Automated Quality Management: More Than Just Scoring automated quality management

Automated Quality Management: More Than Just Scoring

AI has been quietly knocking on contact center doors for years. But in 2023, with the thunderous buzz around ChatGPT and generative AI, the call finally became impossible to ignore.

Today, AI is solidly inside every top-performing contact center—everything from automated quality management to virtual agents. For customer experience (CX) leaders, the question is no longer if AI and automation have a place in our contact centers but, rather, when and how. When does it make the most sense to integrate AI and machine learning into your CX center’s business processes? And how can they help deliver exceptional customer experiences while increasing efficiency, automating tasks, and reducing costs?

According to recent research by DMG Consulting:

Automated Quality Management: More Than Just Scoring automated quality management

For many customer support centers, a good place to start leveraging the power of AI is with quality management processes. Automated quality management systems can be a fast track to experience improvements—for both customers and employees—as well as boost agent productivity and overall operational efficiency.

What Is Automated Quality Management (AQM)?

Automated quality management, or AQM, can optimize the entire quality management process for customer service centers through efficiency and effectiveness improvement, often related to time-consuming and repetitive tasks in the areas of:

  • Customer interaction scoring
  • Quality evaluation
  • Agent scheduling 
  • Coaching and performance evaluation
  • Call transcription
  • Compliance

Unlike manual quality management processes and tasks, which, by necessity, only monitor random samplings of interactions between contact center teams and customers—usually only about 2%—AQM solutions ensure quality analysis and quality control of every customer support agent interaction.

Automation helps give customer support managers comprehensive views of agent performance and more clearly highlights areas that need work. While minimizing human error, these valuable insights elevate results and improve compliance.

Why Is AQM Important For Contact Centers?

AQM systems are important for contact centers because of the numerous and significant benefits they deliver in a customer service setting.

They empower customer service organizations to focus on turning up employee performance by more closely tracking compliance with service standards. The ultimate result is a more consistent experience for customers and happier teams.

With a boost from AI, traditional quality management takes a giant step past basic process improvements to quickly expand and enhance:

  • Team performance
  • Agent engagement
  • Customer experience
  • Long-term customer loyalty
  • Bottom-line financial results
  • Overall business success

Beyond Scoring

AQM has shifted how modern contact centers manage and continuously improve customer experience by going beyond traditional, manual scoring to incorporate advanced features, like sentiment analysis and topic categorization, for a much more sophisticated approach to quality management.

Traditionally, quality management in customer support centers primarily involved time-intensive, manual scoring by supervisors based on predefined criteria. However, this approach has limitations, including clear subjectivity.

It’s also extremely time-consuming. More advanced AQM tools, on the other hand, provide valuable time savings and greater accuracy compared to manual processes.

How Does AQM Work?

AQM is much more than scoring. Here’s how it works to leverage AI:

Sentiment Analysis: Understanding The Emotional Context

One of the key elements of AQM is sentiment analysis. An important part of sentiment analysis is the use of natural language processing and machine learning algorithms to assess the emotional tone of customer interactions. By uncovering emotions ranging from satisfaction to impatience to frustration, contact center leaders gain a deeper understanding of customer experiences—and get actionable insights for improvement.

Sentiment analysis empowers customer service leaders to spot what is triggering positive and negative emotions. They can then use the learnings when training and coaching their teams.

For example, positive sentiment can be celebrated and reinforced. Conversely, when negative sentiments are uncovered, specific behaviors are addressed and corrected quickly, leading to measurable shifts in customer satisfaction. 

Automated sentiment analysis, powered by AI,  is an especially powerful tool for quality management, particularly when used with more traditional customer feedback, such as customer surveys, net promoter score, and online reviews.

Topic Categorization: Uncovering Insights From Conversations

Another critical component of AQM is topic categorization, which involves classifying customer interactions into specific categories, or topics. More than traditional scoring, topic categorization provides an in-depth analysis of the content and context of conversations. For example, advanced machine learning algorithms analyze the language used in interactions to automatically categorize them based on predefined topics.

With topic categorization, contact centers can uncover recurring themes, common issues, and emerging trends in customer inquiries. With a comprehensive understanding of topics discussed, supervisors can implement targeted training programs and personalized coaching, optimizing processes and quickly addressing issues before they escalate.

