Call center quality assurance (QA) ensures that all organizational touchpoints align with company values and objectives. In a survey conducted by Salesforce, 78% of respondents say they have made purchase decisions based on customer service quality. 

This blog covers contact center quality assurance, benefits, and best practices to ensure standard service delivery. 

What is call center quality assurance?

Quality assurance is a process of evaluating customer interactions, including email, chats, texts, and phone calls to meet pre-defined benchmarks. Contact center quality assurance processes ensure that customer interactions align with business goals and that your agents provide an excellent experience at all levels. 

Manual quality monitoring in a high-volume contact center can be challenging and affect results. Artificial intelligence (AI) solutions have improved QA capabilities to optimize quality assurance in organizations in recent years. Machine learning and intelligent automation can review all interactions for sentiment, detect phrases, and auto-assign tickets based on given parameters. These tools free up time spent combing through multiple conversations. 

Quality assurance moves you up the customer service scale

Quality assurance processes ensure that customer interactions align with business goals. Contact center QA increases the relevance of your coaching sessions, enhancing agent productivity and efficiency. 

Here are some other benefits of adopting quality management into your customer-centric approach:

• Customer engagement and retention. When support agents perform better, customer satisfaction scores increase. QA makes customer satisfaction predictable to an extent, and teams can spur customer engagement since they know what works and what doesn’t. 

• Process improvements. Agents want to do a good job. If there are low QA scores, there may be a gap in your training or knowledge base, or something is wrong with the product offering. QA helps you identify ways to improve both agent and customer experiences.  

• Performance optimization. By looking beyond CSAT and reviewing multiple interactions, teams can discover strategies that drive customer satisfaction, replicate with various teams, and improve employee performance.

Echo AI enables teams to eliminate manual QA processes and leverage AI capabilities to make QA workflows smarter, faster, and more efficient. Managers can automatically identify areas of improvement, such as communication gaps, grammar and spelling errors, sentiment, and much more by adopting Echo AI's quality management system (QMS).

9 quality assurance best practices to improve contact center interactions

For quality assurance to work its magic in your organization, you must set up and implement the right processes. Consider some of these QA best practices to achieve optimal results in your contact center. 

1. Explain the QA program to all agents

   Contact center QA programs require a set of standards and procedures that define and measure the quality of your product and service. QA programs include policies and procedures to determine agent performance, operational efficiency, customer experience, and alignment with business goals. 
   
   Agents can only meet QA standards when they’re aware of metrics that you prioritize. Conduct training programs explaining how your QA software works and empower employees with the right tools. 
   
   

2. Provide ongoing feedback loops with agents

   From a recent survey we conducted on 483 customer-facing employees, 83% of respondents want feedback on their performance. Managers need to switch their focus to monitoring team performance, providing timely, constructive feedback, and motivating agents to reach their highest potential. Integrating QA with performance analytics allows team leaders to provide personalized coaching.
   
   In providing feedback, team leaders need to create a balance between highlighting areas of improvement and commendation. Agents should also have the opportunity to share their thoughts with managers and appeal a QA grade. 
   
   

3. Define and track the right metrics

   Metrics are quantitative measurements that gauge the effectiveness of any approach to a goal. Contact center metrics such as scorecard interactions, customer satisfaction (CSAT) and first-call resolution help teams determine if they are meeting customer and company expectations. Metrics to consider include:

   • NPS scores

   • Abandon rates

   • Hold times

   • First contact resolution (FCR)

   • Average Handle Time (AHT)
     
     

4. Build a sufficient knowledge base

   A knowledge base serves as a central repository of information for your team and includes how-to guides, frequently asked questions, and troubleshooting help, which encourages self-service. 
   
   Research conducted by McKinsey reveals that employees spend 20% of their time searching for information about work processes. Knowledge bases help team members find information quickly, boost productivity, and serve customers better. 
   
   

5. Evaluate team performance 

   According to the World Quality Report, 75% of senior industry figures believe there is a need for new test strategies and the use of AI in testing. Echo AI Health scores give managers an overview or a granular evaluation of individual or team performance. Scorecards also enable teams to ensure quality and a great CX experience. By revisiting KPIs and metrics, managers can adjust workflows and processes for maximum efficiency.  
   
   

6. Look for trends

   As with any industry, discovering ways to improve processes and delight customers with faster service and resolutions keeps organizations ahead of the competition. A quality management program guides company direction by enabling managers to uncover trends in the reasons customers are reaching out to your support team. 
   
   

7. Use Generative AI to track all customer interactions

   Generative AI can be used to track all customer interactions, enabling the extraction of valuable insights such as sentiment analysis, keywords, and customer intent. It can also provide contact center operators with a detailed understanding of customer behavior, the primary causes of product complaints, and delivery issues. One of its most valuable applications lies in generating comprehensive summaries of prominent trends and themes derived from a business's entire historical dataset encompassing calls, texts, chats, customer surveys, and CRM data. This empowers generative AI to identify and validate customer support issues, allowing contact center leaders to allocate resources effectively for resolving the highest priority challenges, all supported by data.

