For a call center, service quality is everything. But, in order to achieve a high level of quality, the efficiency of the call center’s main processes must first be tuned and maximized. To improve the quality of how they provide service in the first place, call centers might want to audit and review, test and analyze, and, as a result, revise or completely rehaul certain workflow processes due to their inefficiency or lack of management.
This is where quality assurance comes in—a set of practices that put existing workflow processes under a microscope, trial them out, and suggest improvements from the end-user perspective. Timely QA equips call centers with proven methods of smoothing out the edges (e.g., getting rid of costly routines) and boosting the productivity standard (e.g., through optimized performance).
All that said, the main questions are—what does QA stand for in call centers? Which nuances and specific methods of conducting it are there? And how can a call center boost its QA approaches for high-end workflow optimization results?
Quality Assurance is a set of efforts that helps make sure the service is delivered to an end-user (e.g., a client or a caller) in the highest-quality way possible—quickly, intuitively, and smoothly at every touchpoint.
A team manager, lead, or admin may thus use QA techniques to test the user experience from the end-user perspective, interaction by interaction, and adjust things for better results and higher metrics.
In a call center, QA usually includes systematic monitoring, audit or analysis, and optimization of the quality of interactions with callers. However, QA goes beyond simply seeing whether agents follow scripts or meet performance targets—it is a holistic approach tuned for the long-term improvement of a call center’s workflow on both ends.
The overarching objectives of call center QA include:
Сall monitoring is only one of many methods managers or admins may use to audit the user experience quality and make sure all protocols are in check. In turn, QA is a whole set of methods, techniques, and approaches, that is set up individually for a call center to deliver ongoing results from many angles.
Another important distinction that should be noted and not used interchangeably is between QC and QA, which are essentially different in that:
Example in a call center setting:
The takeaway is simple: with a due focus on QA, call centers can prevent issues rather than merely recognize and address them post-factum.
Now that we have the what is call center quality assurance question more or less figured out, it is even more important to see why this entire approach requires its due attention. Let’s take a look.
QA improves operational efficiency by identifying inefficiencies such as redundant workflows, bottlenecks, or unnecessary escalations. By analyzing performance data, QA processes uncover opportunities to streamline tasks and reduce resource waste.
For instance, if repeated delays in call routing are spotted, a call center may want to revise protocols for shorter caller wait times. Such optimizations enhance the customer experience as well as lower operational costs, enabling call centers to achieve more with fewer resources.
Quality assurance helps contact center agents perform better by providing focused feedback and clear guidance on areas they can improve. Regular check-ins don’t just sharpen their skills—they also boost confidence and keep morale high.
For example, a QA review might show that an agent struggles with handling tricky customer complaints. With targeted coaching, they can build the skills needed to resolve issues more effectively. Continuous feedback creates a supportive environment where agents can grow and feel ready to tackle diverse customer needs.
Quality assurance helps businesses make smarter decisions by turning performance data, customer feedback, and operational trends into clear insights. By analyzing this information, companies can spot patterns, address problem areas, and focus on what needs improvement.
For instance, QA might highlight that customers are often frustrated with delays in product deliveries. This could prompt a review of communication or logistics processes, leading to better outcomes. Using these insights, leaders can fine-tune their strategies while staying in tune with what customers expect and need.
Quality assurance can help keep businesses compliant with strict regulations, especially in industries like healthcare, finance, and telecommunications. Do all agents follow data privacy rules and communication standards, from properly disclosing terms to protecting sensitive customer information?
For instance, QA might catch cases where agents forget to explain mandatory fees, allowing managers to step in and address the issue. By identifying and fixing these gaps early, QA reduces the risk of fines and legal trouble while reinforcing customer trust in the company’s professionalism and integrity.
Quality assurance drives long-term customer satisfaction by helping make sure every interaction is handled with care and consistency. Through call monitoring, feedback integration, and focused agent training, QA pinpoints areas where communication, product knowledge, or tone might fall short, helping teams make meaningful improvements.
For example, if customers find an agent’s explanations too technical or experience delays in resolving their issues, QA can uncover these patterns and shape further actions.
Call center quality assurance is a collaborative effort that can rest on multiple organization positions. Depending on the size and structure of the call center, QA responsibilities may be handled by dedicated teams or integrated into existing roles.
Here’s a breakdown of who typically handles call center QA and their responsibilities:
QA analysts usually rule and direct the whole QA process, offering unbiased evaluations that help improve customer interactions and maintain service quality.
Responsibilities:
Supervisors bridge the gap between frontline agents and management, seeing to that QA meets both operational goals and customer expectations.
Responsibilities:
While managers may not be directly involved in QA evaluations, they rely heavily on the insights provided to refine workflows, improve service quality, and meet organizational targets.
Responsibilities:
Training specialists make sure that insights from QA evaluations are put into the core of actionable improvements in agent skills and behavior.
Responsibilities:
Empowering agents to take part in QA is always a great idea that motivates continuous growth.
Responsibilities:
Technology teams assist in enabling scalable, data-driven QA processes that cut out tons of manual effort and boost accuracy through automation and other tech.
