Quality Assurance (QA)
QA in customer support is the systematic process of monitoring, evaluating, and improving the quality of agent interactions to ensure they meet established standards for accuracy, tone, and resolution effectiveness.
In Depth
Traditional QA involves team leads or dedicated QA analysts manually reviewing a small sample of interactions — typically 2-5% — scoring them against rubrics that evaluate greeting, empathy, accuracy, resolution, and compliance. The fundamental problem is sample bias: reviewing 5% of conversations means 95% go unmonitored. AI-powered QA transforms this by automatically evaluating 100% of interactions in real-time.
AI can score conversations for sentiment, check for policy compliance, detect escalation patterns, and flag interactions that need human review. When AI agents handle conversations directly, QA becomes even more powerful because every response can be evaluated against quality criteria before it reaches the customer. GuruSup provides built-in QA analytics that evaluate every AI-handled interaction, ensuring consistent quality while giving supervisors visibility into edge cases that need attention.
Related Terms
CSAT Score
CSAT (Customer Satisfaction Score) is a metric that measures how satisfied customers are with a specific interaction or overall service, typically collected through post-interaction surveys.
Speech Analytics
Speech analytics uses AI and NLP to automatically analyze recorded or real-time voice conversations, extracting insights about customer sentiment, agent performance, compliance, and trending topics.
Sentiment Analysis
Sentiment analysis is an NLP technique that identifies and classifies the emotional tone behind text, determining whether a message expresses positive, negative, or neutral sentiment.
Learn More