Root Cause Analysis: Identifying Underlying Issues

Automated quality management systems often incorporate root cause analysis capabilities. This enables customer support centers to dig deeper into the underlying issues affecting service quality and better understand overall customer dissatisfaction and specific complaints. Instead of merely identifying symptoms, AQM systems help identify the root causes of recurring problems.

For example, if sentiment analysis and topic categorization reveal consistently negative customer feelings in a specific category, root cause analysis can help uncover whether it is due to a training deficiency, system error, or process inefficiency. Addressing the root cause allows customer service centers to implement more effective and sustainable solutions, leading to continuous improvement and overall operational excellence.

Real-time Analytics: Immediate Action For Long-term Improvement

Beyond periodic evaluations, AQM provides real-time analytics and empowers customer service supervisors to monitor and quickly respond to issues with team performance. With real-time insights, team leaders can promptly intervene to provide actionable feedback so agents can make necessary adjustments.

This kind of coaching helps build support team members’ confidence. As a result, both employee experience and customer satisfaction improve.

Through real-time analytics, contact centers can create dynamic and responsive quality monitoring environments, ensuring consistent compliance with quality standards. This agility is especially valuable in industries where customer expectations and market dynamics are constantly evolving.

Coaching And Training Integration: Fostering Agent Development

AQM does more than simply identify areas for improvement. Well-developed AQM solutions also facilitate targeted coaching and training programs for long-term impact. Through integration with learning management systems, they help contact center leaders create personalized development plans for agents based on performance data.

For instance, if sentiment analysis indicates that particular agents struggle with handling certain emotional situations, managers can tailor coaching sessions to address these specific challenges and develop stronger skills. A more personalized approach to coaching not only enhances individual agent performance, but it also contributes to a more agile and adaptable contact center workforce, which is good news for businesses, employees, and customers long-term.

Automated Quality Management: More Than Just Scoring automated quality management

The Future Of Quality Management Is Now

The benefits of AQM transcend traditional scoring methodologies. The integration of sentiment analysis, topic categorization, root cause analysis, real-time analytics, and coaching capabilities create a comprehensive and nuanced quality management strategy.

It’s what’s next for every top-performing contact center and can deliver the highest quality of customer interactions and compliance standards. To unlock the full benefits of AI in quality management though, CX organizations must define effective strategies early.

By using these advanced features, leading organizations elevate the overall customer experience, address issues at their core, and foster continuous improvement. As technology continues to develop and advance, embracing the multifaceted capabilities of AQM will be a CX boon and customer service center.

Resources To Help

While the draw to integrate AI into your operations is strong—and the benefits are clear— before you jump in, there are important considerations for your contact center.

Defining your strategy early and understanding potential challenges along the way will help ensure success. With more information, you can make better decisions. These two resources are a smart place to start.

Automated Quality Management: More Than Just Scoring automated quality management


How To Infuse AI Into QM: What You Need to Know

In this webinar, Playvox experts discuss how quality management and AI successfully work together, and they share implementation best practices. 

You’ll learn:

  • How AQM can benefit your contact center
  • Important considerations when incorporating AI into your core quality processes
  • Best practices for implementing AI-driven features

Watch on demand here.

Automated Quality Management: More Than Just Scoring automated quality management


Take Quality Management One Step Further With AI

In the ebook, you’ll learn:

  • How and why quality processes have shifted
  • How automation and AI impact quality efforts
  • Key components of an AQM solution
  • How to introduce AI and automation into your quality management efforts

Download the ebook here.

Playvox AutoQA is a collection of functionality that reveals the full picture of what is driving customer interactions by identifying underlying sentiment. AutoQA uses AI to assist your analysts with scoring to drive a more efficient scoring and feedback process while empowering your team to achieve desired results. It could help you begin leveraging the benefits of AI for a comprehensive, next-level AQM strategy.

Whether you still have questions about the right time to automate your quality management or you’re ready to hear about Playvox solutions, our team is here to talk about your goals and how we can help you achieve them. 

Automated Quality Management: More Than Just Scoring automated quality management
Playvox Team

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