The value of AI in quality management


For decades now, contact centre quality assurance has been a crucial part of running a successful business and maintaining a good brand image. Effective companies thrive through the experiences that they enable. It’s how these organisations differentiate themselves from the competition and create loyalty among customers.

However, as the contact centre continues to evolve, it’s becoming increasingly difficult to track the quality of every experience at once. Distributed teams working remotely aren’t as easy to watch as in-office employees. There’s also the presence of new channels for customer support to consider, from video to instant chat. A more intelligent system is necessary to ensure ongoing QA success.

AI could be the key to fundamentally transforming the interactions between brands and their customers, while giving businesses a more effective view of the customer journey.

Bringing AI into Quality Assurance

Until recently, quality assurance practices have suffered a range of inefficiencies. Manual processes mean that employees have to spend time on repetitive tasks and data entry rather than serving clients. Limited scope meant team leaders could only get a small view of the customer journey, rather than seeing insights from ever interaction.

Artificial Intelligence can eliminate common problems and provide end-to-end visibility. With artificial intelligence infused services, businesses can track 100% of customer interactions through every channel. This allows for a more complete single point of truth for business insights.

QA tools with AI enhancements can collect historical data from every aspect of your organisation and use huge amounts of information to deliver actionable insights for business leaders. For instance, you may discover that you get better customer satisfaction scores on messaging apps than over voice calls, so you can increase your number of messaging agents.

The right intelligent systems can also send instant alerts and notifications to team members when they see a problem with something like call quality, or bandwidth. This helps teams to resolve issues that might harm brand reputation faster.

Intelligent CX Monitoring in a New World

Even before the rise of the pandemic, companies were beginning to realise that they couldn’t handle the sheer volume of data delivered by customer interactions manually. Artificial intelligence opens the door to more accurate, automated, and efficient ways to gather insights on quality assurance. You can set up a system that analyses and scores every voice call and messaging interaction automatically, with minimal manual input from your employees.

This means that your teams have more time to focus on delivering the best customer experiences, and your business leaders have the data they need to make important decisions about quality management. Some tools can even make historical changes on how to improve call quality based on historical solutions to previous cases.

Eventually, an AI-infused strategy for quality scoring doesn’t just lead to better evaluations, it also means that you can make more informed decisions about how to serve customers based. Whether you’re using surface-level analytics, or historical reports, access to more advanced, aligned, and accurate data leads to better business outcomes.

Source: CX Today

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