Description
Overview
This Contact Form Text Classifier for eCommerce is an automation workflow designed to categorize and route customer inquiries submitted via contact forms. This orchestration pipeline uses AI-powered text classification to identify message intent, enabling precise handling of requests such as quotes, product information, orders, or general problems. Triggered by a webhook form submission node configured with mandatory Name, Email, and Message fields, it supports structured, intent-based communication flow for eCommerce and customer support teams.
Key Benefits
- Automates classification of contact form messages with AI-driven text categorization.
- Routes inquiries via email to the appropriate department based on message intent.
- Logs all submissions into categorized Google Sheets databases for record-keeping.
- Supports fallback handling for messages outside defined categories to ensure no data loss.
- Enables seamless integration with external forms through webhook triggers.
Product Overview
This automation workflow activates upon submission of a contact form titled “Contacts,” which requires users to provide Name, Email, and Message fields. The form trigger node listens for incoming webhook submissions, initiating the workflow synchronously. Submitted messages are forwarded to a text classification node leveraging a GPT-based language model configured to categorize text into four main classes: Request Quote, Product info, General problem, and Order. Messages that do not match these categories default to “other.” Based on classification results, the workflow branches into multiple email dispatch nodes, each targeting a specific department with relevant content including sender details and message text. Simultaneously, it appends submission records to corresponding Google Sheets documents, creating structured data repositories for tracking and analysis. The workflow relies on OAuth2 credentials for Google Sheets access and SMTP credentials for email delivery. Error handling follows platform defaults, with no explicit retry or backoff logic implemented.
Features and Outcomes
Core Automation
This no-code integration accepts contact form submissions as inputs and applies deterministic AI classification rules to route messages into predefined categories. The Text Classifier node utilizes a system prompt template ensuring consistent JSON-only output for category assignment.
- Single-pass evaluation of message content for swift classification.
- Branching logic directs outputs to dedicated email and logging nodes.
- Fallback category ensures all inputs are handled without omission.
Integrations and Intake
The workflow integrates with contact form webhooks for intake, authenticated Google Sheets via OAuth2 for data storage, and SMTP servers for email delivery. Incoming payloads must include Name, Email, and Message fields as required by the form trigger.
- FormTrigger node for webhook-based intake of contact form data.
- Google Sheets nodes for categorized data persistence and analysis.
- SMTP nodes configured for email dispatch to designated departments.
Outputs and Consumption
The workflow produces categorized email messages and appends structured rows to Google Sheets asynchronously. Output fields include sender Name, Email, Message, category label, and submission timestamp, facilitating downstream analysis or reporting.
- HTML-formatted emails routed to department-specific addresses.
- Google Sheets rows appended with fields: TO, DATA, NOME, EMAIL, CATEGORIA, RICHIESTA.
- Asynchronous logging supports auditability without blocking email dispatch.
Workflow — End-to-End Execution
Step 1: Trigger
The workflow initiates on submission of a contact form via a webhook trigger node named “On form submission.” The form requires three fields: Name, Email, and Message. Each submission payload activates the workflow with the user’s input data.
Step 2: Processing
The submitted message text undergoes basic presence validation through required field enforcement on the form trigger. The message is then processed by the “Text Classifier” node, which applies a system prompt to instruct AI classification without additional schema validation beyond text presence.
Step 3: Analysis
The text classification node uses a GPT-based model to categorize the message into one of five categories: Request Quote, Product info, General problem, Order, or other (fallback). The classification output is a JSON object containing the selected category, with no additional explanation or metadata.
Step 4: Delivery
Classified messages are routed to dedicated SMTP email nodes corresponding to each category for dispatch to respective departments. Concurrently, submission data is appended to category-specific Google Sheets documents. Emails include sender details and message content, with the sender’s email set as the reply-to address.
Use Cases
Scenario 1
An eCommerce support team receives diverse customer inquiries via a contact form. The automation workflow classifies each message by intent and routes it to the appropriate department. This reduces manual sorting and accelerates response times, ensuring inquiries are addressed efficiently.