Responsibilities:
For QA to be ultimately effective, these roles must collaborate. For instance, QA analysts might work with training specialists to address skill gaps identified during evaluations. Managers might partner with technology teams to implement advanced AI tools for better insights.
Knowing what to expect from call center QA and how exactly it works is half the deal and a great motivation to move on to actionable steps. Here is the outlook on the usual methods and areas they target.
Call monitoring and scoring are the baseline techniques of call center QA that allow supervisors or QA analysts to assess agent performance against predefined criteria. This method shines the light on the very foundation of contact center performance—everyday caller interactions, helping to make sure they support company standards and meet customer expectations.
Common evaluation criteria include:
QA teams can pick out areas where agents excel or need improvement by scoring calls based on these and other metrics.
QA teams may also observe agents’ screen activities during calls, complementing call monitoring to see whether agents use all tools at their disposal and keep all processes up to the workflow standards. Any spotted process inefficiencies help figure out qualification gaps and set future training directions.
Insights to derive from screen monitoring include:
For instance, monitoring might reveal that agents consistently miss updating customer details after calls, which calls for a refresher on CRM usage.
Customer feedback surveys provide direct insights into how customers feel about their interactions with the call center. The main metrics to drive such surveys should include net promoter score (NPS) and customer satisfaction (CSAT) rate.
Main points that can be gathered with customer feedback surveys:
For example, a low NPS might indicate that users could use faster response times, hinting that a workflow needs adjustments to improve speed.
AI-powered speech analytics tools enable a smart analysis of call recordings. These tools pick out keywords, detect sentiment, and flag potential issues, showing where a call center can improve service.
Speech and call analytics tools running on AI also provide insight that manual reviews cannot achieve in a call center-scale environment.
What speech analytics can do:
For instance, speech analytics might show that more complaints are appearing about using a new product, which will direct the call center team to update FAQs or start sharing more user materials.
Last but not least, a set of pre-defined performance metrics helps understand agent effectiveness and overall service quality through data and statistics.
The most important metrics to keep in check include:
For example, if QA pinpoints a low FCR rate, extra training on troubleshooting techniques or improved access to resources may be necessary. In turn, a high AHT might show the need to speed up the workflow.
The above methods summarize the processes usually employed when conducting contact center quality assurance. However, there are ways to maximize all the above approaches and achieve some extra efficiency, be it via technology, additional efforts, or workflow philosophy. Here are some pro tips for that.
Integrated with a specialized AI model, QA becomes faster, smarter, and more efficient across the line with the help of automation, real-time responsiveness, and point-on robotic accuracy. Smart tools like chatbots, can analyze high volumes of neverending, cut manual workload for human agents, and provide insights and metrics.
Must-have innovative features for call center QA include:
Example:
A financial services call center can use AI to monitor live interactions. If an agent overlooks a compliance disclosure, the system alerts them to include it.
A well-structured QA program rests on clearly defined, measurable quality standards. These standards should guide all further checks and set expectations for both agents and supervisors.
How to establish quality standards:
Example:
Clear quality standards help agents understand what’s expected of them and drive continuous improvement (i.e., referring to a single set of metrics at all times).
Timely training helps agents expand product knowledge, double down on caller empathy, and boost technical skills. equipping agents to confidently handle growing customer needs.
How to implement effective training programs:
Example:
A call center finds out through QA that agents struggle with upselling. This calls for targeted upselling training, commonly resulting in a 20% productivity boost.
Some individual responsibility, where agents get to analyze their own performance, always pushes specialists for more, pointing out specific performance gaps.
Here are a few ideas on how to promote self-evaluation:
Example:
By self-evaluating and proactively working on their weak points, agents build individual confidence and free up the supervisory burden.
Constantly giving, sharing, and exchanging feedback is a great way to keep agents eagerly and responsively growing in their skills.
Some of the best practices for maintaining feedback include:
Example:
A retail call center can implement a monthly feedback program that sets different categories for top-performing agents, boosting morale and motivating underperformers to improve.
QA teams can use tools to intervene during calls and live interactions in order to provide immediate guidance and support to agents.
Real-time monitoring can help:
Example:
A tech support center can use real-time monitoring to guide agents handling complex product issues, with supervisors available to intervene when needed.
One other pro tip that must be mentioned separately: There’s no need to try and do all the QA heavy lifting single-handedly—turning to a technologically enabled outsourcing partner will save a mighty ton of time, expenses, and nerves.
Simply Contact can become that trusty partner in delivering tailored call center quality assurance solutions that help personalize call center interactions, facilitate workflow tasks, and make things much simpler for both agents and callers via consultation and custom software.
Our expertise includes:
Training programs support: Use the analysis of KPIs provided by your support partner to perfect training programs and maximize agent performance.
Summing things up, what is quality assurance in call center if not the necessary regular review and revision of a structure that must stay very dynamic and resilient? Contact center agents, especially commercial operators and sales reps, have some of the most demanding responsibilities while keeping up with the competition. Using every means of assuring the quality and convenience of their work is only a fair business decision.
Discover how Simply Contact’s QA solutions can streamline your workflows, improve customer interactions, and drive lasting success. Get in touch today to see how we can support your goals.
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