First response time (FRT) is how long a customer waits between submitting a support request and receiving the first reply that meets your definition of a response. To measure it usefully, define what starts and stops the clock, which requests count, and whether you use calendar or business hours. Then report the result alongside unanswered requests, response quality, and resolution outcomes: a quick reply is not necessarily a helpful one.
What first response time measures
FRT, also called first reply time, measures the wait for the first qualifying response—not the time it takes to solve the customer’s problem. Salesforce describes it as the time for a support representative to send the first meaningful reply after a customer submits a request. That wording highlights an important distinction: a receipt confirmation may show that a request arrived, but it may not answer the customer’s question or advance the case.
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Zendesk uses a specific ticketing definition: its first reply time runs from ticket creation to the first public agent comment. A ticket solved without a public comment does not contribute to Zendesk’s FRT metrics. Zendesk’s documentation also says most bot or automated actions do not count toward standard first-reply reporting, with documented exceptions; messaging and live chat have additional reporting details. Those are product-specific rules, not a universal definition for every support system.
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- Resolution time: how long it takes to solve or close a request.
- First-contact resolution: whether the issue is resolved in the first interaction.
- Target attainment: the share of eligible requests answered within a defined response goal.
These measures answer different questions. A team can reply quickly but need many follow-ups to solve issues, or take longer to reply while resolving them in one exchange. Reading them together gives a more complete view of service.
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Define the metric before calculating it
Two FRT figures are only comparable if they use the same rules. Write down the definition before setting a target, comparing teams, or reviewing a trend. In particular, settle the following choices:
- Start event: Does the clock begin when a customer submits a form, when a ticket is created, or at another recorded event? If those timestamps differ, specify which one is authoritative.
- Stop event: Is the first qualifying reply a public human response, a meaningful answer, or a separate acknowledgement? If acknowledgements count, say so.
- Eligible population: Decide how to handle requests with no reply, tickets solved without a public answer, agent-created tickets, spam, merged tickets, and reopened requests. Keep the same inclusion and exclusion rules from one reporting period to the next.
- Clock convention: Choose calendar time or staffed business time. For business time, document the staffed hours, time zone, and holiday calendar.
- Channels: Specify whether email, web forms, social, messaging, live chat, and phone are reported together or separately. Their service expectations and reporting rules may differ.
Keep an FRT definition separate from the service-level agreement (SLA) that sets a response goal. Zendesk documents calendar-hour and business-hour versions of first-reply values. Its SLA targets can pause outside business hours, while standard reporting and SLA calculations may behave differently. Record both the metric’s clock convention and the SLA’s rules so a change in one is not mistaken for a change in the other.
Calculate and report FRT
For each eligible request that has a qualifying reply, subtract the start timestamp from the timestamp of that reply. For example, if a request is submitted at 10:00 a.m. and its first qualifying response is sent at 11:15 a.m., its FRT is 1 hour and 15 minutes under a calendar-time definition. Under a business-hours definition, the elapsed value depends on the service schedule and any applicable pauses.
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For a reporting period, calculate the average by adding the qualifying intervals and dividing by the number of eligible requests with a qualifying reply. Publish that denominator and your exclusion rules with the result. Do not let unanswered requests disappear from the operational picture just because they cannot yet have a completed first-reply interval: report them separately as an unanswered queue, with its size and age.
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Use more than one summary. An average can be pulled upward by a small number of very slow cases; a median shows the midpoint and can better describe a typical wait when there are outliers. Neither tells the whole story, so include target attainment and inspect the slow tail as well.
| Measure | What it tells you | What it can miss |
|---|---|---|
| Average FRT | The mean wait among requests with a qualifying reply. | A few very long waits can pull it upward; it does not show unanswered requests unless those are reported separately. |
| Median FRT | The midpoint wait among requests with a qualifying reply. | A reasonable midpoint can coexist with a small group of customers waiting much longer. |
| Share answered within target | How often replied-to requests meet the stated goal. | The goal, eligible population, and clock convention must be clear; this measure alone does not describe waits beyond the target or unresolved requests. |
| Unanswered queue and age | How many requests still lack a qualifying reply and how long they have waited. | It is a live backlog view, not a completed FRT statistic. |
Zendesk recommends reviewing first-reply reporting alongside ticket volume and CSAT feedback. A useful broader scorecard can also include FRT by channel, priority, product area, request type, team, and time of day where the data supports those cuts; backlog age; first-contact resolution; and resolution time. Interpret segments carefully: a channel or team with a different case mix may not be directly comparable to another.
Set targets without mistaking examples for benchmarks
There is no single universal FRT target established by the sources used for this article. A reasonable goal depends on the channel, the promise made to customers, staffed hours, urgency, and the kinds of issues the team handles. Set explicit goals by channel and priority when those needs differ, then assess performance against the same definition over time and against customer feedback.
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Diagnose delays before changing the workflow
Start by locating when and where waits increase. Compare FRT with incoming volume and backlog, then segment by channel, priority, and time of day if the underlying data is consistent. A brief increase during an unusual demand spike calls for a different response than a recurring gap in coverage or a queue that grows steadily. Zendesk recommends using ticket-created-by-hour reports to understand demand and coverage patterns.
Use the pattern to choose an intervention rather than issuing a blanket instruction to respond faster:
- Match coverage to demand. Look for predictable periods when requests arrive faster than the team can handle them. Adjust coverage where the pattern supports it, and check whether the backlog and slow tail improve afterward.
- Improve triage and routing. Make urgent requests visible, apply priorities consistently, and assign tickets promptly. For messaging, review unassigned queue time and configure routing to match agent capacity.
- Help agents find and send useful answers. Train agents on products and policies, maintain internal documentation, and create reusable reply macros or templates. Agents should personalize a template to the customer’s issue rather than use a fast but irrelevant stock response.
- Reduce avoidable repeat questions. Create customer-facing articles for recurring issues and keep them current. Clear self-service content can reduce repeated requests and free agent capacity for cases that need individual help.
- Choose channels that fit the need. Offer a faster live channel when it is appropriate and staffed. When a customer moves between channels, preserve the case context so they do not have to start over.
- Check service quality as well as speed. Review CSAT, customer comments, first-contact resolution, and resolution time with FRT. If speed improves while customers still cannot make progress, the change has not solved the underlying service problem.
Use automation without distorting the measure
Automation can assist with triage and routing, and prewritten replies can reduce the time agents spend composing common answers. But the metric should reflect the event the organization intends to measure. Decide whether an automated acknowledgement counts as a response; if the intended measure is time to a meaningful support reply, track acknowledgement time separately rather than allowing an automatic receipt message to make substantive FRT appear shorter.
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Frequently Asked Questions
Should FRT include requests that have not received a reply yet?
A request without a qualifying reply does not have a completed first-response interval. Keep those requests visible in a separate unanswered-queue count and age view so a completed-response average does not hide current waits.
Can I compare first response time across phone, live chat, and email?
Only with care. First define the start and stop events and clock convention for each channel, then report channels separately when the definitions or customer expectations differ. A combined number can conceal important differences.
Does a faster first response mean customers are getting better support?
Not by itself. FRT measures the wait for a first reply, not whether that reply resolves the issue or helps the customer make progress. Read it alongside feedback and resolution measures.
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