Hello Alex,
I can think of some practical use cases, I will list them below;
- Automate action item detection. This will automatically identifies important follow up tasks from conversations, highlights needs for customer record updates, flags cases requiring escalation and streamlines post-call work flow management.
- Sentiment analysis with context. This goes beyond the basic positive and negative labels. It will id up to 3 positive and 3 negative sentiment drivers per interaction and provide specific context for customer emotional states.
- Interaction intelligence provides a quick understanding of customer intent. It also does automatic outcome classification (resolved, partially resolved, open) and root cause analysis of negative experiences.
As for business case I believe there are three points, one would be operational efficiency. This reduces time spent on manual call reviews, streamlines quality management processes, automates task identification and followup and enables proactive issue management. The second is enhanced customer experience this includes faster issue resolution by getting a better understanding of interactions. Proactive identification of customer friction points and improved services quality through data driven insights. Third, team performance optimization. This would include data driven coaching opportunities, clear visibility into interaction outcomes, objective performance metrics and scalable quality management.
To answer your question about reporting AI insights can help with journey flows visualization. This is available in architect for inbound and secure call flows. This will help visualize the customer journey within flows, tracks flow milestones and monitors containment rates. It also integrates with quality management. This is accessible through QM programs. It works with both voice and digital transcripts and supports compliance monitoring.
And finally to answer your question about increasing accuracy. We have done system improvements with continuous updates to transcription accuracy, enhanced language support (including recent improvements for Portuguese) and refined PCI and PII entity detection. Some configurable options would be to customize sensitive data masking, adjust the PCI/PII entity redaction and integrate with compliance tools.
Hope this helps!
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Cameron
Online Community Manager/Moderator
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Original Message:
Sent: 09-05-2025 09:40
From: Alex Slocum
Subject: AI Insights
What is a practical Use Case for AI Insights for the call center operations. If we were to create a business case for it would be the key benefits? Since it is view view Interaction Analytics is there reporting that can be put in place? Is there a way to increase its accuracy?
#ConversationalAI(Bots,AgentAssist,etc.)
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Alex Slocum
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