Do you see QA as a necessary evil? Or a force for good? For too long it’s been perceived as the former, a must-have for ensuring compliance and monitoring service quality, but more of a sunk cost than a real contributor to call center ROI.
Thankfully, with the evolution of the call center QA function, alongside improvements in software and the advent of AI-powered quality assurance, this perception has changed for the better.
Your quality assurance efforts go far beyond just monitoring and compliance. If you do it right, QA can serve as a tool for revenue growth, profitability, and cost-efficiency. By shifting the image of call center QA in your organization, you can make a huge difference to both customer experience and the bottom line
In this post, we’ll explore how you can enhance call center ROI with a strategic approach (and AI tools), leading to lower operational costs, higher customer satisfaction (CSAT), happier agents, and more.
Handling customer issues on the first interaction eliminates repeat contacts, lowering operational costs and improving customer satisfaction. QA pinpoints common failure points and ensures agents have the right tools to drive up FCR rates.
Spotting issues and upset customers before escalation allows you to address concerns proactively, reducing churn and reinforcing brand loyalty. QA tools can analyze sentiment and flag negative interactions before they spiral out of control, so you can take immediate action and prevent a negative customer experience.
QA-driven insights reveal which agents are (or aren’t) successfully upselling or cross-selling, and how they’re doing it. Then, you can use your QA to recreate these strategies and develop new training opportunities to improve other agents and drive up revenue per call.
By analyzing call patterns and agent behavior, QA helps you streamline your average handle time (AHT) without sacrificing service quality. Optimized workflows and targeted coaching lead to faster, more effective resolutions, and lower labor costs.
QA ensures your agents are adhering to industry regulations and internal policies. Automated quality monitoring flags potential violations in real-time, helping you avoid costly fines (and damage to your brand or reputation).
Not all agents are perfect, and issues like billing mistakes or misinformation about policies can cause lost revenue and upset customers. QA helps spot these inconsistencies before they get out of control, reducing costly errors and improving accuracy.
QA data identifies individual and team-wide skill gaps, allowing for focused coaching. This helps make sure that your training investments deliver measurable improvements (so you’re not wasting money on inefficient training sessions).
Clear feedback, recognition, and career development opportunities keep your agents engaged and motivated. Through structured insights, QA offers a system for measuring and showcasing improvements, decreasing churn and saving resources on hiring new talent.
Meeting service level agreements (SLAs) requires you to be precise with your metrics and what you deliver. QA monitors key metrics like response times and resolution rates, ensuring your team consistently meets (or exceeds) expectations.
Your QA is more than just a monitoring tool for compliance and call quality. When it’s used strategically (and with the right mindset), QA drives revenue, boosts efficiency, and strengthens customer relationships—all impacting your bottom line.
Try to reframe QA as a positive contributor to call center ROI by:
"Most quality teams are already supporting the business by driving growth, reducing churn, and delivering valuable insights—it’s just not always understood or perceived as valuable as it should be." - Nerys Corfield (Contact Center Consultant, Injection Consulting)
Traditional QA relies on manual call reviews and random sampling, leaving most customer interactions unchecked. This limited approach makes it hard to catch performance issues, compliance risks, and revenue opportunities—especially at scale. AI-powered QA changes all of this.
AI-powered QA can help drive a healthier call center ROI by:
Evaluating 100% of conversations
Delivering real-time insights
Automating repetitive processes
And more
With AI, you take the guesswork of manual QA. Instead of reviewing only 10 calls per agent (per month), AI scans every conversation, identifying patterns in customer sentiment, agent performance, and compliance adherence. This complete visibility ensures you catch potential problems early, reducing revenue loss from unresolved issues or dissatisfied customers.
"AI can analyze 100% of interactions, while human evaluators are limited to small samples—it’s a game-changer for coverage and accuracy." - Derek Corcoran (Founder & CEO, Scorebuddy)
AI-powered QA also lowers operational costs by automating quality monitoring and reporting. Instead of spending hours manually scoring interactions, your team can focus on more impactful actions. AI-driven insights help you streamline workflows, optimize training programs, and boost agent productivity, while reducing costs and maintaining service quality.
Seeing measurable improvements to CSAT and customer lifetime value (CLV) is easier when you have real-time data on customer pain points. AI can detect dissatisfaction and trends before they escalate, encouraging proactive customer service among your agents.
AI systems process vast amounts of customer interactions, raising questions about data protection. By keeping humans a part of the process, you can mitigate some of these concerns. AI can flag critical issues, while human reviewers verify sensitive interactions and ensure compliance with security policies.
With the rapid adoption of AI in the last few years, it’s easy to see why agents and evaluators could be resistant. Show them that AI is a tool to enhance performance (not replace them). By automating repetitive tasks, AI allows employees to focus on higher-value work, like personalized coaching, handling complex cases, and improving the customer experience.
With many popular AI tools operating with a “black box” approach (i.e. not showing us how an algorithm decides on an answer), it’s easy to hesitate around AI adoption. Running pilot programs alongside trusted, transparent AI tools can help show its value and impact on call center ROI.
By testing AI on a smaller scale and measuring its impact on QA accuracy, agent performance, and cost savings, you can show leadership and employees the real benefits before full implementation.
Many see QA as just another expense, but it can actually make a significant difference in generating call center ROI. To make a strong business case for your QA program, you need to show exactly how it impacts revenue, cost-efficiency, and compliance risk. This means connecting QA improvements to real financial outcomes that leadership cares about.
"Think about what would happen if you didn’t have a QA function. What would the cost be? What risks would arise?" - Nerys Corfield (Contact Center Consultant, Injection Consulting)
Start by demonstrating how QA contributes to revenue growth. By using QA data to show how better call quality leads to higher customer retention and sales, you make it clear that QA drives revenue, not just there to monitor agents.
Next, focus on cost savings. A well-executed QA program identifies inefficiencies, like excessive AHT or customer callbacks, for example. By addressing these issues—through targeted training or optimized processes and workflows—you lower labor costs and improve overall efficiency.
Use the data your QA software collects to highlight how reducing unnecessary call volume or improving agent performance leads to significant savings.
Finally, emphasize how QA can reduce financial risks. Compliance violations, billing mistakes, and mishandled disputes can lead to hefty fines, lost revenue, and potential legal troubles. A strong QA process ensures that agents follow regulations and company policies, helping to catch potential issues before they become costly problems.
The right approach to QA turns call centers from cost centers into revenue generators. But to do it, you need to reframe how you view (and use) QA in your business. By focusing on how AI can improve call center ROI through tighter compliance, lower operational costs, and better workflows—and regularly measuring its contributions—you can see the impact for yourself.
Get real-world QA + call center ROI strategies from an expert panel—watch our free webinar now.
