Revealing the Top 11 AutoQA Metrics
Spotting “Hot Spots” in Call Center, CX, and Support Operations
Exploring Our Top AutoQA Metrics
We analyzed our customer data and hand-picked 11 popular AutoQA metrics that demonstrate the precision and transformative capabilities of these insights. These metrics provide a new lens for CX teams, uncovering hidden insights that traditional methods miss completely.
Screenshot Requested
Helps identify agents' troubleshooting approach.
Measures the balance between asking for screenshots and internal research.
Provides a coachable metric to improve customer issue resolution efficiency.
Negative Sentiment
Detects negative customer sentiment in conversations.
Focuses on identifying agents with higher rates of negative sentiment interactions.
Enables coaching to improve customer interaction quality and empathy.
Low Empathy Response
Evaluates the agents' responses to highly negative sentiment from customers.
Measures the use of personalization and empathy in responses.
Aims to ensure responses come across as empathetic and not robotic.
High Effort - Chat
Analyzes chat interactions for signs of high customer effort.
Considers factors like chat length, back-and-forth, and repeated phrases.
Helps identify areas where customer interactions can be made more efficient.
Re-Open Rate
Tracks the rate at which resolved conversations are reopened.
Focuses on ensuring resolutions are complete and meet customer needs.
Aids in assigning the right agent to handle reopened issues effectively.
Repeat Empathy
Evaluates the frequency of repeated empathy statements in responses.
Aims to avoid the use of repetitive and insincere empathy phrases.
Encourages more varied and genuine empathy in customer interactions.
Internal Processes Followed
Assesses adherence to internal processes during customer interactions.
Helps ensure agents follow specified procedures accurately.
Enables coaching for process compliance and efficiency improvement.
Transfers
Measures the frequency of ticket transfers between agents.
Evaluates the effectiveness of initial issue handling by agents.
Aids in optimizing ticket routing and minimizing unnecessary transfers.
Email Close Rate
Tracks which agents successfully close email interactions.
Focuses on the final agent's role in resolving email inquiries.
Complements the First Contact Resolution (FCR) metric for email support.
Time in Knowledge Base
Monitors how often agents refer to the knowledge base during interactions.
Analyzes the duration agents spend accessing knowledge resources.
Helps identify training and knowledge utilization gaps.
Chat to Email
Measures the frequency of transitioning from chat to email for issue resolution.
Reflects the need for multi-channel support in resolving complex issues.
Assists in optimizing the chat-to-email transition process for better customer experiences.
Unveiling AutoQA Metric Categories
In addition to the individual AutoQA metrics we've discussed, let's also explore the overarching categories that these metrics fall into. Understanding these categories provides a structured approach to enhancing your customer service quality assurance strategy.