This article provides a complete, practical walkthrough of the Googlesheets Gmail Automation Webhook 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:  
   Streamlining Customer Inquiries: Automating WordPress Contact Form Responses with AI and n8n
   
   Meta Description:  
   Discover how to efficiently handle customer inquiries from your WordPress site using an n8n automation workflow with Google Gemini AI. Automatically classify, respond to, and archive messages without lifting a finger.
   
   Keywords:  
   n8n workflow automation, WordPress CF7 automation, AI contact form response, Google Gemini integration, automate customer support, natural language classification, contact form auto email draft, Google Sheets integration, AI response generator
   
   Third-Party APIs Used:
   
   1. Google Gemini (PaLM) API – Used to classify messages and generate context-aware email drafts using natural language processing.
   2. Gmail API – Drafts automated responses to customers based on classified content.
   3. Google Sheets API – Stores contact form submissions alongside AI-generated responses to maintain a structured record.
   4. WordPress Contact Form 7 to Webhook Plugin – Sends POST requests to the n8n webhook when a user submits a contact form.
   
   —
   
   Article:  
   In an age where businesses juggle dozens or even hundreds of customer inquiries daily, responding accurately, quickly, and professionally is essential. Whether it's answering product queries or updating customers on the status of their orders, the process must be streamlined to save time and maintain customer satisfaction.
   
   This is where automation shines. Using n8n—a powerful open-source workflow automation tool—combined with state-of-the-art AI from Google Gemini and structured data storage via Google Sheets, we've developed a workflow that transforms raw contact form submissions into classified, thoughtful, and neatly archived email drafts. Here’s how it works.
   
   1. The Trigger: WordPress Contact Form 7 (CF7) Integration  
   The journey begins with a customer submitting a message through a Contact Form 7-enabled form on a WordPress site. Thanks to the “CF7 to Webhook” plugin, this form’s data is sent as a POST request to an n8n webhook. This plugin acts as a bridge between the WordPress site and your workflow automation tool, making the form data accessible in real-time.
   
   2. Structuring the Data  
   Once the message hits the n8n webhook, the workflow sanitizes and structures the input using a “Set” node. This extracts relevant values from the payload, such as the sender's name, email, phone number, and message body. Having clean and granular data is essential for downstream AI models to accurately analyze and respond to inquiries.
   
   3. Intelligence Kicks In: Google Gemini Classification  
   The AI engine at the heart of this system is Google Gemini (formerly known as PaLM). The workflow sends the extracted message to a message classification node, which utilizes Gemini to label each submission into one of three primary categories:
   
   - Product Info – The user is asking for more information about a product or service.  
   - Order Info – The inquiry relates to an existing order.  
   - Other – Miscellaneous or uncategorizable queries.
   
   This layer of smart filtering ensures that each message is treated appropriately, setting the stage for hyper-relevant replies.
   
   4. AI-Powered Response Generation  
   Each classification type has a dedicated natural language model chain that generates a custom draft response. Using a system prompt fine-tuned for professionalism and empathy, the model analyzes the customer’s request and constructs a complete email composed of:
   
   - A personalized greeting
   - Message acknowledgment
   - Context-based response
   - Proposed next steps or actions
   - A polite closing with a company signature
   
   This holistic approach ensures every response feels personal and helpful—even though it’s completely automated.
   
   5. Drafting and Email Management  
   Each AI-generated draft is passed to the Gmail API, which saves it as a draft in the appropriate department’s Gmail account (e.g., sales@yourcompany.com or support@yourcompany.com). This allows a human agent to review and send the email if necessary, offering a perfect blend of automation and oversight.
   
   6. Structured Record-Keeping with Google Sheets  
   Every submission, along with its classification, customer data, and AI-generated draft, is appended to a designated Google Sheet. This centralized repository makes audit trails, trend analysis, and team collaboration seamless.
   
   Three distinct append actions are defined based on message types ("Product Info", "Order Info", or "Other"), so everything remains organized.
   
   7. Customization and Flexibility  
   One of the greatest strengths of this workflow lies in its adaptability. You can easily customize the classification labels, add more message categories, or adjust the system prompt to match your brand's tone and customer service principles. For international use cases, you could even modify the GPT prompts or Gemini models to handle different languages and local practices.
   
   —
   
   Why This Workflow Matters  
   This n8n workflow is not just a productivity hack; it’s a strategic upgrade to your customer engagement process. Businesses today cannot afford to overlook or delay customer communications. By implementing this AI-augmented system, you ensure every inquiry is met with professionalism and speed—while freeing up valuable resources.
   
   Whether you run a SaaS business, manage e-commerce orders, or operate a service-oriented website, this intelligent automation grants you the power to scale customer interactions without scaling your team.
   
   Final Thoughts  
   In today’s digital business environment, response speed can make or break a customer relationship. By implementing this n8n-driven automation workflow powered by Google Gemini and integrated with Gmail and Google Sheets, you bridge the gap between technology and empathy—offering helpful, thoughtful replies almost instantly.
   
   With automation tools like this, your team can shift their focus from reactive support to proactive growth.

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.