customer.

There are two ways to look at it, and they shouldn't be confused:

• Total (gross) resolution time: the real calendar clock, open to close, with nothing subtracted.
• Effective (net) resolution time: only time within business hours and, sometimes, minus the time the case spent waiting on the customer.

Net is fairer for judging your team's performance, because it doesn't penalize them for a customer who took three days to reply.

How to calculate resolution time

For a single case:

Resolution time = Close date/time − Open date/time

For your operation's average:

Average resolution time = Sum of all resolution times / Number of closed cases

One important tip: don't stop at the average. Look at the median and the percentiles too (for example, P90). A handful of very complex cases can inflate the average and paint a misleading picture. If your average is 8 hours but P90 is 3 days, you have an outlier problem the average is hiding.

What a good resolution time looks like

It depends heavily on the type of query and the channel. A hours-of-operation question resolves in seconds; a complex technical incident can legitimately take days. That's why an absolute number is less useful than segmenting:

• By case type (simple query, complaint, technical incident).
• By channel (chat is usually faster than email).
• By priority or agreed SLA.

Setting internal SLAs (for example, "simple queries under 1 hour, incidents under 24 hours") gives you concrete, measurable goals instead of a generic figure.

Factors that stretch resolution time

1. Lack of context: the agent wastes time asking for data that was already in the history.
2. Agent-to-agent bounces: each handoff resets the customer's mental clock.
3. Scattered information: if the answer lives in three systems, it takes longer.
4. No prioritization: urgent cases stuck behind trivial ones.
5. Repetitive manual work: copying, pasting, and searching by hand.

How to reduce resolution time

Give the agent full context

A unified customer history, with every prior conversation across any channel, keeps the agent from starting from zero. With Omnifox, each conversation arrives with the contact card and the omnichannel history in view, so agents resolve without asking the same thing twice.

Automate the repetitive

An AI agent can resolve frequent queries end to end, leaving humans the cases that truly need judgment. That noticeably lowers average resolution time.

Use a knowledge base and macros

Saved answers for the most common problems let agents resolve in one click instead of writing from scratch.

Route by skill

If the case lands directly with the agent who knows how to solve it, you avoid escalations and waits.

Define and monitor SLAs

Alerts when a case nears its time limit keep it from being forgotten at the bottom of the queue.

Resolution time vs. other metrics

Don't work this metric in isolation. Pair it with:

• FRT (first response time): the speed off the starting line.
• FCR (first contact resolution): how many cases close without back-and-forth.
• CSAT: whether resolving fast actually left the customer happy.

A low resolution time with a low CSAT is a red flag: you may be closing cases without truly solving them.

Conclusion

Resolution time is the metric that best reflects the core promise of your service: solving the customer's problem. Reducing it isn't about rushing agents; it's about giving them context, tools, and automation so every case moves without friction.

If you want to close cases faster with the full customer history on one screen and automate the repetitive parts, start trying Omnifox today.