TL;DR

How long it takes, end to end, to actually solve a customer's problem and close the conversation.

Key Points

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Average resolution time = total resolution time for all solved cases divided by the number solved in a period. [2][3]

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It spans the whole lifecycle: wait time, investigation, every back-and-forth [[chat-message]], and any [[escalation]] before close. [1]

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Decide up front whether you measure in calendar time or [[business-hours]], and whether time waiting on the customer counts. [3]

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Distinct from [[first-response-time]] and [[average-response-time]]: those clock the first reply, this clocks the fix. [1]

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A few outlier cases skew the mean, so tracking median and percentiles (P50/P90) gives a truer picture than the average alone.

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Fast resolution that leaves the customer confused is worse than slower resolution with clear updates, so pair it with [[customer-satisfaction-score]]. [3]

What resolution time measures

Resolution time captures the customer's lived experience of getting a problem fixed, not just the speed of the first reply. The clock starts when a visitor or Contact opens a Conversation and stops when the issue is genuinely solved and the case is closed. ^[1] Because it covers waiting, investigation, internal handoffs, and repeated message exchanges, it is a broader efficiency signal than First Response Time (FRT) or Average Response Time. ^[3] Many help desks split it into first resolution time, ending at the first solve, and full resolution time, ending at the last solve if a case is reopened, so you can see how often a fix actually sticks. ^[4]

How to calculate it

The standard formula is total resolution time for all solved cases divided by the number of cases solved in the period. ^[2] For example, three cases closed in 2, 4, and 6 hours give 12 hours over 3 cases, or a 4-hour average. ^[2] The number is only meaningful once you fix the rules: whether you measure raw calendar hours or only Business Hours, and whether time spent waiting on the customer is paused. ^[3] A common refinement is to report the median and high percentiles (P90, P95) alongside the mean, since a handful of stalled cases can otherwise drag the average far from typical experience.

Reducing resolution time

The biggest wins come from removing friction rather than rushing agents. Routing the right cases to the right Support Operator quickly, defining clear Escalation paths, and reusing answers through a Knowledge Base or canned responses all cut the back-and-forth that inflates the number. ^[1] Self-service and Ticket Deflection keep simple questions from ever becoming open cases. In a lightweight Live Chat product like Eloqra, where operators reply through Telegram and there is no Ticketing System or SLA engine, resolution time is best read informally as the gap between a visitor's first Chat Message and the moment their Conversation is marked Closed. ^[4]

Sources & References

Gorgias - Resolution Time: What to Aim For and How to Decrease It ↗

Geckoboard - Average Resolution Time (KPI examples) ↗

Front - Time to resolution metric: everything customer support needs to know ↗

Zendesk Help - About native Support time duration metrics ↗

Last updated: June 25, 2026

Related Terms

First Response Time (FRT)

First Response Time (FRT) is the elapsed time between a customer's first message in a conversation and the first human reply from a support agent. It measures how quickly your team acknowledges an inbound request, not how long it takes to resolve it.

Average Response Time

Average Response Time (ART) is a support metric measuring the mean time customers wait for an agent reply across all messages in a period, not just the first one. It is calculated as total wait time divided by the number of replies sent.

First Contact Resolution (FCR)

First Contact Resolution (FCR) is the percentage of customer issues fully resolved in a single interaction, with no transfer, callback, or follow-up needed. It measures how often a support team solves a problem the first time the customer reaches out.

Customer Satisfaction Score (CSAT)

Customer Satisfaction Score (CSAT) is a support metric that measures how happy a customer is with a specific interaction, product, or service, usually captured by a short post-interaction survey. It is expressed as the percentage of respondents who rate their experience as satisfied or very satisfied.

Service-Level Agreement (SLA)

A service-level agreement (SLA) is a documented commitment between a service provider and its customers that defines the standard of support to be delivered, such as how fast inquiries are acknowledged and resolved, and how that performance is measured. [1]

Escalation

Escalation is the process of moving a customer issue from a first-line agent to someone with more seniority, authority, or specialized expertise when it cannot be resolved at the current level. It routes the conversation to the person best equipped to solve it, rather than leaving it stuck.

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