Website Email Extractor & Contact Scraper — Emails, Phones, Address & 14 Socials

Website Email Extractor & Contact Scraper crawls any website and extracts the full contact profile for every domain: emails, phone numbers, physical address, company name, and 14 social media platforms. Give it a list of URLs and get back a clean dataset ready to import into any CRM or spreadsheet. No subscriptions.

⚡ TRY IT FOR FREE

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What data can Website Email Extractor & Contact Scraper extract?

Data type	Details
📧 Email addresses	Deduplicated per domain, quality-filtered, Cloudflare obfuscation decoded, [at]/(at) obfuscation decoded, optional MX validation
📞 Phone numbers	High-confidence (phones) from tel: links + lower-confidence (possiblePhones) from page text. US and international formats.
🏢 Company name	Extracted from og:site_name and application-name meta tags
📍 Physical address	Extracted from Schema.org PostalAddress JSON-LD or HTML microdata
📄 Page context	pageTitle and pageDescription of the page where each email was found (per-email mode)
💼 LinkedIn	Company and personal profiles
🐦 Twitter / X	Brand and personal handles
📸 Instagram	Business and creator profiles
📘 Facebook	Pages and business profiles
▶️ YouTube	Brand channels
🎵 TikTok	Brand and creator profiles
💻 GitHub	Organization profiles, user profiles, and repositories
💬 WhatsApp	Business numbers, direct links, and WhatsApp Channels
✈️ Telegram	Channels, groups, and user profiles
🎮 Discord	Server invite links
📌 Pinterest	Brand profiles
👻 Snapchat	Public profiles
🧵 Threads	Public profiles
👥 Reddit	Subreddits and user pages

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Why use Website Email Extractor & Contact Scraper?

Most contact scrapers return only emails or lock you into a monthly subscription. This one returns the full contact profile for every domain — including address, company name, and 14 social platforms — and you only pay for what the Actor actually finds.

Feature	This Actor	Email-only scrapers	$10–$20/mo scrapers
Email addresses	✅	✅	✅
Phone numbers	✅	❌	✅
14 social platforms	✅	❌	✅
Company name	✅	❌	❌
Physical address	✅	❌	❌
Page title & description	✅	❌	❌
Email domain validation	✅	❌	Paid add-on
Contact page auto-discovery	✅	❌	❌
Cloudflare + [at] email decode	✅	❌	❌
Pay per event (no subscription)	✅	Some	❌
Per-email and per-domain output	✅	❌	❌

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How to scrape contact information from any website

1. Create a free Apify account using your email.
2. Open Website Email Extractor & Contact Scraper and go to the Input tab.
3. Add your URLs — one domain per entry. Duplicates are handled automatically.
4. Pick an output mode — per-email for CRM import or per-domain to get everything grouped by site.
5. Click Start — the Actor automatically discovers contact pages and crawls up to the configured depth.
6. Download your data as JSON, CSV, Excel, XML, or HTML, or connect via API.

{
  "urls": [
    { "url": "https://company1.com" },
    { "url": "https://company2.com" },
    { "url": "https://company3.com" }
  ],
  "contactPagesOnly": true,
  "outputMode": "per-domain"
}

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How much does it cost to scrape emails from websites?

Website Email Extractor & Contact Scraper uses the pay-per-event (PPE) pricing model — no subscription, no monthly fee. You pay only for what the Actor actually does. Check the Pricing tab for the full event list.

There are two billable events:

Event	Price	When it fires
domain-processed	$0.01	Once per domain, when the first page loads successfully. Does not fire if all pages are blocked (status: "blocked") or the site is a JS-only SPA (status: "js-only").
email-found	$0.004	Once per unique email found. Does not fire if no emails are found.

Estimated cost by batch size (assuming ~2 emails per domain on average):

Domains	Emails found	Estimated cost
10	~20	~$0.18
50	~100	~$0.90
100	~200	~$1.80
500	~1,000	~$9.00
1,000	~2,000	~$18.00

You are not charged for sites that cannot be scraped. Domains that require residential proxies may incur additional platform proxy usage costs.

