What are the Quality Assurance metrics?

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Quality assurance or quality control plays an important role in any industry. It provides the means through which the defects and the problems while delivering a manufactured product or any service can be prevented. Though the terms, quality control, and quality assurance are used interchangeably these days, there is an underlying subtle difference between them.

Each and every industry has their own guideline & benchmark for customer satisfaction and performance. Many industries across the vertical, use the familiar data-driven DMAIC model for improvement. DMAIC stands for define, measure, analyze, improve and control. While in the BPO industry including the various b2b call center, quality assurance is used as a comprehensive evaluation system. It is the major guiding system to improve and revamp the productivity of the workforce. And this is achieved through various common quality assurance metrics such as average handle time (AHA), first call resolution(FCR), customer satisfaction rate(CSAT) etc.

The first step towards improving one’s quality assurance metrics is to define the desired goals of the quality assurance(QA) program. For instance, is it to increase the customer satisfaction or to boost the performance of the agents. Based on the need, choose the QA metric that best aligns with the goals of the enterprise. Then, establish a method to record and evaluate these metrics.

Now let us dive into some common contact center QA metrics

Average Handle time-

It is the average time taken to successfully complete a transaction, it can either be a telephonic conversation, a chat or any other means of customer interaction. A typical transaction includes any hold-time, talk time or any related task performed during the transaction. Both b2c and b2b call center should strive to achieve a low AHT coupled with a high customer satisfaction rate.

Net promoter score-

The NPS is a yardstick tool to examine the customer loyalty and customer satisfaction of a business. For instance, it can tell us how likely is a customer to recommend a business to his/her friends and relatives.

Customer satisfaction score-

CSAT measures the degree to which a customer is satisfied after interacting with an agent. It can be a simple scale of 1 to 10 or any other customized scale. Its advantage is that it is simple, concise and intuitive.

Average speed of answering-

It is a customer-centric metric that gauges the average time taken by the contact center to answer an incoming call.

Customer effort score-

The goal of this metric is to rate the effort of a customer during a call. It is quite similar to the CSAT score but instead of the satisfaction level, the customer effort is measured. Contact center enterprises aim to lower their CES so as to keep their customers happy.

B2c and b2b call center companies utilize these metrics in various ways to keep their quality assurance top notch. These are a great tool to boost productivity and reduce costs. Now let us take a quick look at how these metrics can benefit an enterprise:

Enhance customer experience-

With better call handling, efficient call routing, and the application of other operational refinements QA metrics gives us an insight into how to customize the functionalities within a contact so as to improve the user experience.

Consolidate agent performance-

These metrics provide the management with detailed information on how to strengthen and refine the training procedures and build a stronger and better framework so as to extract the optimum productivity of the agents.

Boost operational Performance-

Inefficiencies can frustrate customers as well as affect the performance of the whole process. With the help of these metrics, the managers can establish the key areas of improvement. And brainstorm better and ingenious methods and tactics to bolster operational performances of the b2c and the b2b all center campaigns.

Cost reduction-

As mentioned above, these metrics are the key to cost reduction in an enterprise. A well-oiled engine is an efficient one. And as efficiency goes up, the average or per unit costs of running an operation significantly goes down.

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