Targeted B2B Outreach → Automated Lead Precision System

A custom-built workflow that identifies high-fit companies, enriches contacts, and generates tailored outreach at scale.

This system automates the entire prospecting pipeline—from scraping job listings to sending personalized emails—resulting in significantly higher response rates.

Project Summary

Automated scraping of job listings to detect companies offering employee perks

Filtering logic to detect relevant keywords in job descriptions

Exported lead list enriched with verified HR contacts

Tailored outreach emails automatically generated per company

Fully automated end-to-end workflow using Python, Apollo, and n8n

Messages customized to each company's context

Significant improvement in first-touch reply rates

System Architecture

Job Listing Scraper

Identify relevant companies

Keyword Matching

Extract meaningful signals

Lead Enrichment in Apollo

Append HR contacts

Automated Personalised Outreach

Generate & send tailored emails

Key Challenges & Solutions

Broad Targeting Didn't Work

Company-size and industry filters produced low-quality outreach.

Solution:
Scrape job ads to find companies actively promoting employee benefits.

Generic Messaging Underperformed

Mass emails created little relevance for recipients.

Solution:
Automatically generate tailored messages based on each company's job ad.

Manual Prospecting Was Slow

Researching companies individually was not scalable.

Solution:
Automate scraping, enrichment, and email generation using Python + n8n + Apollo.

Technical Implementation

1. Scraping Job Posts

# Python script querying Arbeitnow API
import requests
import pandas as pd
import re

KEYWORDS = [
    "urban sports", "wellpass", "qualitrain",
    "gympass", "mental health support", "employee wellbeing",
    "betriebliche gesundheitsförderung", "health budget"
]

API_URL = "https://arbeitnow.com/api/job-board-api"

def count_keywords(text, keywords):
    text = text.lower() if text else ""
    return {kw: len(re.findall(re.escape(kw), text)) for kw in keywords}

# Fetch jobs and filter by keyword matches
resp = requests.get(API_URL)
jobs = resp.json().get("data", [])

# Export matched companies to CSV
df.to_csv("keyword_matches.csv", index=False)

2. Lead Enrichment

# Import CSV into Apollo
# Append verified HR contacts
# Export enriched lead list

apollo.import_csv("keyword_matches.csv")
apollo.enrich_contacts(job_titles=["HR Manager", "People Ops"])
enriched_leads = apollo.export()

3. Personalised Email Generation & Delivery

// n8n workflow: loop through each lead
for (const lead of enrichedLeads) {
  // Send job-ad context to ChatGPT for email drafting
  const email = await chatgpt.generateEmail({
    company: lead.company,
    jobContext: lead.matchedKeywords,
    contactName: lead.hrContact,
  });

  // Push final email to Apollo via API
  await apollo.pushEmail(lead.id, email);
}

// Apollo sends emails automatically on schedule

First-touch response rate (up from 1%)

100%

Automated workflow

Manual research required

10x

Higher message relevance

Want to build smarter outreach workflows?

Let's design an automated prospecting system that finds high-fit leads and generates personalized outreach at scale.

Let's connect →