Call centers are using more AI and automation tools these days. This creates a challenge – how to properly combine the new AI technologies with the old manual quality assurance processes. Completely replacing manual QA with AI could mean losing important knowledge and skills. But only using the outdated manual methods means missing out on AI’s ability to analyze calls better and faster. The best solution is finding a good balance that uses both AI’s analytical power and human reviewers’ unique expertise.
Blending AI speech analysis with human intelligence providing nuanced feedback is key for consistently great customer service. Uniting the new AI capabilities with manual QA is crucial as call centers bring in more advanced technologies.
The Legacy of Manual Call Center Quality Assurance
For decades, call centers have relied on manual QA processes where a small percentage of recorded calls are randomly sampled and reviewed by a team of auditors. These auditors analyze call handling, adherence to scripts, customer satisfaction, and other key metrics. Their findings are then used to identify training opportunities, process improvements, and top performers.
While this approach has been the industry standard, it suffers from some inherent limitations:
- Sample Size: Typically, only 1-5% of total call volumes are reviewed due to the labor-intensive nature of manual audits. This small sample size means many calls slip through untouched.
- Subjectivity: With humans doing the auditing, there’s always some degree of subjectivity and personal bias in the scoring and feedback.
- Scope Creep: Auditors can only focus on a limited set of criteria and metrics. Many nuances and details inevitably get missed.
The Transformative Power of AI Call Ingestion
Enter AI call ingestion and analysis. By automatically transcribing and analyzing 100% of call recordings using speech recognition and natural language processing, the game changes completely, as you have full visibility into every customer interaction with complete objectivity.
Sophisticated AI models can evaluate conversations in their entirety, analyzing things like emotional sentiment, crosstalk patterns, adherence to compliance requirements, and even pick up on the root causes of customer frustration or confusion. This unprecedented depth of insight simply can’t be replicated through manual random sampling.
Bridging the Gap: A Balanced Approach
The key lies in finding the right balance and seamlessly integrating AI and human intelligence as part of a holistic quality management strategy. By leveraging the scale and objectivity of AI analytics, while retaining the invaluable context and nuance of human expertise, call centers can unlock unparalleled levels of quality and customer satisfaction.
So Where Does That Leave Your Traditional Internal QA Auditing Process?
Achieving this harmonization of AI and human QA is an ongoing journey, requiring a cultural shift within call center operations. Organizations must embrace a mindset of continuous improvement, where data-driven insights and human feedback are seamlessly integrated to drive operational excellence.
Regular calibration sessions between AI models and human auditors can help align expectations, refine scoring criteria, and ensure consistency across the quality management process. Cross-functional collaboration between technology, operations, and training teams is also crucial, enabling the rapid adoption of improvement initiatives informed by both AI and human intelligence.
Furthermore, human auditors can leverage AI analytics to prioritize their efforts, focusing on high-risk or high-value interactions highlighted by the AI models. This targeted approach ensures that human resources are optimally utilized, while still benefiting from the breadth and scale of AI analysis.
Limited sample sizes and subjectivity holding you back with your call center quality management strategy? Well, unlock unparalleled quality and satisfaction with Etech Global Services. Contact us today for more information!