To control costs, use maxEmailsPerDomain to cap emails per site and maxPagesPerDomain to limit the number of pages crawled per domain.

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⚙️ Input parameters

Parameter	Type	Default	Description
urls	array	required	Website URLs to crawl
outputMode	string	per-email	per-email: one row per email (includes pageTitle + pageDescription) · per-domain: all contacts grouped
maxEmailsPerDomain	integer	0	Global email cap per domain — cost control (0 = unlimited)
maxPagesPerDomain	integer	0	Max pages to crawl per domain — cost control (0 = unlimited)
crawlDepth	integer	2	How deep to follow links (1–5)
contactPagesOnly	boolean	true	Only visit contact-related pages (faster, cheaper)
extractPhones	boolean	true	Extract phone numbers
extractSocials	boolean	true	Extract 14 social profiles
extractAddress	boolean	true	Extract physical address via Schema.org
validateEmails	boolean	false	DNS MX check — filters dead email domains
includeDebugInfo	boolean	false	Add debugInfo array to output for troubleshooting
proxyConfiguration	object	Apify Proxy	Pass null for direct mode (no proxy)

For the full input reference, see the Input tab.

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📊 Output examples

outputMode: "per-email" — one row per email (CRM-ready)

Best for importing directly into HubSpot, Salesforce, Apollo, or any sequencer. Every row includes the email, which page it came from, company name, address, phones, and social profiles.

{
  "sourceUrl": "https://acme.com",
  "domain": "acme.com",
  "companyName": "Acme Corp",
  "address": "123 Main St, San Francisco, CA 94105, US",
  "pageUrl": "https://acme.com/contact",
  "pageTitle": "Contact Us — Acme Corp",
  "pageDescription": "Get in touch with our sales and support teams.",
  "email": "sales@acme.com",
  "phones": ["+1-555-0123"],
  "possiblePhones": [],
  "socials": {
    "linkedin": "https://linkedin.com/company/acme",
    "twitter": "https://x.com/acmecorp",
    "instagram": null,
    "facebook": "https://facebook.com/acmecorp",
    "youtube": null,
    "tiktok": null,
    "github": null,
    "whatsapp": "https://wa.me/15550123",
    "telegram": null,
    "discord": null,
    "pinterest": null,
    "snapchat": null,
    "reddit": null,
    "threads": null
  },
  "scrapedAt": "2026-06-04T10:00:00.000Z"
}

outputMode: "per-domain" — all contacts grouped

One row per domain with all emails, phones, address, company name, and socials found across every page visited.

{
  "sourceUrl": "https://acme.com",
  "domain": "acme.com",
  "companyName": "Acme Corp",
  "address": "123 Main St, San Francisco, CA 94105, US",
  "emails": ["sales@acme.com", "info@acme.com", "support@acme.com"],
  "phones": ["+1-555-0123", "+1-555-9876"],
  "possiblePhones": ["(800) 555-9876"],
  "socials": {
    "linkedin": "https://linkedin.com/company/acme",
    "twitter": "https://x.com/acmecorp",
    "instagram": null,
    "facebook": "https://facebook.com/acmecorp",
    "youtube": null,
    "tiktok": null,
    "github": null,
    "whatsapp": "https://wa.me/15550123",
    "telegram": null,
    "discord": null,
    "pinterest": null,
    "snapchat": null,
    "reddit": null,
    "threads": null
  },
  "pagesScanned": 3,
  "status": "success",
  "scrapedAt": "2026-06-04T10:00:00.000Z"
}

The status field tells you what happened per domain:

Value	Meaning
success	Contacts found, no pages were blocked
partial	Contacts found, but some pages were blocked by bot protection
empty	Crawled OK but no contacts found (contact form only, or genuinely no public email)
blocked	All pages were blocked — no data collected
js-only	Site renders content via JavaScript (SPA/React/Vue) — no static HTML contact data found

You can download the dataset as JSON, CSV, Excel, XML, or HTML from the dataset view.

