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Automated Feedback Sentiment Analysis and Alert System

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Mattermost Automate streamlines feedback management by automatically analyzing sentiment from Typeform responses. When negative feedback is detected, it sends immediate alerts to the designated Mattermost channel, ensuring timely responses and improved user engagement. This workflow enhances communication and facilitates proactive issue resolution.

Workflow Overview

Mattermost Automate streamlines feedback management by automatically analyzing sentiment from Typeform responses. When negative feedback is detected, it sends immediate alerts to the designated Mattermost channel, ensuring timely responses and improved user engagement. This workflow enhances communication and facilitates proactive issue resolution.

  • Event Organizers: Those who collect feedback after events and want real-time sentiment analysis.
  • Customer Experience Managers: Professionals looking to understand customer sentiments and improve service based on feedback.
  • Data Analysts: Individuals who analyze customer feedback and need automated tools to streamline their processes.
  • Developers: Tech-savvy users who want to integrate various services for automated workflows.

This workflow addresses the challenge of efficiently collecting and analyzing feedback from events. By automating the sentiment analysis process, it enables users to quickly identify negative sentiments and take necessary actions, enhancing overall customer satisfaction and engagement.

  1. Trigger: The workflow begins with a manual trigger from a Typeform survey where participants provide feedback about an event.
  2. Sentiment Analysis: The feedback text is sent to AWS Comprehend for sentiment analysis to detect if the sentiment is NEGATIVE.
  3. Conditional Logic: An IF node checks the sentiment result. If the sentiment is negative, the workflow proceeds to notify via Mattermost.
  4. Notification: A message is sent to a designated Mattermost channel, summarizing the feedback and its sentiment score, ensuring that the team is promptly informed about any issues.

Statistics

5
Nodes
0
Downloads
27
Views
1497
File Size

Quick Info

Categories
Communication & Messaging
Manual Triggered
+2
Complexity
medium

Tags

manual
medium
noop
logic
conditional
typeformtrigger
mattermost
awscomprehend

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