   
   

8. Use omni-channel intelligence to boost quality assurance

   Your QA process is only as effective as the data being used to coach and train on. That’s why being able to analyze customer interactions across all channels including voice, chat, texts and emails is so critical. Opt for solutions that also bring in your CRM data and customer surveys to create a more cohesive snapshot of your entire customer service operation. This approach enables you to coach  agents to improve performance while tapping into the broader scope of your customer experience to give you the insights necessary to improve quality standards across operations, supply chain and more.

   
   

9. Monitor all call center interactions in real time

   Monitoring all call center interactions in real time is crucial for call center leaders to drive better business outcomes because it allows them to ensure quality customer service, identify and address issues promptly, and provide immediate coaching and feedback to agents. This real-time oversight helps maintain customer satisfaction, reduce errors, and improve agent performance, ultimately leading to higher customer retention, increased efficiency, and improved overall business success.

What are the benefits of contact center quality assurance?

Ensure quality management with Echo AI

Echo AI empowers managers to deliver real-time targeted feedback with machine learning and intelligent automation, which improves the quality of agent interactions and ensures customer satisfaction. Get a live Echo AI demo today. 

Frequently asked questions about call center quality assurance

How regularly should you hold quality assurance checks?

The standard for conducting quality assurance checks can vary by industry. Best practice is to provide QA reports as soon as the QA monitor has filled out the scorecard. Waiting for biweekly, monthly, or quarterly reviews means lost time from learning and improving service, and often a front-line employee may not even remember an interaction. As teams hone their skills, streamline workflows, and improve service delivery, QA specialists can reduce reviews' frequency for high-performing agents. 

What is the best way to monitor written customer service?

Look for a solution that provides sentiment analysis, spelling and grammar checks, and has the ability to check for key phrases in emails, text, or chat support. Modern QA programs will allow QA monitors to quickly complete scorecards with suggested scores based on AI, and will provide both the grader and the agent easy side-by-side views of the scorecard and the written interaction. 

What skills does a contact center QA analyst need?

Contact center QA analysts need to ensure that all interactions meet industry standards and align with organizational objectives. QA analysts need to possess qualities such as attention to detail, outstanding written or verbal communication, technical knowledge, and interpersonal skills. 

What’s the difference between call center quality management and quality assurance?

Quality assurance is just one piece of the puzzle within the broader quality management category. 

Quality management in a call center involves the overall process of ensuring that the service provided meets or exceeds predetermined standards. It includes a broader scope of activities aimed at improving the performance and efficiency of the call center as a whole. Quality management may include agent performance, workforce optimization, scheduling, gamification, quality assurance, and more key areas that are aimed at improving overall operational efficiency.

Quality assurance, on the other hand, is a specific component of quality management. It focuses on monitoring and evaluating the performance of individual agents or teams to ensure they adhere to established quality standards and procedures. Quality assurance typically involves activities such as call monitoring, scoring, providing feedback, coaching, and conducting performance evaluations. Its primary objective is to maintain consistency in service delivery and ensure that agents meet the required quality benchmarks.

Quality assurance is a subset of quality management, focusing on the tactical implementation of quality standards within the call center environment.

What are some examples of call center quality assurance metrics to track?

Call center quality assurance metrics are essential for monitoring and improving customer service performance. Here are some examples:

1. First Call Resolution (FCR): Measures the percentage of customer inquiries or issues resolved during the first contact without needing subsequent follow-ups.

2. Average Handle Time (AHT): Tracks the average duration of each customer interaction, including hold time and talk time. It helps assess efficiency and productivity.

3. Customer Satisfaction Score (CSAT): Collects feedback from customers to evaluate their satisfaction levels with the service received. Typically measured through post-interaction surveys or ratings.

4. Net Promoter Score (NPS): Assesses customer loyalty by asking customers how likely they are to recommend the company's products or services to others.

5. Call Monitoring Score: Involves live or recorded monitoring of calls by supervisors to evaluate agent performance based on predefined criteria such as adherence to scripts, professionalism, and problem-solving skills.

6. Quality Assurance (QA) Score: Provides an overall assessment of call quality based on predefined criteria, including adherence to company policies, accuracy of information provided, and tone of communication.

7. Abandonment Rate: Tracks the percentage of calls abandoned by customers before reaching an agent. High abandonment rates may indicate long wait times or insufficient staffing.

8. Service Level: Sets targets for the percentage of calls answered within a specified time frame (e.g., 80% of calls answered within 30 seconds). It ensures timely response to customer inquiries.

9. Agent Adherence: Measures agents' adherence to schedules, breaks, and other operational guidelines to ensure consistent service delivery.

10. Issue Resolution Time: Tracks the time taken to resolve customer issues or inquiries from initiation to closure. It helps identify bottlenecks and improve efficiency.

11. Call Transfer Rate: Measures the frequency of calls transferred from one agent or department to another. Excessive transfers may indicate training gaps or inefficient routing processes.

12. Compliance Metrics: Tracks adherence to regulatory requirements, industry standards, and internal policies during customer interactions.

13. Upsell/Cross-sell Conversion Rate: Measures the success rate of agents in promoting additional products or services to customers during interactions.

14. Customer Effort Score (CES): Assesses the ease with which customers can get their issues resolved. It measures the perceived effort required by customers to interact with the company.

These metrics, when used in combination, provide comprehensive insights into call center performance, agent effectiveness, and customer satisfaction levels. Adjustments and improvements can then be made based on the analysis of these metrics to enhance overall service quality.