How AI is Reducing Burden on Call Center Quality Assurance (QA) Teams

Call center quality assurance (QA) teams are constantly overburdened with administrative, repetitive tasks that keep them from what’s important: ensuring that your product or service meets the required standards so customers and prospects receive an excellent experience.  

Luckily, call center QA teams can leverage artificial intelligence (AI) to boost efficiency, improve accuracy, and enhance efficiency to focus on higher-value activities.   

Enhanced coverage  

Humans can only analyze and assess so much data on any given day. By leveraging AI-powered technology to assist with your quality assurance process, you can analyze massive volumes of call center data quickly and efficiently. This allows your human QA team members to take a closer look at any gaps identified by your AI tool that may need a deeper analysis.   

For enterprises, you get a much broader view of your entire customer base when you leverage AI technology to help review calls. On average, companies only review 2% of their agent’s calls because manual listening is time-consuming, making it nearly impossible to analyze every interaction (Forrester).   

When you only review 2% of calls, you are potentially missing out on a wealth of untapped data, insights, and opportunities hidden beneath the surface. Analyzing this data can uncover compliance violations, customer experience gaps, and more, often faster than traditional survey methods. With AI powered conversation compliance, you can evaluate 100% of calls, giving you a complete, holistic view of the customer base so you can prioritize improvements, track progress, and address issues causing complaints more effectively.  

Reduced time spent on manual processing   

The average QA professional in a call center spends 25-30% of their day manually reviewing calls (Forrester). An AI-powered conversation intelligence tool can review calls for you and automatically score them so QA teams can focus on higher-value activities like training, coaching, and providing a more positive customer experience.    

Not only do QA professionals spend a significant amount of time manually reviewing calls, but they also spend time analyzing those calls for continuous improvement. AI can analyze call results and identify potential areas of concern. This reduces the manual effort required for data sifting and helps QA professionals pinpoint issues faster.  

Improved accuracy  

Leveraging AI within your QA teams also leads to improved accuracy. Many of the responsibilities that fall within QA parameters involve reviewing and assessing agents’ performances. With AI, that process becomes automated and more efficient.   

Take call scoring, for example. After a customer interaction, each call gets a score based on key performance indicators (KPIs) like script adherence, sentiment analysis, regulatory compliance, call outcomes, and more. These factors can be completely customizable to the industry or use case needed to ensure consistency across every interaction.  

Traditional call scoring often relies on human reviewers who may have unconscious bias or make mistakes. AI removes human bias and scores phone calls on pre-defined and pre-determined criteria, ensuring consistency across the board.  

Increased call center efficiency   

AI can boost your QA team’s efficiency in many ways: automating repetitive tasks, faster test execution and analysis, predictive maintenance, and more. By leveraging AI, repetitive tasks become automated, freeing up quality assurance teams’ time for more strategic initiatives.   

Because of AI’s capabilities to interpret mass amounts of data quickly and efficiently, testing and analysis can be done faster than ever. Instead of taking days to evaluate data and run tests, these processes become automated, leading to quicker results and faster resolutions to any problem that may arise.   

Predictive maintenance also leads to increased efficiency. AI doesn’t just react to problems; it can predict them. For instance, if an agent’s performance is declining or a particular service issue rises quickly, AI will easily and quickly be able to flag data before the declining performance becomes worse. By analyzing past data and usage patterns, AI can identify areas prone to issues, allowing your QA teams to address them proactively before they snowball into bigger problems.  

Are you ready to implement an artificial intelligence tool to help unburden your call center’s QA teams?  

By leveraging artificial intelligence to help unburden your quality assurance teams, you can switch from a reactive to a proactive approach to enhancing the customer experience. AI can help QA teams improve accuracy, increase efficiency, and reduce time spent on manual processing so they are free to focus on higher-value tasks that require human expertise and judgment.   

If you think an AI-powered conversation intelligence tool can help supplement your QA team, contact us today and check out our new guide, “How AI and Technology is Transforming Conversational Compliance.”