Call Centre Quality Monitoring Guide 2026

Capacity explores what call centre quality monitoring is, how quality monitoring software improves CX and how AI and automation have changed it.

Delivering consistently great customer experiences isn’t easy. Every interaction matters, yet ensuring customers leave satisfied after every conversation with your support team is a challenge.

As your contact centre grows, quality assurance becomes even more critical and complex. When thousands of customers reach out each day, outdated, manual QA methods simply can’t keep up.

That’s where AI-powered call centre quality monitoring changes the game. With the market projected to grow from USD 47.3 billion in 2026 to USD 72.31 billion by 2035, it’s clear this technology is becoming essential.

What is Call Centre Quality Monitoring?

Call centre quality monitoring is the structured process of reviewing and evaluating customer interactions, such as phone calls, chats, or emails, to ensure agents meet defined standards for service quality, accuracy, and professionalism.

It’s essentially how a call centre checks whether agents are doing the job the right way and how they can improve.

You’ve probably heard an automatic message before talking to a customer support agent stating that a call is recorded for quality purposes. Most interactions with customers are recorded to ensure compliance and quality.

Here Are Some Ways Call Centres Evaluate Customer Interactions:

• Manual reviews – supervisors or QA analysts listen to recorded calls or read chats
• Live monitoring – listening in real time
• Speech and text analytics – AI tools scan 100% of interactions for trends, risks, or keywords
• Customer feedback – surveys (CSAT, NPS) tied back to agent performance

Setting KPIs helps evaluate communication effectively. When you know what you want to measure and focus on, you know what to look for during the evaluation.

How Does Call Centre Quality Monitoring Improve KPIs?

Call centre quality monitoring improves KPIs by turning real customer interactions into actionable behaviour change.

As the saying goes, “You can’t improve what you can’t measure!”, which is best applied to call center quality assurance.

When you monitor how your team handles customer inquiries and the experience customers have with your business, you can identify opportunities and gaps. But the list of benefits goes on—let’s take a look.

More Efficient Calls

Call centre quality assurance software identifies behaviours and process gaps that slow calls down, such as unnecessary scripting, poor probing, or incomplete resolutions.

Coaching based on monitoring results focuses on eliminating these issues, leading to lower handle time and fewer repeat contacts without sacrificing quality.

And with the right tools, you can expect to cut your resolution times even further. Lyft, a ridesharing company, offers a good example.

After integrating an AI-powered quality monitoring system, the company successfully reduced the average customer service resolution time by 87% and now resolves thousands of customer requests daily.

Enhanced Agent Performance

Quality monitoring sets clear, consistent expectations for what good performance looks like. Agents improve faster because feedback is specific, objective, and directly tied to customer outcomes.

Let’s take a look at another example, this time focused on productivity increases. Games24x7, a popular gaming company, implemented an AI-powered quality sampling platform to automate quality assurance processes.

Soon after, results followed: the company increased employee productivity by 20%, as teams were able to handle more inquiries in less time.

Personalized Coaching

Quality data highlights individual strengths and weaknesses, allowing team leads and managers to tailor feedback to each agent rather than relying on generic training. This targeted approach accelerates skill development and improves long-term retention of best practices.

Reduced Agent Turnover

Retaining call centre employees can be a challenge, with the industry’s turnover rate sometimes reaching as high as 60%.

When monitoring is transparent and developmental, agents perceive feedback as fair and supportive rather than punitive. Clear expectations and meaningful coaching reduce stress, increase engagement, and lower attrition.

How Does Call Centre Quality Monitoring Improve CX?

Quality monitoring is your first step to improving call centre customer service. When you know what works and what could be better, you can adjust your communication to improve how your customers experience your business. And with the right tools, you can achieve it faster, while cutting costs.

Enhanced Support Quality

Studies show that AI assistance boosts productivity by 15% on average, especially for less experienced workers.

Quality monitoring ensures agents follow best-practice behaviors like active listening, empathy, and accurate resolution. Consistent evaluation and feedback raise the overall standard of service customers receive across every interaction.

Higher Convenience

By identifying friction points such as repeated questions, long holds, or unresolved issues, quality monitoring helps streamline interactions. Customers get faster, smoother resolutions with less effort on their part.

More Personalization

It’s not enough to add a name to your email subject line. Personalization is getting, well… more personalized. But it’s challenging without the right tools.

Research on AI in retail found that 25% of shoppers want AI to personalize their experience. Monitoring highlights how well agents tailor conversations based on customer context, history, and intent. Coaching reinforces personalization behaviors, leading to interactions that feel relevant rather than scripted.

Greater Consistency Across Channels

Call centre quality monitoring software applies shared standards across calls, chat, and email, reducing inconsistencies in the customer experience. Customers receive the same level of service regardless of channel or agent.

Increased Trust and Confidence

We surveyed 1,000 people, and it wasn’t surprising that only 42% feel their issues are truly resolved after contacting a business.

Accurate information, compliant handling, and a professional tone, reinforced through quality monitoring, build support that doesn’t disappoint. Consistently positive experiences increase confidence in the brand and willingness to return.

