This article provides a complete, practical walkthrough of the Splitout Limit 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:**  
   Streamlining Sales Prospecting: How to Automatically Find LinkedIn Profiles and Generate Personalized Outreach Using n8n, Bright Data, and GPT-4o-mini
   
   **Meta Description:**  
   Discover how this n8n workflow integrates Bright Data and OpenAI's GPT-4o-mini to automate LinkedIn profile discovery and personalized follow-up email generation for sales prospecting.
   
   **Keywords:**  
   n8n, LinkedIn automation, sales prospecting automation, Bright Data, GPT-4o-mini, OpenAI, web scraping, automated outreach, sales intelligence, lead generation, LinkedIn profile extractor, AI workflow, B2B sales tech
   
   ---
   
   ## Automating LinkedIn Prospecting with n8n, Bright Data, and GPT-4o-mini
   
   Prospecting for the right leads on LinkedIn can be incredibly time-consuming—especially when trying to discover the correct profile for someone based on limited data like name and company. Now imagine you could automate the entire process: receive a name and company via a form, fetch LinkedIn results, extract relevant data to confirm the prospect's identity, research the company, and then send a fully tailored follow-up email with proper HTML styling, all without lifting a finger.
   
   That’s exactly what this custom-built sales automation workflow does—leveraging the visual workflow automation tool n8n, the data extraction powerhouse Bright Data, and OpenAI’s GPT-4o-mini language model.
   
   Let’s walk through how this smart, end-to-end solution works and why it can be a game-changer for sales teams, recruiters, and marketers looking to streamline their connection strategy.
   
   ---
   
   ## Step-by-Step Breakdown of the Workflow
   
   ### Step 1: Collect Prospect Data via a Form
   
   The workflow begins with a simple n8n form trigger labeled "Sales Prospecting." It asks the user to input:
   - Person’s full name
   - Person’s company  
   
   This interaction kicks off the automation and feeds data into the next steps.
   
   ### Step 2: Formulate a Google Search to Find a LinkedIn Profile
   
   Using the form data, a dynamic search URL is constructed:
   ```
   site:linkedin.com/in [Full name] [Company name]
   ```
   This search string is encoded and becomes the target of a Bright Data web scraping request.
   
   ### Step 3: Scrape Google using Bright Data
   
   Bright Data’s “web_unlocker1” proxy zone is employed to fetch the result of the Google search without being blocked by anti-bot mechanisms. The output is returned in JSON format for further parsing.
   
   ### Step 4: Extract HTML and Process with GPT-4o-mini
   
   The raw HTML from the search results is parsed via n8n's HTML extract module. Extracted content is passed to GPT-4o-mini (via LangChain integration) with instructions to:
   - Parse all LinkedIn profile URLs
   - Match profiles with provided name and company
   - Identify potential matches and key information (title, position, etc.)
   
   ### Step 5: Isolate the Best-Matching LinkedIn Profile
   
   Once GPT-4o-mini returns structured results, the workflow filters them to find profiles marked as a “match.” Only one result is allowed to proceed—the most confident match.
   
   If no match is found, the workflow branches to inform the user automatically through a fallback message.
   
   ### Step 6: Perform Company Research
   
   Simultaneously with LinkedIn scraping, the workflow creates another Google search for the company name alone. Using Bright Data again, it fetches company-related content, which is parsed and interpreted by GPT-4o-mini to generate foundational context around the company.
   
   ### Step 7: Generate a Personalized Outreach Strategy
   
   With both the user’s LinkedIn data and the company overview parsed, the workflow calls GPT-4o-mini one final time. This prompt instructs the model to:
   - Interpret the prospect as a buyer persona
   - Suggest contact strategies
   - Generate a customized follow-up plan
   - Output as styled raw HTML using Tailwind CSS for aesthetic formatting
   
   ### Step 8: Send the Outreach Email
   
   The final output is sent to the form submitter’s (or designated) email using n8n's native SMTP node. The email contains a polished, professional report with advice on how to approach the lead based on real-time data.
   
   ---
   
   ## Why This Workflow Matters
   
   This automation helps solve a fundamental inefficiency in sales: finding accurate lead data and crafting personalized messages. By integrating multiple third-party services in a seamless n8n workflow, sales teams can:
   
   - Save hours of manual LinkedIn and Google searching  
   - Increase the accuracy of their outreach  
   - Scale personalized engagement  
   - Build competitive advantages in outbound campaigns
   
   ---
   
   ## Third-Party APIs and Tools Used
   
   - **Bright Data (formerly Luminati):**  
     Used for scraping LinkedIn and company-related Google search content without bot roadblocks.
     
   - **OpenAI (GPT-4o-mini):**  
     NLP model used for parsing search results, evaluating matching profiles, analyzing buyers, and generating follow-up content.
     
   - **Google Search (indirectly via Bright Data):**  
     Source of both LinkedIn and company-related search results.
     
   - **SMTP Email Service:**  
     Sends the final outreach strategy to the designated recipient.
   
   ---
   
   ## Final Thoughts
   
   Automating outreach doesn’t have to mean sacrificing personalization. With the right mix of web scraping, AI, and modular tools like n8n, sales teams can build scalable yet highly tailored workflows like this one. Whether you're conducting B2B outreach, recruiting, or doing competitive analysis, this intelligent automation pattern can be a template for operational excellence.
   
   Ready to automate your lead generation strategy? Let your CRM talk to AI. Let n8n do the heavy lifting.
   
   --- 
   
   Want help setting something like this up? Head over to n8n.io or reach out to a certified automation expert!

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.