This article provides a complete, practical walkthrough of the Openai Form Automation 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:
   Streamline Customer Feedback with AI: Automating Sentiment Analysis in n8n Using OpenAI and Google Sheets
   
   Meta Description:
   Learn how to automate customer feedback processing with n8n by integrating OpenAI's sentiment analysis and Google Sheets. Capture responses, analyze sentiment, and store insights effortlessly.
   
   Keywords:
   n8n workflow, sentiment analysis, customer feedback automation, OpenAI GPT, Google Sheets integration, form trigger automation, emotion classification, AI feedback analysis, workflow automation tools, low-code automation
   
   Third-Party APIs Used:
   
   1. OpenAI API
      - Purpose: To classify customer feedback sentiment (e.g., Positive, Negative, Neutral)
      
   2. Google Sheets API (via OAuth2)
      - Purpose: To store structured feedback data in a shared spreadsheet for tracking, reporting, and customer service analysis
   
   Article:
   
   Automating Customer Sentiment Insights with n8n, OpenAI, and Google Sheets
   
   In today’s fast-paced digital landscape, customer feedback is a goldmine of insights—but without the right tools, it’s easy for valuable feedback to slip through the cracks. Automating the collection, processing, and storage of customer opinions not only saves time but helps organizations respond faster and smarter. That’s where low-code automation tools like n8n come in.
   
   This article walks you through an efficient, AI-powered feedback automation workflow built in n8n. It takes customer responses from a simple form, analyzes the sentiment using OpenAI’s GPT model, and logs the results in a Google Sheet for real-time review and action.
   
   The Workflow Overview
   
   At a high level, this workflow performs three essential steps:
   
   1. Collect customer feedback through a web form.
   2. Analyze the feedback’s sentiment using OpenAI.
   3. Store the synthesized results in a Google Sheet for transparency and action.
   
   Let’s zoom into each stage of this pipeline and see how it adds value.
   
   Step 1: Capturing Feedback Through a Form
   
   Using n8n’s Form Trigger node, a web form is presented to customers, prompting them to provide:
   - Their name
   - A dropdown selection about what their feedback is about: Product, Service, or Other
   - Detailed feedback in a text area
   - Optional contact details
   
   Every time a user submits the form, it triggers the rest of the workflow. This form serves as the entry point for funneling raw qualitative data into a more structured feedback pipeline.
   
   Step 2: Automating Sentiment Classification with OpenAI
   
   Once form data has been submitted, it branches into two primary workflows:
   - The raw form data continues into one pathway
   - Simultaneously, the textual feedback undergoes AI analysis via the OpenAI Node.
   
   Here, a dynamic prompt is constructed:  
   "Classify the sentiment in the following customer feedback: {{ $json['Your feedback'] }}"
   
   This prompt utilizes OpenAI’s language model (such as GPT-3.5 or GPT-4) to analyze the tone and context of the feedback, returning results like "Positive", "Neutral", or "Negative". This layer of analysis helps internal teams quickly prioritize issues and gauge overall customer happiness at a glance.
   
   Step 3: Merging and Storing Insights in Google Sheets
   
   The next step involves combining the AI-classified sentiment with the corresponding customer form data. n8n’s Merge node (set to “multiplex” mode) brings together the AI-generated result and the form inputs into a single object payload.
   
   Then, using the “Google Sheets” node configured with the company’s OAuth credentials, this unified data is appended as a new row into a connected Google Sheet. The columns include:
   
   - Timestamp (automatically tracked)
   - Customer Name
   - Contact Info
   - Feedback Category (Product, Service, Other)
   - Original Feedback Text
   - Sentiment Classification
   - Data Entry Source (“Form”)
   - Any urgency indicators (optional / for future modification)
   
   This spreadsheet becomes a real-time dashboard that customer service teams, product managers, and analysts can monitor to inform decisions, respond to urgent feedback, and track overall sentiment trends.
   
   Ease of Setup and Scalability
   
   Setting up this automation is straightforward for anyone using n8n:
   
   1. Connect your Google Sheets and OpenAI accounts via API credentials.
   2. Customize or import the example feedback Google Sheet.
   3. Deploy the form and publish it to customers via email, website, or support portals.
   
   This modular flexibility means the workflow can evolve with your business. You can expand it to filter negative feedback for ticket creation, tag feedback by keywords, or even send automated alerts to team members.
   
   Conclusion
   
   With this n8n workflow, businesses can convert unstructured customer data into structured insights without spinning up a whole dev team. By incorporating the intelligence of OpenAI and the simplicity of Google Sheets, this automation makes it easy to consistently gather, analyze, and store feedback at scale.
   
   Instead of manually digging through form submissions, companies can now rely on a real-time, AI-powered sentiment analysis workflow—leading to faster intervention, increased customer satisfaction, and meaningful improvements.
   
   To get started, download the example workflow and spreadsheet from the linked resources in the instructions, hook up your credentials, and start collecting smarter feedback today.
   
   —
   
   Need help scaling your n8n workflows for CRM, marketing, or support? Let us know, and we’ll help build a custom automation plan.

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.