- Customer Support Teams: Automate responses and manage long-lived JIRA issues effectively. - Project Managers: Gain insights into unresolved issues and improve team efficiency. - Developers: Reduce the time spent on repetitive tasks and focus on coding. - Business Analysts: Analyze customer feedback and issue resolution trends to improve service quality.
Problem Solved
What Problem Does This Workflow Solve
- Long-Lived Issues: Automatically identifies JIRA issues unresolved for over 7 days, ensuring they are addressed promptly. - Customer Engagement: Sends reminders to users for pending actions, reducing the likelihood of unresolved queries. - Automated Resolution: Utilizes AI to suggest solutions based on historical data, decreasing the workload on support staff. - Sentiment Analysis: Evaluates customer satisfaction and escalates issues when negative sentiment is detected, ensuring a proactive approach to customer service.
Workflow Steps
Detailed Explanation of the Workflow Process
1. Scheduled Trigger: The workflow runs daily to check for unresolved JIRA issues older than 7 days. 2. Fetch Issues: Retrieves a list of long-lived issues from JIRA. 3. Parallel Processing: Each issue is processed in parallel using the Execute Workflow node for efficiency. 4. Comment Aggregation: Collects and simplifies all comments related to the issue for better context. 5. AI Classification: Uses a text classifier to determine the state of the issue (resolved, pending more information, or still waiting). 6. Sentiment Analysis: Analyzes the sentiment of the comments to assess customer satisfaction. 7. Automated Responses: If a solution is found, it posts a response and closes the issue; if unresolved, it sends a reminder or escalates if sentiment is negative. 8. Notifications: Sends updates to Slack channels for visibility and team coordination.
Customization Guide
How Users Can Customize and Adapt This Workflow
- Adjust the JQL Query: Modify the JQL in the 'Get List of Unresolved Long Lived Issues' node to fit your criteria for unresolved issues. - Change the AI Models: Update the OpenAI Chat Model parameters to use different models or adjust the prompts for better responses. - Modify Notifications: Customize the Slack messages and channels to fit your team's communication preferences. - Add New Nodes: Integrate additional tools or nodes for other platforms (e.g., email notifications) to expand functionality. - Refine Conditions: Tweak the conditions in the 'if' nodes to better suit your operational needs.