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Outbound Call Center Metrics (13 Top KPIs)

Published: Apr 20, 2022

Results for outbound call centers are improved by carefully managing call center metrics in combination with key performance indicators (KPIs). The choice about what metrics to measure and track is an integral part of a successful strategy for an outbound call center campaign.

outbound call center metrics

Selecting Call Center Metrics

There are many metrics to consider for strategic success, which can be chosen to support the goals of the organization running an outbound call center program. Here are some popular outbound call center metrics and an explanation about why they are good to monitor:

First Call Close

This metric is probably one of the most valuable to track for many organizations. If an agent gets a potential client on the phone; this is the best time to close the deal. Call-backs have very low-performance metrics and can be a huge waste of resources.

Conversion Rate

This is the percentage of calls that resulted in a successful outcome. Some examples of this include the number of sales, appointments made, or survey questions answered.

Calls per Agent

This metric tracks the efficiency of each agent. Agents who are not motivated to make calls can severely lower success results. Automated dialing improves this metric. A subset of this metric is the number of dials per hour.

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Calls per Account

This metric tracks the number of calls and whether a connection was made. A high number of calls per account, without a success, may indicate that an account should be removed from the program.

Hit Rate In Call Center Metrics

The hit rate is calculated by dividing the calls made by each agent with the number of those calls answered by a prospect. Success depends on having a high hit rate.

Hold Time

Use of automated dialing, to maximize efficiency, occasionally means that potential prospects, after they answer the phone, are waiting on hold for an agent to speak with them. This time should be as close to zero as possible because the longer, on average, that it is per call; more call abandonment occurs.

Abandoned Call Ratio

This is a calculation of the number of lost calls while a prospect is waiting on hold for an agent. This should be very low; otherwise, the automatically dialing speed should be reduced to lower this ratio.

Average Call Length

This metric is useful for fine-tuning adjustments in the call presentation, also known as the “pitch”. Pitches that take too long, can reduce success.

List Closure Rate

This rate measures the percentage of prospects that were closed in comparison to the total number of potential prospects for a targeted, outbound call center campaign. A low rate indicates problems with the calling list, such as bad numbers, cold leads, or the improper inclusion of “do not call” numbers.

On-Call Rate

This metric compares the amount of time an agent spends on calls against the amount of time spent between calls either taking down notes, filling surveys or possibly being delayed.

Call Quality

This metric is usually a scoring system that is used for an independent audit of calls. This is done by reviewing a statistically appropriate amount of the live audio of the calls or the audio recordings of the calls. Things to consider include, is the agent staying on the pitch script, being polite, and engaging the prospect?

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Call Etiquette

Call etiquette is a subset of call quality. Because the differences are subtle, this metric can be easily overlooked. However, it turns out to be a very powerful way to increase success. It is more than simply being polite. It includes conversation rules that psychologically improve call outcomes. One rule is, to avoid the use of negative language. For example, a bad response would be, “It is out of stock.” A better response is, “If you order now, you will be one of the first to receive it when it comes in.” Another example is to avoid putting a prospect on hold. If it is absolutely necessary to put a call on hold, the agent should explain why (such as getting a supervisor to take the call) and give the prospect an accurate hold-time estimate.

Revenue per Successful Call

This is about maximizing revenues for each successful close made on a call. An example of an enhanced technique for this metric is to use an offer of an up-sale to increase revenues, such as, after concluding the first order, adding a second order of the same item for a discounted price.

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Setting Benchmarks For Call Center Metrics

Experienced call center managers are helpful in setting up the initial performance benchmarks for a new outbound call center program. These benchmarks are, at first, estimated based on the past performance of similar outbound call center projects. Benchmarks are used from other outbound call center campaigns that are in the same industry sector or have other characteristics that make them a good choice for comparative purposes.

After a new outbound call center program runs for a while; it sets its own benchmarks by the results achieved. Then, the goal is to improve on the past results by making modifications to the calling processes in fine-tuning the campaign to make the program more effective.

Monitoring Performance

Real-time monitoring of outbound call center performance against the benchmarks allows the call center management staff to quickly make adjustments that increase performance. Experienced human technicians typically use an A/B test as guidance for making program adjustments. In an A/B test, one parameter is adjusted in the A group and measured against the same number of calls for the B group. For example, 1,000 calls can be tested for a specific time of day against 1,000 other calls at a different time of day in order to compare results.


Using outbound call center metrics effectively in an outbound call campaign can substantially increase a campaign’s effectiveness. Experience call center managers that are highly skilled in creating, monitoring, and adjusting the metrics are appropriate choices in order to deliver the desired results. These efforts may be enhanced by applying new methods of data analysis.


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