This article provides a complete, practical walkthrough of the Form Googlesheets 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:  
   Transforming eCommerce Customer Support with Automated Contact Form Classification in n8n
   
   Meta Description:  
   Discover how an intelligent n8n workflow automates contact form handling for eCommerce businesses using OpenAI for message classification, streamlined departmental routing, and Google Sheets data logging.
   
   Keywords:
   n8n workflow, eCommerce automation, contact form automation, text classification, OpenAI, Google Sheets automation, customer support automation, LangChain, AI form processor, webhook automation, automated email routing, GPT-4, form submission AI
   
   Article:
   
   Revolutionizing eCommerce Customer Support: Automating Contact Form Classification with n8n
   
   In the fast-paced world of eCommerce, providing timely, personalized customer support is critical—but manually managing contact form submissions can be tedious and prone to error. Enter the “Contact Form Text Classifier for eCommerce,” a powerful n8n workflow that leverages artificial intelligence and automation to streamline how eCommerce businesses handle customer inquiries.
   
   This intelligent automation solution routes messages to the appropriate departments, classifies inquiries using AI, and logs essential data in a Google Sheet for future reporting. Let’s break down how this workflow functions and how it can elevate your customer support strategy.
   
   The Need for Smart Contact Form Processing
   
   eCommerce businesses typically receive a diverse array of inquiries: requests for quotes, product information, complaints about orders, and general queries. Using a single inbox to manage such varied content creates delays, clogs workflows, and risks important messages getting missed or misinterpreted.
   
   This n8n-powered blueprint solves those difficulties by offering:
   
   - Instant categorization using AI
   - Auto-routing to the correct department
   - Logging for analytics and follow-up
   - Scalability and integration with third-party tools
   
   Core Workflow Breakdown
   
   1. User Submission via Contact Form
   
   The workflow begins with the "On form submission" node which is triggered when a customer submits their details and message through a contact form. The form fields collected include Name, Email, and Message. This form can be customized or replaced—for example, with Contact Form 7 in WordPress—thanks to the webhook integration.
   
   2. AI-Powered Text Classification
   
   Next, the message body is passed to the “Text Classifier” node, a LangChain-enabled n8n node utilizing OpenAI’s GPT-4 model (via the "OpenAI" node) to classify the message.
   
   The text is categorized into one of five buckets:
   
   - Request Quote
   - Product Info
   - General Problem
   - Order
   - Other
   
   The system prompt instructs AI to format its result strictly as a JSON object without explanation, ensuring clean and usable data for the rest of the workflow.
   
   3. Dynamic Email Routing
   
   Based on the classified result, the workflow directs the message to the appropriate department via the following email nodes:
   
   - Quote Dep.
   - Prod. Dep.
   - Gen. Dep.
   - Order Dep.
   - Other Dep.
   
   Each email includes the sender’s name, email, the original message, and a category label. A reply-to header ensures that responses go directly to the customer.
   
   4. Data Logging in Google Sheets
   
   Beyond email alerts, organizational knowledge is preserved through dedicated logging per category. The classified data is appended to a Google Sheet (“Classified Contact Form”) within specific sheets depending on the category, such as:
   
   - Quote DB
   - Prod DB
   - General DB
   - Order DB
   - Other DB
   
   Each entry documents the submission date, customer details, inquiry category, and full message—an invaluable resource for analytics, customer tracking, and proactive outreach.
   
   Flexibility and Integration
   
   This workflow is modular, making it highly adaptable:
   
   - Form inputs can come from any service supporting webhooks (i.e., CF7, Unbounce, Typeform).
   - Emails can be rerouted through any provider by replacing the SMTP node (Gmail, Outlook, SendGrid, etc.).
   - Data storage can be modified to use tools other than Google Sheets such as Airtable, MySQL, or Notion.
   
   Applications and Benefits
   
   This solution is perfect for:
   
   - eCommerce stores seeking to optimize their support funnel
   - B2B wholesalers managing quote requests
   - Multi-product companies needing issue categorization
   - Teams wanting better cross-department message handling
   
   The end result is more responsive customer service, less time spent triaging emails, and better data collection.
   
   Conclusion
   
   The “Contact Form Text Classifier for eCommerce” is more than just a workflow—it’s a blueprint for intelligent support. By leveraging GPT-4, smart routing, and cloud-based logs, businesses can deliver faster, more accurate responses with minimal human intervention. Whether you're scaling your support team or improving customer experience, this automation delivers immediate ROI.
   
   Third-Party APIs Used:
   
   1. OpenAI (via LangChain for text classification using GPT-4)
   2. Google Sheets API (for structured data logging)
   3. SMTP Provider (for email sending — replaceable with Gmail, Outlook, etc.)
   
   If you’re an eCommerce business ready to modernize your contact process, this workflow provides the perfect launchpad.
   
   — Written with AI Assistance —

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.