Structured Business Data Extractor

📊 Structured Business Data Extractor

🚀 Extract verified business emails and phone numbers from websites in seconds — clean, structured, and ready for CRM.

Extract clean, structured business data (company name, emails, phone numbers, and metadata) from public websites for research, CRM enrichment, and company profiling.

This Actor converts unstructured website content into machine-readable records designed for automation workflows, analytics, and lead enrichment pipelines.

No outreach. No logins. Public websites only.

🚀 What This Actor Does

Given one or more public website URLs, this Actor:

Crawls homepage and relevant internal pages (contact, about, support) Extracts validated email addresses and phone numbers Detects the company or organization name Tracks pages that were scanned Outputs clean, structured records to an Apify dataset

To ensure cost efficiency and reliability, results are only saved when meaningful contact data is found.

👥 Who This Actor Is For

This Actor is designed for:

CRM & RevOps teams enriching company records Researchers and analysts building structured datasets Founders and operators profiling businesses Developers building lead generation and automation pipelines ✅ Key Features

🟢 Python-based (lightweight, fast, cost-efficient) 🟢 Smart internal page discovery (contact, about, support pages) 🟢 Strict email and phone validation 🟢 Placeholder and low-quality data filtering 🟢 Cost-aware extraction (no unnecessary dataset writes) 🟢 Clean, structured, automation-ready output 🟢 Reliable and production-ready

📥 Input Required

Start URLs List of public website URLs to scan.

Optional

Max pages – Maximum number of internal pages to scan per site (default: 5)

Example Input { "start_urls": [ { "url": "https://www.iana.org/contact" } ], "max_pages": 5 } 📤 Output

The Actor writes results to the default dataset:

Example Output { "company_name": "IANA", "website": "https://www.iana.org", "emails": ["iana@iana.org"], "email_status": "found", "phones": ["+14242542545"], "phone_status": "found", "pages_checked": [ "https://www.iana.org", "https://www.iana.org/contact" ], "industry": null, "linkedin_company": null, "scrape_status": "completed", "scraped_at": "2026-02-22T03:53:38Z" } 📊 Output Fields Field Description company_name Detected company name website Website processed emails Extracted email addresses email_status found / not_found phones Normalized phone numbers phone_status found / not_found pages_checked Pages scanned during extraction industry Reserved for enrichment linkedin_company Reserved for enrichment scrape_status Run status scraped_at UTC timestamp 🧠 How It Works Loads the homepage Discovers relevant internal pages Scans visible content Extracts emails and phones using robust patterns Applies validation and filtering Normalizes formats Saves structured output

The workflow is designed for transparency, data quality, and long-term reliability.

⚠️ Limitations & Notes Works only on publicly accessible websites Does not scrape social media platforms No CAPTCHA bypassing No login-based scraping Accuracy depends on website structure

This Actor prioritizes stability, data quality, and cost efficiency.

🛡️ Legal & Ethical Use

You are responsible for complying with:

Website terms of service Local data protection laws (e.g., GDPR, CCPA) Ethical data usage standards

Use this Actor only for legitimate business purposes.

⭐ Recommended Use Cases CRM enrichment Business research Lead validation Market research Company profiling Data pipeline enrichment 🔧 Customization

This Actor can be extended for:

Deeper multi-page crawling API / enrichment integrations CSV / Excel pipelines Custom validation rules Monitoring and alerting ✅ Status

Production-ready · Cost-efficient · Store-safe · Reliability-focused

👤 Author

Leoncio U. Coronado Jr Data Automation & Web Scraping Engineer Apify Verified Actor Developer