Adding Quality Metrics to Your Data Analytics

    If you can’t measure it, you can’t manage it, especially when it comes to quality assurance. 

    How can you tell if you’re providing a quality customer experience if you don’t have call center metrics to tell you exactly how you’re performing? You can’t.

    The good news is that there are many critical quality metrics that any contact center can easily add to their data analytics. 

    We’re not talking about average call handle times or calls per hour, which are highly relevant but probably already part of your analytics process, we’re talking about true benchmarks of your contact center’s efficacy and seeing how you can improve call center QA.

    What Quality Metrics Should You Measure?

    There are many available KPIs for contact centers: from those that measure sales to those that measure productivity. But what are the metrics that measure quality and customer satisfaction?

    Turn complex QA data into actionable insights

    1. First Contact Resolution (FCR)

    First Contact Resolution (FCR)—also known as first call resolution—is one of the most essential quality metrics in your arsenal. It helps you keep track of whether or not repeat contact or callbacks are necessary across every channel. 

    It’s the gold standard quality metric for customer satisfaction, helping you measure whether anything is missing that causes your customers to contact you again to resolve their query. 

    Just make sure to define exactly what FCR means for your contact center before you start measuring. Does it mean the customer didn’t have to call back or does it mean they didn’t have to be transferred to multiple agents to find the answer? Once you define FCR, then you can set the benchmark.

    2. Service Level & Response Time

    You need to ensure your Service Level Agreements (SLAs) are met, which means you need to measure your call center QA metrics, your service level, and response time rates. These QA metrics reveal how easy it is for customers to access your contact center, how many agents are required to deliver exceptional customer service, and how your contact center compares to your competitors. 

    Together, these metrics illustrate what your customers experience whenever they contact you. Your aim should be consistency no matter how busy you get.

    3. Schedule Adherence

    How well your agents adhere to a schedule is not just a metric of productivity, it also demonstrates how well your agents are performing. The goal is for each agent to achieve 80 to 90 percent schedule adherence, and to keep your agents accountable.

    4. Contact Quality Management Score

    Whatever method your customers use to contact you—call, email, live chat, social media, etc.—an essential metric is your quality management score. This measures how well your agent was able to help the customer based on their skills. It measures:

    • Product knowledge
    • Technical knowledge
    • Communications skills
    • Problem solving skills

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    5. Reason for Contact

    A quality metric that is often overlooked is the reason why your customers contacted you in the first place. Keeping track of why someone called—or even called back again—will help you discover weaknesses in your self-service tools, support, and technical knowledge. The last thing you want is the same question/concern coming up over and over again without any improvement.

    6. Employee Engagement

    Employee engagement is extremely important for customer satisfaction, since your agents are the single most important factor when it comes to customer experience. The more engaged your employees, which can be tracked by conducting both quantitative and qualitative surveys, the more likely they are to provide high quality support for your customers.

    How and Where do Business Intelligence Tools Fit In?

    Once you start measuring your quality metrics, you then have another challenge —you have to sift through the mountains of data to make informed, real-time decisions. 

    That’s where business intelligence (BI) tools can help. These tools can help you extrapolate insights from your metrics in order to improve overall customer satisfaction and boost efficiency.

    BI tools help you capture all of your agents’ actions, so you can identify trends, tasks, and behaviors. Then, you can take this information and make changes to your contact center. 

    For example, BI can help you identify repetitive tasks that can be automated for improved service and cost efficiency. It can also help you predict staffing demands by analyzing call trend volume or answer questions such as, “Who is our top performing agent in terms of customer satisfaction?” 

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    Adding in Quality Scores

    One of the most valuable business intelligence tools for any contact center quality assurance program is customer experience scoring, which can be either internal (self-scoring) or external (Net Promoter Score). Quality scoring provides you with a consistent and effective way to determine customer satisfaction from either your agent’s perspective or the customer’s. Both are invaluable for helping your contact center improve the customer experience.

    When it comes to internal quality scoring, Scorebuddy has powerful reporting and analytics tools that allow you to spot trends and exceptions, so you can manage, coach, and improve. Using a selection of over 30 reports, Scorebuddy makes it easy to dig deep into your call center’s quality scores and carry out a root cause analysis to identify common pitfalls, broken processes, or training gaps. 

    You can also catch agents who are performing at the best-in-class level and recognize their good work, which improves agent engagement and loyalty.

    For external quality scoring, your Net Promoter Score (NPS) measures customer satisfaction on a scale of 0-10. It tells you how likely it is that a customer would recommend your brand to a friend or colleague, which reveals whether you have happy or unsatisfied customers. 

    It’s a simple survey that you can provide to customers after their contact with you to see how satisfied they are with the result. Combined with the quality metrics mentioned above, it can help you find gaps in the customer experience.

    There are countless reasons to add quality metrics to your data analytics and there are almost just as many metrics to consider. Once you decide what makes the most sense for your contact center and implement a scoring and reporting software such as Scorebuddy (along with a BI software, where there is a need for more sophisticated analyses) into your QA process, you’ll be set up for success—able to consistently improve the customer experience and your contact center’s efficacy.


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