How Have AI and Automation Changed Quality Monitoring?

Back in the day, companies could evaluate only so many customer interactions. You’d select a few calls or text interactions and have someone manually go through the transcript, checking it against the criteria.

AI and automation have shifted quality monitoring from manual spot-checking to continuous, insight-driven improvement.

The biggest change is:

• Scale
• Speed
• Objectivity

First, AI-powered call center quality monitoring software enables evaluation of 100% of interactions, not just a small sample. Instead of reviewing 1–3% of calls, speech and text analytics automatically scan every conversation to detect:

• Compliance issues
• Sentiment
• Silence
• Interruptions
• Resolution signals

Second, automation turns monitoring from reactive to real-time and predictive. AI can flag risk during or immediately after an interaction—such as escalation likelihood or compliance breaches—allowing faster intervention. Teams no longer wait weeks for QA results to take action.

Third, quality monitoring is now more consistent and objective. Automated scoring applies the same criteria to every interaction, reducing reviewer bias and variability between evaluators. Human QA shifts from scoring mechanics to coaching, judgment, and edge cases.

6 Best Practices For Using AI in Call Centre Quality Monitoring

AI is a game-changer in reducing manual work and helping you scale your business. Let’s discuss practical steps you can take today to begin using AI in call center quality monitoring.

1. Identify Key Opportunities

Start by defining what “quality” actually means for your operation. Every business is different, and so should be your goals.

You might look into increasing first-resolution rates or reducing wait times, and AI can help you identify the areas that need more work.

You can use AI-powered call center quality assurance software to surface high-impact behaviors that most strongly influence CX and performance KPIs, such as:

• Missed resolutions
• Compliance risk
• Low-empathy moments
• Inaccurate or outdated information
• The need for a specialized agent

Let’s take a common situation in call centers: A support team notices CSAT is declining even though agents are meeting handle-time targets.

AI analysis shows that low CSAT correlates strongly with calls where agents fail to summarize the resolution before ending the call.

By redefining “quality” to include clear call closure and configuring AI to flag missing summaries, the team targets coaching on that behavior. CSAT improves without increasing call length.

2. Provide Continuous Training

Many call centers have a misconception that AI is a one-time thing. You upload information once and expect it to magically transform your customer experience.

But AI insights should feed ongoing coaching, not one-time corrections. Use recurring quality trends to update training content, reinforce best practices, and shorten time to proficiency for new agents. Continuous learning keeps performance improving as customer expectations evolve.

A much easier route is choosing AI tools that never stop learning. For example, Capacity, an AI-powered customer and employee support platform, connects and unifies your corporate information across touchpoints, such as:

• Files
• Internal communication
• Third-party integrations
• Slide decks
• And more

Not only does AI learn from accurate and comprehensive data, but it also stays connected to it, learning as your business moves forward. Every new interaction or update makes the brain behind the platform smarter.

3. Deploy Across All Your Channels

The best way to avoid data silos or gaps is to apply AI-powered call center quality management software consistently across:

• Voice
• Chat
• Email
• Messaging

Cross-channel monitoring ensures quality standards remain uniform and allows teams to understand how customer behavior and agent performance differ by channel.

Let’s think about this situation: A contact centre monitors call quality with AI but relies on manual reviews for chat and email.

AI analysis across all channels later reveals that chat interactions have the lowest resolution rates due to delayed responses and incomplete troubleshooting.

By deploying AI consistently across voice, chat, and email, the team standardizes quality expectations and improves resolution rates across digital channels.

4. Reward High-Performing Agents

It’s common to face resistance or difficulties when introducing AI-powered systems. Often, it’s not because people dislike the technology, but because they’re overwhelmed by the extra work of learning new tools and integrating them into existing processes.

Instead, use AI-backed quality data to recognize agents who consistently deliver strong outcomes. Southwest Airlines offers a great example: they incorporated an employee appreciation program to motivate their staff.

The impact was clear, 86% of employees felt genuinely valued and respected, and nearly 8 in 10 reported higher engagement and motivation thanks to the program.

Transparent, objective recognition builds trust in the call center QA process and motivates agents to repeat the behaviors that drive great customer experiences.

5. Collect Customer Feedback

Combine AI quality insights with direct customer feedback like CSAT or CES to validate what customers actually value. This connection helps distinguish between internally “compliant” interactions and experiences customers truly perceive as high quality.

6. Choose The Right Tools

Select AI tools that are explainable, configurable, and easy for agents and managers to understand. The best call center quality management software supports human oversight, integrates with existing systems, and translates insights into clear coaching actions—not just scores.

Your Call Centre Quality Monitoring Done Right

When it comes to customer experience, you need to ensure your tool stack can meet growing customer demand and evolving business needs.

Quality assurance, though it happens in the background, is one of the most important drivers of the service your customers expect and deserve.

This blog post has been re-published by kind permission of Capacity – View the Original Article

For more information about Capacity - visit the Capacity Website

Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Capacity
Reviewed by: Megan Jones