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Website Data Extractor

Pull structured data from any website — no code, no setup required

Muhammad Bilal
Muhammad Bilal Virk
2 min read
Data extractor
Paste a page's HTML source (Ctrl+U on any site) — extraction runs entirely in your browser, so nothing is uploaded and there are no CORS limits.
Paste HTML above to extract contacts, links and structure.

Extract structured data from any website without code. Enter a URL and specify what you want — company name, contact email, pricing, product descriptions, or any other visible data — and get clean, structured output ready to paste into a spreadsheet or CRM.

What This Tool Extracts

Business Information

  • Company name, description, and tagline
  • Contact email addresses and phone numbers
  • Physical address and location
  • Social media profile links

Commercial Data

  • Pricing tables and plan names
  • Product names, descriptions, and SKUs
  • Team members and their titles
  • Job postings and requirements

SEO & Technical Data

  • Page title and meta description
  • H1 and heading structure
  • Internal and external link counts
  • Technology stack signals

Use Cases

  • Prospect research — extract company info before a sales call
  • Competitor analysis — monitor competitor pricing and product changes (pair this with the Competitor Automation Gap Analyzer to see their tech stack at the same time)
  • Lead enrichment — fill in missing CRM fields from a prospect's website
  • Market research — collect data from multiple sources for a report

Web scraping is governed by robots.txt conventions, terms of service, and (in some jurisdictions) computer misuse laws. Always:

  1. Check the site's robots.txt before scraping
  2. Review the terms of service for "automated access" restrictions
  3. Rate-limit your requests to avoid overloading the server
  4. Never scrape personal data without a lawful basis under GDPR

Building a Scraping Pipeline

For systematic, recurring data extraction — competitor monitoring, lead enrichment, market tracking — I can build a robust scraping pipeline with scheduling, error handling, and data normalisation. This is the same kind of pipeline behind the API automation work I write about on the blog. Book a consultation.

Muhammad Bilal
Muhammad Bilal Virk
AI automation engineer — building agents, workflows, and RPA that remove repetitive work.
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