This article provides a complete, practical walkthrough of the Mattermost Typeform Send Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Automating Negative Feedback Alerts with n8n, Typeform, AWS Comprehend, and Mattermost
   
   Meta Description:  
   Discover how to automatically analyze sentiment from event feedback using n8n and send notifications for negative responses directly to a Mattermost channel with AWS Comprehend and Typeform.
   
   Keywords:  
   n8n workflow, Typeform integration, AWS Comprehend, Mattermost alert, sentiment analysis automation, no-code workflow, negative feedback detection, customer feedback automation
   
   Third-Party APIs Used:
   
   - Typeform API (for collecting user feedback)
   - AWS Comprehend API (for sentiment analysis)
   - Mattermost API (for sending alerts/messages)
   
   Article:
   
   In today's fast-paced digital environment, customer feedback plays a pivotal role in improving services and products. But sifting through large volumes of responses manually to find critical feedback can be time-consuming and prone to human error. This challenge can be tackled head-on using n8n — a powerful open-source automation tool — alongside Typeform, AWS Comprehend, and Mattermost to create an automated feedback monitoring system.
   
   In this article, we'll walk through a simple n8n workflow designed to listen for responses to a Typeform survey, detect negative sentiment using AWS Comprehend, and send a real-time alert to a Mattermost channel when negative feedback is identified. The automation minimizes manual effort, reduces response time, and ensures that urgent concerns are flagged effectively.
   
   Understanding the Workflow
   
   Let’s break down the workflow step by step to understand how it functions.
   
   1. Typeform Trigger — Capturing Feedback
   The workflow begins with the “Typeform Trigger” node, which listens to a specific Typeform (identified by its form ID: DuJHEGW5) for new submissions. Specifically, it’s configured to extract a response to the question: “What did you think about the event?”
   
   This node acts as the entry point for feedback coming from form respondents — once a user submits the form, the workflow is automatically triggered.
   
   2. AWS Comprehend — Analyzing Sentiment
   Next, the user’s comment is passed to the "AWS Comprehend" node. AWS Comprehend is a powerful machine learning API from Amazon Web Services that detects the sentiment behind a given piece of text (Positive, Negative, Neutral, or Mixed). In this case, we send the answer from Typeform to AWS Comprehend for analysis.
   
   The node is configured to perform the detectSentiment operation and returns sentiment classification along with sentiment scores for each category.
   
   3. IF Node — Filtering Negative Responses
   After receiving the sentiment classification from AWS Comprehend, the workflow uses an “IF” node to evaluate whether the sentiment is “NEGATIVE.” This is a decision-making node that routes the automation down two paths:
   
   - If the sentiment is negative, proceed to notify via Mattermost.
   - Otherwise, terminate gracefully via a NoOp node (which essentially does nothing, used as a placeholder or endpoint).
   
   4. Mattermost Notification — Real-Time Alerts
   If the feedback is categorized as negative, the workflow sends a notification to a pre-specified Mattermost channel using the “Mattermost” node. The message includes not only the textual feedback but also the confidence score for the negative sentiment as returned by AWS Comprehend. This lets your support or event team know exactly which feedback items require immediate attention.
   
   Here’s an example of the notification format:
   "You got new feedback with a score of 0.89. Here is what it says: The event was disorganized and started late."
   
   This type of alert elevates critical feedback to the right team in real-time, enabling swift follow-up, understanding, and corrective action.
   
   Why This Automation Matters
   
   - Real-Time Monitoring: By leveraging AI-powered sentiment analysis, this workflow ensures feedback is interpreted and reacted to immediately.
   - Human Resource Optimization: Teams no longer need to read through every piece of feedback to find action items — automation handles this heavy lifting.
   - Scalable Solution: As your event or business grows, this system scales effortlessly to handle increased volume.
   - Emotional Intelligence for Business: Monitoring sentiment is not just technical but strategic. It enables empathy-driven responses that can strengthen customer satisfaction and retention.
   
   Getting Started
   
   To replicate or adapt this workflow for your own use case, you’ll need:
   
   - A free or paid n8n instance (self-hosted or cloud)
   - AWS account with permissions for Comprehend
   - A Typeform account with an active form
   - Mattermost workspace and appropriate channel ID
   
   You'll also need to configure and store appropriate credentials for the Typeform API, AWS Comprehend, and Mattermost inside n8n. These are securely managed in n8n and used to authenticate API calls.
   
   Conclusion
   
   Feedback is a goldmine of insights, but only if you can act on it quickly and effectively. This n8n workflow demonstrates a simple yet powerful way to automate the detection and management of negative sentiment in user feedback. By integrating Typeform, AWS Comprehend, and Mattermost, you can ensure better customer experiences and operational agility — all without writing a single line of code.
   
   Whether you're organizing events, managing product feedback, or supporting customer service teams, this automated solution offers a scalable, reliable, and intelligent way to stay on top of critical feedback.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.