Achievement Awards Group specializes in employee recognition strategies to boost morale and enhance workplace productivity through rewards and consulting services.

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Today, we’re diving into something that’s revolutionizing contact centre operations: the powerful combination of quality assurance and artificial intelligence. Claire, this topic is packed with potential, isn’t it?

It really is, Jonathan. When we think about contact centres, most of us picture them as the backbone of customer service—fielding tens of thousands of calls every month. These interactions aren’t just about solving problems; they shape how customers feel about a brand. That’s why quality assurance, or QA, is so critical. But here’s the thing: traditional QA has its limits. And that’s where AI steps in.

Right. It’s like this: Imagine a football team that’s only evaluated on one or two matches a season. You wouldn’t get the full picture of their performance, would you? That’s the challenge with traditional QA in contact centres. In this episode, we’re going to explore how AI takes us from sampling a fraction of interactions to analyzing every single call. The result? Game-changing insights that empower teams and improve customer experiences.

Let’s set the stage by talking about how traditional QA works. Picture this: A quality assurer listens to a handful of calls—maybe 250 in a month. In a contact centre receiving 25,000 calls, that’s just 1%. And those calls? They’re randomly selected, so you’re hoping the sample reflects the bigger picture.

And to be clear, this isn’t about the quality assurers themselves. They’re doing crucial work. But they’re limited by time and human capacity. Richard Cramer, Loyalty Director at Achievement Awards Group, put it best: “We’re always looking for ways to QA the QA.” Incremental improvements are great, but when something comes along that can multiply your impact tenfold—like AI—you have to take notice.

So, what happens when we introduce AI into this process? Let’s start with the basics. AI can transcribe all 25,000 calls in a fraction of the time it would take a human. Suddenly, you’re not just sampling 1% of interactions—you’re analyzing 100%.

And it’s not just about transcribing calls. AI can detect patterns and insights that might slip through the cracks with manual QA. For example, imagine a customer mentions a competitor’s name during a call. That’s often a subtle but significant sign of dissatisfaction. AI can flag it immediately.

AI doesn’t just stop there. It can pick up on emotional cues—like anger or frustration—by analyzing voice tone, speed, or volume. And it works both ways. For instance, if a contact centre agent is hesitant or unsure, AI might detect a slower speech rate or a lower vocal tone. This real-time feedback allows managers to step in and support their teams when it matters most.

Another thing that makes AI so powerful is that it doesn't just catch red flags; it can identify green lights, too. What are agents doing well? What’s working in customer interactions? AI ensures you’re not missing moments of excellence that deserve recognition.

Let’s zoom out to the macro level. AI isn’t just transforming individual calls—it can help us revolutionize the way we understand the bigger picture. Take aggregated data from all 25,000 calls. AI can spot patterns that would be nearly impossible for humans to identify.

For example, let’s say a large number of customers are calling about difficulties resetting their passwords. That insight could highlight a need to improve the user interface. Or maybe there's a spike in queries about a particular product. That could signal an opportunity to partner with another brand and meet customer demand.

And here’s the beauty of AI: It doesn’t forget. While humans need training and retraining, and often start fresh in new roles, AI builds a knowledge base over time. It can detect shifts in behavior, like changes in call volumes or the times of day people are reaching out. These insights give you the ability to adapt proactively.

Now, one concern people often raise about AI is whether it will replace human jobs. But in this context, AI doesn’t take jobs—it enhances them. Think about the role of a quality assurer. Right now, they spend hours listening to and transcribing calls. With AI handling those repetitive tasks, they can focus entirely on improving agent performance and driving meaningful change.

Exactly. And it’s not just the listening and transcribing. AI can even automate administrative tasks, like drafting follow-up emails. Johan Hechter, Business Process Consultant at Achievement Awards Group, highlighted this perfectly. Instead of spending hours writing emails, AI can draft them instantly, ensuring they’re accurate and compliant with HR and legal policies.

And it’s not just about saving time. When AI automates these tasks, it frees up quality assurers to do what they do best: supporting agents, enhancing training, and ensuring customers have the best experience possible. It’s a shift from menial to meaningful work.

Let’s take a moment to think about the broader implications. By leveraging AI in QA, companies aren’t just improving efficiency—they’re elevating the entire customer experience. AI provides insights that help businesses adapt, innovate, and stay ahead of the curve.

And the impact goes beyond the contact centre. Imagine using AI-driven insights to inform other areas of your business—marketing, product development, even partnerships. It’s about creating a culture of continuous improvement, where data drives smarter decisions across the board.

That’s the big takeaway here. AI isn’t just a tool for better QA—it’s a catalyst for transformation. It empowers teams to focus on what matters most, supports continuous learning, and ultimately helps companies build stronger, more meaningful relationships with their customers.

So, what’s the next step? If you’re in a leadership role, it’s time to ask: How can we use AI to enhance our operations? How can we shift from reactive to proactive, from good to truly great?

AI in quality assurance isn’t just a trend—it’s the future. Start integrating these tools and see how they can transform your contact centre, your team, and your customer relationships.

