This article provides a complete, practical walkthrough of the Webhook Http 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

   Sure! Here's the deliverable based on the provided n8n workflow:
   
   ---
   
   ## Title:
   Automating Company Data Enrichment with n8n, OpenAI, and Web Scraping Tools
   
   ## Meta Description:
   Learn how to automate company profiling by enriching Google Sheets data using n8n, OpenAI GPT-4o, and a website scraping tool. Perfect for marketing, sales intelligence, or lead generation workflows.
   
   ## Keywords:
   n8n workflow, OpenAI GPT-4o, web scraping, ScrapingBee, structured data enrichment, Google Sheets automation, AI agent, company profiling, marketing automation, lead enrichment, GPT-4 for business, LangChain, CRM data enrichment
   
   ## Third-Party APIs Used:
   - Google Sheets API
   - OpenAI API (GPT-4o-mini)
   - ScrapingBee API
   
   ---
   
   ## Article:
   
   ### Supercharge Company Profiling with n8n, OpenAI, and ScrapingBee
   
   Collecting meaningful insights about a company's business model, value proposition, and ideal customer profile can be labor-intensive—especially when done manually across dozens or hundreds of leads. But what if you could automate the process from end to end? Using n8n, OpenAI’s GPT-powered agent, and ScrapingBee’s web scraping API, you can turn raw URLs from a Google Sheet into structured, enriched business data.
   
   Let’s break down how this powerful automation workflow operates, and how you can tailor it to transform static company URLs into smart, actionable insights.
   
   ---
   
   ### The Objective
   
   This n8n workflow automatically takes a list of companies from a Google Sheet—each with a company name and website—and enriches them with business intelligence by:
   
   - Scraping their homepage content
   - Analyzing it with GPT-4o-mini from OpenAI
   - Extracting structured data such as their business area, offers, value proposition, business model, and ideal customer profile (ICP)
   - Updating the original Google Sheet with this enhanced information
   
   ---
   
   ### The Workflow Breakdown
   
   #### 🧩 1. Trigger Event: Webhook URL or Manual Execution
   Kickstart the process with a webhook trigger or a manual run. This node initiates the automated enrichment process. You can easily connect it with form submissions, CRM interactions, or any other app that n8n supports.
   
   #### 📄 2. Retrieve Companies from Google Sheets
   Using n8n’s native Google Sheets integration, the workflow pulls in a list of companies with their corresponding website URLs. These are expected to live in columns labeled “Company” and “Website.” Other columns such as “Business model” or “ICP” start empty and will be filled by the AI.
   
   #### 🔁 3. Loop Through Each Company
   The “Split in Batches” node ensures a sequential loop of each row, allowing the scraping and AI processing tools to focus on one company at a time.
   
   #### 🧠 4. Invoke the AI Agent with GPT-4o-mini
   Now the magic begins:
   
   1. A scraping tool is triggered.
   2. The homepage HTML is retrieved using ScrapingBee.
   3. The raw HTML is then converted into a clean Markdown format—ideal for reducing token usage and improving AI interpretation.
   4. The cleaned text is fed to an AI agent (powered by GPT-4o-mini) with a carefully crafted system prompt.
   
   This prompt instructs the AI to extract and summarize:
   
   - Business Area
   - Main Product or Offer
   - Value Proposition
   - Business Model
   - Ideal Customer Profile
   
   Plus, it handles edge cases intelligently: 
   
   - It identifies if the page isn’t business-related
   - Reviews the sufficiency of the content
   - Suggests additional actions if necessary
   
   Bonus: It even accommodates non-English websites, returning all output in English.
   
   #### 📊 5. Parse the Output into Structured Fields
   A "Structured Output Parser" ensures the data returned by the AI matches the required schema. This guarantees consistency and makes it possible to cleanly insert the results back into the spreadsheet.
   
   #### ✅ 6. Write Back to Google Sheets
   Once the AI agent completes its analysis, the structured fields are mapped back to the appropriate columns in the original Google Sheet row. The enriched information includes:
   
   - Business Area
   - Offer
   - Value Proposition
   - Business Model
   - ICP
   - Additional Information (including sufficiency review and suggestions)
   
   ---
   
   ### Scraping Workflow: Under the Hood
   
   The AI agent relies on a dedicated scraper workflow to fetch website content. Here's how this secondary workflow works:
   
   - Triggered dynamically by the AI Agent during execution
   - Uses the ScrapingBee API to request homepage content based on the website URL provided
   - Converts the HTML result to Markdown to optimize AI consumption and minimize token usage
   
   ---
   
   ### Why This Workflow Rocks 🎯
   
   Whether you're in marketing, sales, product strategy, or data ops, the ability to generate business insights from raw company websites is invaluable. Here’s what makes this workflow a game-changer:
   
   - Cuts down hours of manual company research
   - Maintains structured, enriched records you can sync into CRMs
   - Scales automatically with new company entries in Google Sheets
   - Easy to extend—connect Slack notifications, CRM updates, or lead forms
   
   ---
   
   ### Key Considerations
   
   Before deploying this in a real-world setting, keep these best practices in mind:
   
   💬 Token Usage:
   OpenAI usage can rack up fast. Monitor usage, especially if analyzing many companies or parsing lengthy pages.
   
   📜 Legal Compliance:
   Web scraping has legal implications. Always review the terms of use of the websites you're scraping and ensure compliance with regional data protection laws.
   
   📦 Data Quality:
   The enriched data depends heavily on what’s publicly available on a company's homepage. For better results, consider expanding the scrape to subpages like “About,” “Products,” or “Pricing.”
   
   🔒 Robust Error Handling:
   Currently, the workflow lacks detailed error handling. Add retry logic and alerting mechanisms to handle downtime or malformed inputs gracefully.
   
   ---
   
   ### Take It Further 🧠
   
   Want to go beyond a spreadsheet? Here are ideas to upgrade this automation:
   
   - Enrich leads directly inside your CRM (e.g., HubSpot, Pipedrive, Salesforce)
   - Trigger the workflow via form submissions and instantly qualify leads
   - Pipe results to Slack or Microsoft Teams for instant visibility
   - Log company profiles to Notion databases or Airtable for deeper visuals and reporting
   
   ---
   
   ### Conclusion
   
   This workflow is a stellar template for anyone looking to automate company research at scale. By leveraging n8n’s automation engine, OpenAI’s intelligence, and ScrapingBee’s data gathering, you can execute smart data enrichment at startup speeds.
   
   Perfect for B2B marketing teams, sales ops, and founders eager to scale without burning hours—or budgets.
   
   Happy automating! ⚙️🤖
   
   ---
   
   Let me know if you'd like me to package this into a downloadable guide or publish-ready blog format.

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.