- Customer Support Teams: Teams managing customer queries can benefit from timely sentiment analysis to address negative feedback promptly. - Project Managers: Individuals overseeing project timelines can utilize this workflow to monitor issues and prioritize based on sentiment trends. - Data Analysts: Analysts looking to gather insights from customer interactions can leverage the data captured in Airtable for further analysis. - Developers: Those integrating with Linear and Airtable can adapt this workflow to suit their specific needs and use cases.
Problem Solved
Problem Solved
This workflow addresses the challenge of monitoring customer sentiment in real-time. It automates the process of fetching updated issues from Linear, performing sentiment analysis on comments, and notifying relevant teams when sentiment shifts to negative. This proactive approach helps in identifying potential issues before they escalate, ensuring better customer satisfaction and timely responses.
Workflow Steps
Workflow Steps
1. Scheduled Trigger: The workflow initiates every 30 minutes to fetch updated issues from Linear. 2. Fetch Active Linear Issues: It queries the Linear API to retrieve issues that have been updated within the last 30 minutes. 3. Issues to List: The retrieved issues are split into individual items for further processing. 4. Sentiment over Issue Comments: Each issue's comments are analyzed using an AI model to assess sentiment. 5. Combine Sentiment Analysis: The results of the sentiment analysis are combined with the original issue data. 6. For Each Issue: The workflow processes each issue to check for existing sentiment in Airtable. 7. Get Existing Sentiment: It retrieves the current sentiment from Airtable for comparison. 8. Update Row: The workflow updates the Airtable row with the new sentiment and stores the previous sentiment for tracking. 9. Sentiment Transition: It checks for transitions from non-negative to negative sentiment. 10. Deduplicate Notifications: Ensures notifications are sent only for new transitions to avoid redundancy. 11. Report Issue Negative Transition: If a negative transition is detected, a notification is sent to a designated Slack channel to alert the team.
Customization Guide
Customization Guide
- Change the Trigger Frequency: Adjust the schedule trigger to run at different intervals (e.g., every 15 minutes or hourly) based on your needs. - Modify Linear API Queries: Update the GraphQL query to filter issues based on specific criteria (e.g., issues assigned to a particular team or with certain labels). - Customize Sentiment Analysis: You can tweak the AI model parameters used in the sentiment analysis to improve accuracy or adapt it to specific contexts. - Update Slack Notifications: Change the Slack channel in the notification step to direct alerts to the appropriate team members. - Enhance Airtable Fields: Add additional fields in Airtable to capture more insights or metrics based on your specific requirements.