Today, we’re diving into something that’s revolutionizing contact centre operations: the powerful combination of quality assurance and artificial intelligence. Claire, this topic is packed with potential, isn’t it?

It really is, Jonathan. When we think about contact centres, most of us picture them as the backbone of customer service—fielding tens of thousands of calls every month. These interactions aren’t just about solving problems; they shape how customers feel about a brand. That’s why quality assurance, or QA, is so critical. But here’s the thing: traditional QA has its limits. And that’s where AI steps in.

Right. It’s like this: Imagine a football team that’s only evaluated on one or two matches a season. You wouldn’t get the full picture of their performance, would you? That’s the challenge with traditional QA in contact centres. Today, we’re going to explore how AI takes us from sampling a fraction of interactions to analyzing every single call. The result? Game-changing insights that empower teams and improve customer experiences.

Let’s set the stage by talking about how traditional QA works. Picture this: A quality assurer listens to a handful of calls—maybe 250 in a month. In a contact centre receiving 25,000 calls, that’s just 1%. And those calls? They’re randomly selected, so you’re hoping the sample reflects the bigger picture.

And to be clear, this isn’t about the quality assurers themselves. They’re doing crucial work. But they’re limited by time and human capacity. Richard Cramer, Loyalty Director at Achievement Awards Group, put it best: “We’re always looking for ways to QA the QA.” Incremental improvements are great, but when something comes along that can multiply your impact tenfold—like AI—you have to take notice.

So, what happens when we introduce AI into this process? Let’s start with the basics. AI can transcribe all 25,000 calls in a fraction of the time it would take a human. Suddenly, you’re not just sampling 1% of interactions—you’re analyzing 100%.

And it’s not just about transcribing calls. AI can detect patterns and insights that might slip through the cracks with manual QA. For example, imagine a customer mentions a competitor’s name during a call. That’s often a subtle but significant sign of dissatisfaction. AI can flag it immediately.

AI doesn’t just stop there. It can pick up on emotional cues—like anger or frustration—by analyzing voice tone, speed, or volume. And it works both ways. For instance, if an agent sounds hesitant or unsure, AI might detect a slower speech rate or a lower vocal tone. This real-time feedback allows managers to step in and support their teams when it matters most.

That’s what makes AI so powerful. It’s not just catching red flags; it’s identifying green lights, too. What are agents doing well? What’s working in customer interactions? AI ensures you’re not missing moments of excellence that deserve recognition.

Let’s zoom out to the macro level for a moment. AI isn’t just transforming individual calls—it’s revolutionizing how we understand the bigger picture. Take aggregated data from all 25,000 calls. AI can spot patterns that would be nearly impossible for humans to identify.

For example, let’s say a large number of customers are calling about difficulties resetting their passwords. That insight could highlight a need to improve the user interface. Or maybe you notice a spike in calls about a particular product. That could signal an opportunity to partner with another brand and meet customer demand.

And here’s the beauty of AI: It doesn’t forget. While humans need training, retraining, and often start fresh in new roles, AI builds a knowledge base over time. It can detect shifts in behavior, like changes in call volumes or the times of day people are reaching out. These insights give you the ability to adapt proactively.

Now, one concern people often raise about AI is whether it will replace human jobs. But in this context, AI doesn’t take jobs—it enhances them. Think about the role of a quality assurer. Right now, they spend hours listening to and transcribing calls. With AI handling those repetitive tasks, they can focus entirely on improving agent performance and driving meaningful change.

Exactly. And it’s not just the listening and transcribing. AI can even automate administrative tasks, like drafting follow-up emails. Johan Hechter, Business Process Consultant at Achievement Awards Group, highlighted this perfectly. Instead of spending hours writing emails, AI can draft them instantly, ensuring they’re accurate and compliant with HR and legal policies.

And it’s not just about saving time. When AI automates these tasks, it frees up quality assurers to do what they do best: supporting agents, enhancing training, and ensuring customers have the best experience possible. It’s a shift from menial to meaningful work.

Let’s take a moment to think about the broader implications. By leveraging AI in QA, companies aren’t just improving efficiency—they’re elevating the entire customer experience. AI provides insights that help businesses adapt, innovate, and stay ahead of the curve.

And the impact goes beyond the contact centre. Imagine using AI-driven insights to inform other areas of your business—marketing, product development, even partnerships. It’s about creating a culture of continuous improvement, where data drives smarter decisions across the board.

That’s the big takeaway here. AI isn’t just a tool for better QA—it’s a catalyst for transformation. It empowers teams to focus on what matters most, supports continuous learning, and ultimately helps companies build stronger, more meaningful relationships with their customers.

So, what’s the next step? If you’re in a leadership role, it’s time to ask: How can we use AI to enhance our operations? How can we shift from reactive to proactive, from good to truly great?

We’d love for you to explore this opportunity further. AI in quality assurance isn’t just a trend—it’s the future. Start integrating these tools and see how they can transform your contact centre, your team, and your customer relationships.

A contact centre game changer: QA + AI = “kwaai”

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