Top 10 Call Center Quality Assurance Best Practices | Elevēo

Contact centers are handling more customer interactions — and more complex interactions — than they ever have, and that trend promises to continue. Given that reality, adopting call center QA best practices has never been more important. They improve agent aptitude, provide more sophisticated feedback, fuel better agent training and coaching sessions, and establish standards, practices, and processes that support success in call center operations.

What is call center quality assurance (QA)?

‘Continuous improvement’ has been part of the business lexicon for decades. Methodologies and best practices have emerged in its pursuit, providing frameworks for the development of quality assurance processes and technologies that improve call center processes, decrease waste, improve call center agentperformance, and foster customer satisfaction. This ongoing focus on contact center QA management has delivered undeniable value across a range of industries.

Why are call center quality assurance best practices important?

Effective call center quality management is mainly about controlling hundreds or thousands of inbound or outgoing interactions—calls, emails, and chats. The degree of control call center supervisors have is a function of how many interactions they can review and analyze. It’s about correlating key performance indicators (like average handle time or customer satisfaction score) to call quality outcomes, then analyzing those results for root causes. It’s also about drilling down into customer/agent interactions to identify important moments in interaction and understand how they drive customer sentiment.

How to improve quality assurance in a call center?

Effective quality assurance process in call center environments creates a virtuous cycle of interaction, analysis, and feedback. This improves customer satisfaction and net promoter score, enhances process efficiency, and ensures compliance with actionable insights into every customer interaction, including phone, email, and chat.

Generative AI adds a new dimension to quality assurance

An AI-fueled Quality Management tool with Generative AI and Conversation Analytics capabilities enables supervisors to evaluate 100% of contact center calls for compliance, customer satisfaction and agent training. AI also drives Conversation Analytics. That tool reaches deep into the QM process, providing contextual visibility into every conversation and yielding insights that managers can use to reduce customer churn, strengthen compliance, identify emerging issues and evaluate and train agents.

Eleveo’s AI-fueled quality assurance tools include:

• Automated Quality Management with Generative AI and Conversation Analytics enables supervisors to evaluate 100% of contact center calls for compliance, customer satisfaction and agent training.

• Conversation Analytics reaches deep into the Quality Management process. The visibility it provides fuels analysis, which yields insights. Managers can use those insights to evaluate and train agents. They can identify compliance challenges, sources of customer dissatisfaction, agent performance issues and process inefficiencies

• Continuous Speech Recognition
  • for highly accurate speech-to-text capabilities and transcriptions
  • acoustic parameters identification

• Emotion Detection automatically reads customers’ emotions by examining variations in pitch or tone, interruptions, periods of silence and more.

• Auto Summary/Highlights - AI-fueled call summary and highlights tool automatically generates a short informational summary of every interaction, highlights notable moments within the call and shows any next steps that need to be performed by the agent or the customer.

• Topic Detection - AI-fueled topic detection analyzes each call for topics predefined by the contact center manager. Managers can then view the call details to see any related topics, or search by topic.

• Flagging – AI-fueled call flagging alerts managers to any interactions that may indicate a negative customer experience (e.g. any call requiring escalations or indicative of a customer churn risk). Supervisors can view the call details or search by the topic or flag.

• Sentiment Analysis – AI fueled Sentiment Analysis examines issues, like the number of interruptions, periods of silence, volume increases and over-talking to identify customer and agent emotions.

10 Call center quality assurance best practices

1. Automate your QA processes. Only 1 – 3% of an agent’s contacts can be scored manually. That sample rate could increase to 100% with an automated QM solution with speech analysiscapabilities. Automation gives call centers a solid, data-driven, systematic basis for identifying and addressing problems. Consider shifting to predictive or automated QA scoring, using conversation analytics to score 100% of all interactions and provide a holistic, 360˚ view of the agent’s performance. Call center managers will also be able to repurpose their QA specialists for more value-added activities.
   
   
2. Leave positive feedback. Evaluations are about agent performance, morale, and retention. Oftentimes, agents view feedback in a negative light, as a punitive process focused on what they’re doing wrong and what they need to improve. While there are legitimate reasons for highlighting areas for improvement, it’s equally important for every agent evaluation to highlight and reinforce positive agent behaviors, emphasizing where they’ve made progress. This approach can help improve call center metrics and service quality.
   
   
3. Expand this ‘positive feedback’ practice to a group level. Rather than sending numerous memos and engaging in individual desk-drops to emphasize what not to do, be sure to communicate positive behaviors and trends to the broader team, so you can shift the narrative to replicating best practices and quality assurance criteria. This will help empower your agents and encourage a sense of ownership.
   
   
4. Create detailed evaluations. Quality analysis that only provide scores aren’t enough. An evaluation with detailed notes on specific customer interactions and links to knowledge base articles is a necessary and valuable coaching tool. Notes also make it easier for the evaluator to identify commonalities in the call center agent’s performance over time. This is an essential aspect of any quality assurance program.
   
   
5. Revisit your evaluation criteria at least once a year. This presumes that your quality assurance efforts over the past year have identified and solved top dissatisfaction drivers and that you can shift your quality efforts to focus on a new set of emerging challenges. This is key to maintaining a high quality of customer service and ensuring operational efficiency.
   
   
6. Assess customer effort on every contact. Are your internal processes and systems set up to make the customer experience as easy and seamless as possible? For instance, are customers required to navigate a cumbersome, laborious process to get a refund or return a product? Speech analytics tools will enable you to identify and remedy high-effort interactions, reduce customer effort score, increase satisfaction, and ensure long-term customer loyalty.
   
   
7. Integrate 3rd party metadata. Often, quality management systems are data silos. Now, with API integration, it’s possible to tie data from your Quality Management and Speech Analytics tools to your CRM. In another example, you can integrate Salesforce case data into call recordings so that the case ID or even a training class code is tied to an individual contact as metadata. Your data’s intelligence value is much greater, and your analytics capabilities increase exponentially through the ability to see context you may not have considered before. This can also help find areas of improvement in your QA process.
   
   
8. Focus on group-level performance. By identifying performance trends common to the whole group instead of individual agents, you can identify and address underlying issues. Perhaps an outdated or poorly organized knowledge base is contributing to recurring issues — address pervasive deficiencies driving some of your contact center’s most common performance problems.
   
   
9. Build a partnership between your quality team and your learning and development team. Nurturing a symbiotic relationship between quality and learning/development creates a virtuous cycle of continuous advancement. Many view the relationship between these two teams as linear, with the quality team’s responsibilities beginning where training ends. While that’s true, it’s also true that as the quality team identifies ongoing issues, they can feed that information back to the learning and development team, which can then build it into their training modules, leading to continuous improvement.
   
   
10. Monitor your agents’ empowerment language as part of your quality assessment. Studies have identified agent effort as one of the biggest drivers of customer satisfaction/dissatisfaction and long-term loyalty.

One of the simplest steps call centers can take to improve customer satisfaction/loyalty and a range of other key performance indicators (contact rate, talk time, etc.) is to look at the type of language your agents are using. Are they using empowering language, like ‘what I can do is,’ or are they using ineffective language like, ‘I can’t do that, or I’ll have to have you talk to somebody else’? Consider training your agents on the language to use in specific scenarios and helping them rephrase their responses.

Ultimately, quality assurance is about driving better customer experiences, and empowerment language is key.