Automated quality management: What contact center leaders need to know

Madeline Jacobson

January 17, 2024

If you’ve ever been responsible for quality management (QM) in a contact center, you know what a time-consuming and mind-numbing process it is. You listen to a call recording (or review a transcript), evaluate 20+ standard checklist items, record the overall score, and repeat. It’s no wonder the typical contact center only reviews about 1 to 3% of their customer conversations.

However, it’s now possible for contact centers to review 100% of their customer conversations–without hiring an army of QM or quality assurance (QA) managers. Automated quality management software can complete the objective fields on a QM scorecard or checklist, dramatically reducing manual work and increasing visibility into each agent’s overall performance. 

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Why contact centers should automate quality management

Quality management aims to improve agent performance and the customer experience. But it’s difficult to identify meaningful coaching opportunities when you’re only reviewing a small percentage of your agents’ interactions. Don Davey, Tethr’s Senior Director of Customer Success (and a veteran contact center leader) puts it this way: “If you were a contact center agent who handled 1000+ customer interactions per month and I did a QM review of 8-10 of your interactions, do you think I would have enough information to accurately determine if you were a good or bad agent on ALL of your interactions?”

The traditional QM process suffers from limited data and takes up the valuable time of QM, QA, or contact center managers. The more time a manager spends completing QM scorecards, the less time they have to spend on deeper data analyses, strategic planning, and agent coaching.

Quality management automation lets you scale your QM program while also freeing up more time for your managers to focus on impactful activities. Your operational leaders get a better view of how your contact center is performing, your managers get the data they need to provide actionable coaching recommendations, and your agents get targeted feedback to help them improve. 

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How automated quality management works

Quality management automation relies on machine learning, a branch of artificial intelligence. Machine learning models are trained on data sets to find new mathematical relationships in that data. In the case of automated quality management, a contact center’s customer conversations provide the data (i.e., language), and machine learning models use the relationships between words to determine meaning. This allows your QM automation platform to flag when your QM scorecard items occur based on the language your agents use.

Let’s say one of your scorecard items is, “Did the agent set appropriate expectations?” There are different phrases an agent can use to set expectations, many of which will depend on your organization’s policies (e.g., “You should receive an email confirmation in a few minutes,” “I will schedule a follow-up call for you,” etc.). You can train a machine learning model to recognize all of the different expectation-setting phrases (and their variations) and flag where they occur in transcripts. 

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What to automate in the QM process

Questions that have a clear yes or no answer based on what the agent or customer says are great candidates for QA automation. Questions that require critical thinking are best left to a human evaluator. For example, a question like “Did the agent demonstrate active listening skills?” can’t be easily automated, but a question like “Did the agent ask probing questions to diagnose the issue?” can.

You can automate many of the most common items on QM or QA scorecards, but certain performance areas (such as agent knowledge gaps, demonstration of soft skills, and proper tone of voice) are best left to human evaluators.

Consider bringing your automated scorecards and manual evaluations together in a conversation intelligence platform like Tethr. This gives you a central view of your agent performance data. It also allows you to minimize repetitive, manual work while still maintaining a human touch when necessary.  

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5 benefits of automated quality management

Enhanced efficiency

The potential time savings of QM automation are huge. We’ve seen Tethr customers reduce their call monitoring time by 80% when they automated their quality management. That’s 80% more time for managers to spend on coaching and initiatives to improve the customer experience. 

Cost-savings from reduced labor

QM automation helps your current managers get more high-value work done and helps your contact center perform more call reviews without growing your headcount. For example, one of our customers, BCLC, shared they were planning to hire two more QA agents but didn’t have to after implementing Tethr. 

Objective evaluation of agent performance

Automating the QM process takes human bias out of the equation. It allows you to track and measure key performance indicators consistently, giving you a standardized approach to evaluating agent performance. This means agents get data-backed coaching to help them improve, rather than broad feedback based on a handful of their conversations.

Reduced compliance risk

By leveraging automation, you can monitor all customer interactions and track whether agents are staying in compliance with regulatory requirements and industry standards. With QM automation software, your contact center can identify potential violations and address them before they lead to fines, legal action, or damage to your brand reputation.

Insights to inform the customer experience

When you review 100% of your customer interactions, you can identify big-picture trends in agent behaviors and see what controllable factors are impacting the customer experience. From there, you can coach your agents on the behaviors proven to have the biggest positive impact on CX.

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Best practices for automated quality management

Measure what your agents control

When thinking about what to include on your automated QM scorecard, focus on the things your agents can do to positively impact the outcomes your business cares about. For example, including a question like “Did the agent offer further assistance while closing?” helps hold agents accountable for behavior that reduces the likelihood of repeat contacts.

Look at the agent behaviors proven to impact customer satisfaction

Many common QM items, such as “Did the agent use the proper greeting?”, appear on scorecards because they’re easy to confirm and occur on every call. However, basic QM requirements like this don’t necessarily lead to customer satisfaction. The things that do impact customer satisfaction are agent behaviors like acknowledging the customer’s issue, using advocacy language, and setting expectations for next steps–all of which can be tracked with QM automation software.  

Set expectations with agents

Before rolling out your QM automation software, meet with your agents to explain what will be automated and why your contact center is investing in this technology. Highlight the benefits to your agents: namely, that they’ll be objectively evaluated on all their conversations, will receive data-backed coaching, and will be able to more easily measure their improvements.

Set expectations with QM managers

Quality management automation will be an adjustment for your QA or QM managers. Explain that they should expect to see different results with automated reviews than manual reviews because 100% of interactions are being objectively evaluated. This is a good thing because it will help your managers measure their team members’ performance at scale and improve their coaching.

Final takeaways

Traditional quality management isn’t a good experience for the manager or the agent. Managers waste valuable time completing QM scorecards and may only spot-check a handful of interactions per agent each month. Agents only get feedback on a small percentage of their calls, making it difficult for them to learn how to make meaningful improvements. 

While there’s value in manually evaluating agents on certain criteria, such as pace and tone of voice, the bulk of your QM criteria can be automated thanks to machine learning. It’s a win for your managers, who have more time to spend on critical-thinking activities, and for your agents, who get targeted coaching to help them improve. (It’s also a lot more cost-effective than hiring hundreds of QM managers to review 100% of your customer conversations.)

Most importantly, automated quality management helps you identify and prioritize the coaching opportunities that will have the biggest impact on customer satisfaction in your service and sales interactions. And a better customer experience is a win for everyone.

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