Call Center Metrics

The most important Call Center metrics and KPIs. Learn about what metrics and KPIs are best for you, vote, and contribute your own.

Agent Wait Time

Agent Wait Time (Calendar) is the total combined time a ticket was in the pending status. Not to be confused with user-facing metrics such as First Response Time or Resolution Time, Agent Wait time measures the time the support agent has to wait between interactions. Task switching and waiting for replies is an inevitable part of the job but, the longer an agent has to wait for a reply, the less efficient and effective they will be at solving the problem.

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Average Speed to Answer

Average Speed to Answer (ASA) is the average amount of time taken for a call centre agent to answer an inbound customer call, including time spent waiting in a queue. It excludes time spent navigating an IVR system. This metric one of the most important signals tied to customer satisfaction.

Call Abandon Rate

Call Abandon Rate is the percentage of people who hang up before they are able to reach an agent. Abandon Rate is very closely related to Average Time to Answer.

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Call Volume

Call Volume is the count of both incoming and outgoing calls handled. It can be used to measure the number of incoming calls to a Customer Support organization, outgoing calls from a Sales team, calls queued to an Automatic Call Distribution (ACD) service, and dropped calls. Tracking this metric helps you determine required staffing levels and understand customer behaviour.

Call-in Rate

Call-in Rate is the average number of inbound calls received per paid user of a product or service. It is used to monitor changes in call volumes, which can be an early warning sign of product or service issues, and even potential churn.

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Customer Satisfaction

CSAT is a measure of the level of satisfaction that a customer has with a company’s products and/or services, most often provided by the customer as part of a survey. It is commonly used as an indicator of a customer’s loyalty to a company.

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First Contact Resolution Rate

First Contact Resolution Rate (FCR Rate) is the percentage of customer contacts that are resolved on the first interaction with the customer. If a customer's issue can be resolved on the first contact, it eliminates the need for either the agent or the customer to follow up.

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First Contact Resolution Tickets

First Contact Resolution Tickets is the count of customer tickets that are marked as solved by agents on the first attempt. Whether it's a single phone call, a chat conversation or an email response - the customer leaves happy and so does your staff!

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First Response Time

First Response Time (FRT) is the average amount of time an agent takes to provide an initial response to a customer inquiry or support ticket. The speed at which you acknowledge a customer's question is a reflection of your commitment to customer satisfaction and the maturity and efficiency of your call centre.

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Full Resolution Time

Full Resolution Time is the time duration between the ticket creation date and the ticket solved or closed date. Along with a solution that helps the customer and solves the problem, the less time it takes to get to a resolution is good for you and good for the customer. Resolution time is usually measured in hours or days.

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Requester Wait Time

Requester Wait Time (Calendar) is the total combined time a ticket was in the new, open, and on-hold statuses. This number is measured only after a ticket's status changes to pending, solved, or closed. Unlike Full Resolution Time, Requester Wait Time does not take into account pending time – the status set when a ticket is waiting for an answer from the requester.

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Ticket Reopen Rate

Ticket Reopen Rate (RR) is the percentage of solved tickets that have been reopened by customers. It is important for a support team to track ticket reopen rate, as this can provide insight into how well their customer service is performing. Reopen rates provide a direct measure of customer satisfaction with the service they receive and can help determine where improvements need to be made. For example, if an unusually high number of tickets are being reopened after they have been marked as solved, it could be a sign that customers are not getting the answers they need or that agents are not providing satisfactory solutions.

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