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🤔 Which output mode should I use?

Use per-email if you are:

• Importing contacts into a CRM (HubSpot, Salesforce, Apollo, Instantly)
• Running an email outreach sequence
• Working with tools that expect one row = one contact

Every row has the email, the page it came from (pageUrl, pageTitle, pageDescription), and all the domain's phones and social profiles attached. If a domain has 3 emails, you get 3 rows — one per contact, ready to import.

Use per-domain if you are:

• Building a spreadsheet or report where the company is the unit
• Enriching an existing account list (you already have the company, you want to fill in missing fields)
• Running market research or competitive analysis across many domains

Every row has all emails as an array, all phones, and all socials grouped under one domain. One domain = one row, no matter how many emails were found.

	per-email	per-domain
Row unit	One email	One domain
CRM import	✅ Direct	❌ Needs processing
Spreadsheet analysis	⚠️ Repeated rows per domain	✅ Clean
pageTitle / pageDescription	✅ Yes	❌ No
Multiple emails per domain	Multiple rows	Single row, array

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💡 Use cases for website contact scraping

B2B sales prospecting — Turn a list of target domains into a contact file ready to import, with email, phone, LinkedIn, and company address in every row.

Agency lead generation — Find contacts at target companies by category and city, at scale.

CRM enrichment — Fill missing email, phone, address, and social fields for existing accounts in bulk.

Recruiting — Collect contact info from company career and team pages.

Partnership outreach — Extract contacts from potential partners, resellers, or integration targets.

Competitor research — Map the social media presence and contact points of competitors.

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🔗 Integrations

You can integrate Website Email Extractor & Contact Scraper with almost any cloud service or web app. The Apify platform has built-in integrations, a full REST API, scheduling, and webhook support.

• Make / Zapier — trigger workflows when new contacts are found
• Google Sheets — direct dataset export
• HubSpot / Salesforce / Apollo — import CSV or use the API
• Webhooks — get notified when a run completes
• Apify API — apify-client for Node.js and Python
• MCP Server — use this Actor directly inside Claude or any MCP-compatible client

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❓ Frequently asked questions

Does Website Email Extractor & Contact Scraper work on all websites?

It works on most contact, about, and team pages since these are almost always static HTML. For sites that require JavaScript to render content, the Actor detects this and marks the domain as status: "js-only" in the output.

Why didn't it find emails on a specific site?

The most common causes are: emails only visible after a form submission, domain blocking datacenter IPs, or a JavaScript-rendered site. Check the status field in per-domain mode — blocked means IPs were rejected, js-only means the site requires a browser. Enable includeDebugInfo: true in the input to get detailed reason codes in the output.

What is possiblePhones?

possiblePhones contains phone numbers extracted from visible page text via regex — lower confidence than phones, which come from tel: href links. Numbers in possiblePhones may include false positives like order IDs or dates. Use phones for outreach and possiblePhones as a fallback.

How does address extraction work?

The Actor looks for Schema.org PostalAddress data in JSON-LD blocks (the structured data search engines use). If not found, it falls back to HTML microdata (itemprop="streetAddress"). Sites that don't publish structured data will return address: null. You can disable extraction with extractAddress: false.

How do I extract emails from multiple websites at once?

Add all your URLs to the urls array. Each domain is processed independently and results are deduplicated automatically.

Can I use Website Email Extractor & Contact Scraper with the Apify API?

Yes. The Apify API lets you run the Actor, retrieve datasets, schedule runs, and set up webhooks. Use the apify-client package for Node.js or Python. See the API tab for the full reference.

Is it legal to scrape contact information from websites?

Scraping publicly available contact information is generally legal, but you should check compliance with GDPR, CAN-SPAM, and the terms of service of each website before using the data for outreach.

What does email validation do?

When validateEmails: true, each email domain is checked for a valid MX record via DNS. Domains without one are discarded, which filters out dead domains and placeholder addresses. This adds ~100ms per unique email domain.

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Your feedback

If you found a bug or have a feature request, please create an issue in the Issues tab.

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