Use Case - Advanced Status Labels for Confluence
Real-Time Sentiment Tracking in Jira Service Issues
Monitor emotional tone throughout support tickets to boost resolution quality, prevent escalations, and improve customer experience.












Use Case
Real-Time Sentiment Tracking in Jira Service Issues
Challenge:
Enterprise support teams often lack real-time visibility into the evolving emotional state of customers during the lifecycle of a support ticket. Traditional JSM setups only capture static feedback or rely on agents’ subjective interpretation, which can miss critical shifts in customer sentiment. Without this insight, teams risk delayed responses to dissatisfaction, leading to escalations, poor customer experiences, and lost opportunities for timely intervention.

How the Functionality Solves This:
AI Insights integrates directly into individual Jira Service Management issues, enabling support agents and managers to track customer and agent sentiment in real time throughout the entire conversation. By analyzing issue summaries and comments, the tool provides a detailed timeline of emotional tones—such as excitement, frustration, or politeness—recorded against each issue. Agents can hover over conversation points to see sentiment scores and timestamps, and custom fields can surface the latest customer sentiment instantly within the issue view. This granular insight allows teams to spot changing attitudes, tailor their responses dynamically, and address problems before they escalate.

How It’s Better Than Default JSM Functionality:
Standard Jira Service Management lacks built-in, real-time emotional analytics tied to issue conversations. AI Insights enhances this by embedding sentiment analysis directly into issues without requiring additional workflows or external tools. Unlike static or post-resolution CSAT surveys, this solution provides a continuous, context-rich emotional history for each ticket, empowering enterprises to understand the full customer journey and improve resolution quality with timely, informed actions.
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