🎣 Generate personalized cold email icebreakers with Apify, Baserow and OpenRouter GPT-4.1

⚑ 17 views · 🎣 Lead Generation & Enrichment

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Description

This workflow automatically researches a lead’s website, understands what the business actually does, and generates a highly personalized cold outreach subject line and icebreaker using AI.

Instead of guessing or relying on shallow placeholders, it scrapes real website content, summarizes it intelligently, and feeds that context into an LLM to produce outreach that feels relevant and human.

If a website is broken or unreachable, the workflow safely flags it so you can identify faulty leads early.

Sticky Notes

How It Works

1. Fetch Leads from Database

The workflow starts by pulling leads from Baserow, including company name and website URL.

2. Visit and Scrape the Website

The lead’s website is fetched and converted into HTML. If the site fails to load or respond, the workflow records no content and continues without breaking.

All links are extracted from the page, then filtered so only links belonging to the same website are kept.

4. Scrape Multiple Pages

The workflow scrapes up to five pages in total, including the main website page and up to four internal pages. This provides enough context while avoiding unnecessary data.

5. Convert to Markdown and Trim Content

Each page is converted to markdown to reduce token usage and trimmed to a maximum of 5,000 characters to control LLM costs.

6. Aggregate Website Content

All processed markdown content is combined into a single structured input.

7. Generate a Business Overview

An LLM analyzes the aggregated content and generates a concise overview of the company and its offering.

8. Generate Subject Line and Icebreaker

A second LLM uses the company name, lead name where available, and the generated business overview to create a highly personalized subject line and icebreaker for outreach.

9. Update the Database

The final outputs are written back to the database, keeping each lead enriched and ready for outreach.

Use Cases

Requirements

Why This Template Is Useful

Most outreach fails because it is generic. This workflow solves that by grounding every message in real website content while staying fast, efficient, and cost-conscious.

πŸ”— Nodes Used

Airtable, HTTP Request, Baserow, Markdown, Filter, Basic LLM Chain

πŸ“₯ Import

Download workflow.json and import into n8n: Workflow menu β†’ Import from File

πŸ“– Importing guide Β· πŸ”‘ Credential setup