Scenario 2
A product management team needs to track all incoming product-related questions. This orchestration pipeline logs categorized messages into Google Sheets, enabling structured analysis and trend identification without additional manual data entry.
Scenario 3
Customer service handles requests for quotes, orders, and general problems through a single contact point. The workflow’s AI text classifier routes each inquiry to a specialized email address, improving departmental focus and reducing misdirected communications.
How to use
To deploy this Contact Form Text Classifier for eCommerce within n8n, import the workflow and configure the webhook URL in your external contact form. Ensure the form submits required fields: Name, Email, and Message. Set up OAuth2 credentials for Google Sheets access and SMTP credentials for email sending. Activate the workflow to enable live processing. Upon activation, expect incoming submissions to be classified, routed via email, and logged automatically.
Comparison — Manual Process vs. Automation Workflow
| Attribute | Manual/Alternative | This Workflow |
|---|---|---|
| Steps required | Multiple manual sorting, forwarding, and data entry steps. | Automated classification, routing, and logging in a single pipeline. |
| Consistency | Subject to human error and inconsistent categorization. | Deterministic AI classification ensures uniform message categorization. |
| Scalability | Limited by human resource capacity and manual effort. | Scales automatically with incoming submission volume. |
| Maintenance | Requires ongoing training and supervision of staff. | Requires credential updates and periodic prompt tuning only. |
Technical Specifications
| Environment | n8n workflow automation platform |
|---|---|
| Tools / APIs | OpenAI GPT-based language model, Google Sheets API, SMTP email service |
| Execution Model | Synchronous webhook-triggered execution with asynchronous email and data logging |
| Input Formats | Webhook JSON payload with Name, Email, Message fields |
| Output Formats | HTML email messages, appended Google Sheets rows |
| Data Handling | Transient processing; data persisted only in Google Sheets and emails |
| Known Constraints | Relies on availability of external OpenAI and Google Sheets APIs |
| Credentials | OAuth2 for Google Sheets, SMTP credentials for email sending |
Implementation Requirements
- External contact form capable of submitting webhook POST requests with required fields.
- Valid OAuth2 credentials configured for Google Sheets API access.
- SMTP credentials for email delivery to designated department addresses.
Configuration & Validation
- Confirm the contact form submits required fields (Name, Email, Message) through the webhook trigger.
- Verify OpenAI credentials allow classification node to access GPT-based models.
- Test email nodes by sending sample classified messages to department inboxes and confirm receipt.
Data Provenance
- Trigger node: “On form submission” listens to webhook contact form submissions.
- Classification node: “Text Classifier” uses OpenAI GPT-based model for intent categorization.
- Output nodes: SMTP email nodes and Google Sheets nodes store and forward classified data.
FAQ
How is the Contact Form Text Classifier automation workflow triggered?
The workflow is triggered by a webhook-based form submission node configured to listen for contact form inputs containing Name, Email, and Message fields.
Which tools or models does the orchestration pipeline use?
The pipeline uses an OpenAI GPT-based language model accessed via the n8n Text Classifier node for AI-driven message categorization.
What does the response look like for client consumption?
The workflow sends HTML-formatted emails to designated departments and appends structured data rows to Google Sheets for logging and analysis.
Is any data persisted by the workflow?
Data is transiently processed within n8n but persisted externally in Google Sheets and sent as emails; no internal database storage occurs.
How are errors handled in this integration flow?
Error handling relies on n8n platform defaults; no explicit retry or backoff strategies are configured within the workflow.
Conclusion
This Contact Form Text Classifier for eCommerce provides a structured, AI-driven solution to automate the categorization and routing of customer inquiries. It ensures deterministic handling of incoming messages through a predefined set of categories, enabling targeted email dispatch and systematic logging into Google Sheets. The workflow requires valid external API credentials and depends on OpenAI and Google services availability. Its modular design supports integration with various contact form systems and email providers, delivering consistent and scalable processing without manual intervention.
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