How to Automate B2B Lead Generation & Extract Contact Details with Python

wojtek — Tue, 20 Oct 2026 18:24:55 +0000

Finding fresh B2B leads and gathering contact details (emails, phone numbers, social media links) is often one of the most time-consuming tasks for sales, marketing, and recruitment teams.

In this guide, I’ll show you how to automate contact extraction from business websites using the Lead Generator & Contact Extractor Actor on Apify.

🎯 What Does the Lead Generator Do?

Instead of manually browsing websites to copy-paste email addresses and phone numbers, this tool automatically scans target pages and extracts:

✉️ Email Addresses (filtered and cleaned)
📞 Phone Numbers
🔗 Social Media Profiles (LinkedIn, Twitter/X, Facebook, Instagram)
🌐 Website Metadata & Contact Page Links

⚡ How to Extract Leads in 3 Easy Steps

Open the Actor: Go to Apify Console and find the Lead Generator & Contact Extractor.
Provide Start URLs: Enter the URLs of the websites or company directories you want to scrape.
Run & Export: Click Start. Download your list of qualified leads directly as CSV, Excel, or JSON.

📤 Sample JSON Output

Here is an example of the structured contact data you receive:


json
[
  {
    "url": "https://example-company.com
    "emails": ["contact@example-company.com", "sales@example-company.com"],
    "phones": ["+48 123 456 789"],
    "social_links": {
      "linkedin": "https://linkedin.com/company/example
      "twitter": "https://x.com/example"
    }
  }
]

How to Extract IT Job Listings & Salary Data from No Fluff Jobs using Python

wojtek — Tue, 20 Oct 2026 18:06:33 +0000

Analyzing IT market trends, benchmarking salary ranges, or tracking in-demand technology stacks often requires clean and structured datasets.

In this quick tutorial, I'll show you how to automatically extract job details and salary brackets directly from No Fluff Jobs without writing complex scraping scripts or managing proxies yourself.

💡 Why No Fluff Jobs?

Unlike standard job boards, No Fluff Jobs requires companies to list transparent salary ranges (both B2B and Employment Contracts) along with explicit tech stack requirements. This makes it an invaluable resource for:

💼 Tech Recruiters: Benchmarking market compensation for open roles.
👨‍💻 Developers: Finding offers that match preferred tech stacks and salary expectations.
📊 Data Analysts: Tracking demand for programming languages and tools over time.

⚡ How to Extract the Data in 3 Easy Steps

We will use the No Fluff Jobs Python Scraper hosted on Apify.

Open the Actor: Go to Apify Console and search for No Fluff Jobs Python Scraper.
Set Target URL: Paste the URL of the search results or category you want to analyze (e.g. https://nofluffjobs.com/pl/Python).
Run & Export: Click Start. In a few seconds, you can download your structured dataset as CSV, JSON, or Excel.

📤 Sample JSON Output

Here is an example of the clean structured data returned by the scraper:


json
[
  {
    "title": "Senior Python Developer",
    "company": "Tech Company",
    "salary_from": 18000,
    "salary_to": 24000,
    "currency": "PLN",
    "type": "B2B",
    "location": "Warsaw / Remote",
    "technology": ["Python", "Django", "Docker", "PostgreSQL"]
  }
]

DEV Community: wojtek

How to Automate B2B Lead Generation & Extract Contact Details with Python

🎯 What Does the Lead Generator Do?

⚡ How to Extract Leads in 3 Easy Steps

📤 Sample JSON Output

How to Extract IT Job Listings & Salary Data from No Fluff Jobs using Python

💡 Why No Fluff Jobs?

⚡ How to Extract the Data in 3 Easy Steps

📤 Sample JSON Output