While the concept of automated quality assurance in contact centres isn’t a new phenomenon, the advent of artificial intelligence is transforming the function from a compliance exercise to an engine for improving operational efficiency and enhancing customer experiences. Failing to transition to these innovative technologies will leave businesses without an accurate understanding of their customers and facing the risk of losing out to more digitally intuitive competitors.
For many years, quality assurance (QA) was defined by highly manual and rigid processes; legacy contact centres usually ran QA by having someone physically sit and listen to a very small sample – between 5 and 10% – of customer conversations. Historically, this meant an analyst listening to calls, but because they are also human, their assessments can be influenced and tempered by their own environment and mood, which can lead to inconsistencies in the evaluation process.
QA was primarily a retrospective activity, focused heavily on voice interactions, which had multiple pitfalls for businesses:
- Ineffective sampling: Small samples simply cannot reveal where the real areas for improvement lie within a business.
- Point-in-time limitations: The sampling component acts merely as a point-in-time measurement rather than offering continuous, ongoing measurement.
- Flawed assumptions: If your sampling methodology is flawed, you might review the wrong set of calls entirely, leading you to incorrect assumptions about your operations.
- Static tools: Traditional QA tools are notoriously static; if you configured a specific question, you only received the answer to that question, lacking any actionable recommendations on how to improve business processes based on the measurement process.
What is changing in the modern contact centre?
The most critical evolution is the automation of the Quality Assurance component, which has lifted the business view to provide a comprehensive understanding of compliance and improvement areas across the board.
Furthermore, while Quality Assurance historically focused on voice, we have reached an inflection point where you cannot service customers with voice alone. The ability to integrate and assess all other text-based communication channels has become one of the most important aspects of an organisation’s digital journey. Newer tools also capture all omnichannel customer conversations, providing crucial visibility into customer intent and highlighting precisely where processes need fixing.
AI-enabled Quality Assurance plays a pivotal role in improving First Call Resolution (FCR). FCR fundamentally begins with the information an agent has access to, which can be dynamically enhanced by AI tools like Agent Assist. Ultimately, an agent can only perform as well as the knowledge they possess or the guidance they receive. By assessing everything across all channels, AI-enabled QA gives a complete picture of where agents are struggling and where process improvements are heavily required. You cannot fix what you do not know, and a small sample will never highlight the areas where agents are not performing well.
Enabled by AI, modern tools are entirely changing what is possible by dynamically leveraging customer sentiment and intent in order to optimise the service being delivered to the customer. This includes:
- Intelligent routing: Newer omnichannel systems can detect if a customer is expressing dissatisfaction and automatically route that information toward someone better suited to deal with the situation.
- Agent wellbeing: Using sentiment and intent helps direct customers to agents in a manner that balances the emotional toll placed upon the human staff.
- Continuous measurement: While many organisations rely on static NPS and CSAT scores, AI tools provide continuous sentiment tracking, offering a far better way to measure the customer experience and the views of the customer toward your business.
- Optimised profiling: Modern systems enable the creation of agent profiles, ensuring customers are matched with agents who have the highest probability of resolving their query based on their sentiment, intent, or even specific language requirements.
By integrating these capabilities, organisations are taking Quality Assurance far beyond an exercise for compliance. Today, the data analysis of what is happening in the business is much more crucial than a confirmation of who is asking all the questions in the script. Quality Assurance must never be just a tick-box exercise but should actively enhance business processes and ultimately customer experience.
The rise of digital agents and a new era of Quality Assurance
The rise of digital agents introduces a bold new frontier for contact centres. Configured largely using Large Language Models (LLMs), digital agents act as an entry point into the business that can either make or break the customer experience. However, they also require Quality Assurance, and this looks vastly different compared to how human agents are monitored:
- AI performance: Ensuring digital agents are performing correctly and measuring their error rates just as we look to measure human agents.
- Specific metrics: For digital agents, QA involves assessing whether the AI understood the question, provided the correct answer, captured the intent and sentiment, and derived proper context from the ongoing conversation.
- Monitoring hallucinations: QA tools that manage the content of digital agents must specifically look at word error rates and hallucination rates to ensure the right information is delivered at the right time.
- FCR: Digital agents must also be measured on FCR to ensure they reach the right answers without going into circular loops.
You cannot improve your digital agent if you do not have data, making robust Quality Assurance completely essential.
Evolution of human roles in the contact centre
Despite the rise in the use of technology and automation, AI-enabled Quality Assurance plays an equally vital role in the development of people in the contact centre. The benefits are two-fold for the business: improving processes and procedures, and uplifting the human component.
With the right tools, information, and AI-driven insights and recommendations, the role of Quality Assurance managers evolves into one that is focused deeply on the holistic customer experience. QA managers must now use real-time data to improve processes, identify how to make both digital and human agents better, and put together highly relevant skills development roadmaps for their human staff.
For the agents, automating this component ensures 100% QA on all agents and conversations in a neutral manner, helping to identify exactly where agents need support to grow. When you combine a QA tool with a gamification component, you create a powerful platform to upskill agents, ensure they adhere to compliance, retain good-quality staff, and put them on a definitive roadmap for development.
The risks of automating everything
However, businesses must carefully understand the risks of over-automation. You simply cannot automate everything within the contact centre environment, with a primary reason being that AI is not infallible and can (and does) make mistakes, meaning that human oversight is still required. A human-in-the-loop ensures quality, verifies that processes are being adhered to, and is available to take over hand-offs when required for complex customer engagements. People’s roles will undoubtedly change, but employees are ultimately enhanced and empowered by the tools that are made available.
On the other hand, businesses that refuse to explore the possibilities of the future face the very real risk of being left behind by their competitors. Consider the well-known example of Blockbuster and Netflix: people never stopped wanting to watch movies and series; they simply wanted to watch them online and at their own convenience instead of having to rent a physical disc.
Similarly, customers still want their queries resolved, but they demand the efficiency, empathy, and seamless omnichannel experience that only a modern, AI-enhanced contact centre can provide. Enabling your teams with the right AI Quality Assurance tools gives you better insight into the organisation and its conversations so you can continuously look at ways of enhancing the customer experience.
Turn your communication data into actionable insights. With Telviva’s analytics and reporting solutions, your organisation gains clarity, efficiency, and measurable growth. Discover how Telviva Analytics can transform your business; contact us today.