Website Email & Contact Scraper — Find Emails, Phones, Socials (CSV)

Skip ZoomInfo's $15K/year subscription. Feed any list of website URLs to this actor and get clean CSV/JSON of public emails, phone numbers, and social profile links — pulled from each site's contact page. Built for cold-email teams, lead-gen agencies, and bulk-prospecting workflows that need real contact data without per-credit pricing or 50% bounce rates.

Why this scraper, not Hunter.io or Apollo? Hunter.io charges $49/mo for 2,000 lookups by domain — and only finds emails, not phones or socials. Apollo's per-credit pricing burns through monthly limits in two weeks of multi-vertical prospecting. This actor takes any list of website URLs (1 or 10,000), crawls each site's pages, and returns every public email, phone, and social link found — at $0.004/row, no monthly minimum, no credit system.

Pricing: $0.004 per page-row in full mode or $0.004 per unique email in emails_only mode. Example: a 1,000-domain crawl with avg 5 pages each = ~5,000 rows = $20. Compare to Hunter.io's $49/mo for 2,000 lookups, ZoomInfo's $1,250/mo, Apollo's $49+/mo.

Who is this scraper for?

• Cold-email agencies replacing ZoomInfo — Canceled a $15K/year ZoomInfo subscription and built your own pipeline? Feed the domain list to this actor and get fresh, live-extracted contacts at a fraction of the cost (r/Entrepreneur).
• Sales reps doing manual contact-page lookups — "open website → scroll → contact page → copy email → repeat 300 times." This actor automates that exact loop across any number of domains (r/SaaS).
• GTM engineers building n8n + email-finder pipelines — Wire this actor into an n8n or Make.com workflow after a Google Maps or LinkedIn scrape to hydrate each result with direct-site contact data (r/automation).
• microSaaS founders building lead-gen products on Apify — Build a full lead gen pipeline across 4 platforms (Google Maps, Yellow Pages, BBB, email finder) — all on Apify (r/microsaas).
• Sourcing and recruiting teams enriching CRM lists — Bulk-crawl company websites to surface direct email formats, LinkedIn handles, and Twitter/X profiles for candidate outreach.

Why this Actor

• HTTP-first crawling (crawlerType: "http") for cheaper runs
• optional browser mode (crawlerType: "browser") for JS-heavy pages
• shallow crawling with maxDepth and maxPages to keep spend predictable
• include/exclude URL globs for crawl control

Input

Core fields:

• startUrls (required)
• mode (full | emails_only)
• crawlerType (http | browser)
• maxPages, maxDepth
• sameDomainOnly, includeSubdomains
• includeUrlGlobs, excludeUrlGlobs
• extractEmails, extractPhones, extractSocial, extractImages, extractFiles, extractLinks

See .actor/input_schema.json for the full schema.

Output examples

Full mode row

{
  "recordType": "page",
  "seedUrl": "https://example.com/",
  "pageUrl": "https://example.com/contact",
  "depth": 1,
  "statusCode": 200,
  "title": "Contact",
  "emails": ["hello@example.com"],
  "phoneNumbers": ["+12025550123"],
  "socialLinks": {
    "linkedin": [],
    "x": [],
    "facebook": [],
    "instagram": [],
    "youtube": [],
    "tiktok": [],
    "threads": [],
    "telegram": [],
    "whatsapp": [],
    "discord": [],
    "pinterest": [],
    "reddit": [],
    "github": []
  },
  "internalLinks": [],
  "externalLinks": [],
  "images": [],
  "files": [],
  "counts": {
    "emails": 1,
    "phoneNumbers": 1,
    "socialLinks": 0,
    "internalLinks": 0,
    "externalLinks": 0,
    "images": 0,
    "files": 0
  }
}

Emails-only row

{
  "recordType": "email",
  "seedUrl": "https://example.com/",
  "url": "https://example.com/contact",
  "email": "hello@example.com",
  "depth": 1,
  "statusCode": 200
}

### Seed summary row

```json
{
  "recordType": "seed_summary",
  "seedUrl": "https://example.com/",
  "mode": "full",
  "crawlerType": "http",
  "pagesCrawled": 14,
  "failedRequests": 1,
  "uniqueEmails": 6,
  "statusCodeHistogram": {
    "200": 13,
    "404": 1
  },
  "totals": {
    "emails": 9,
    "phoneNumbers": 4,
    "socialLinks": 11,
    "internalLinks": 173,
    "externalLinks": 42,
    "images": 88,
    "files": 7
  }
}

Run summary row

{
  "recordType": "run_summary",
  "mode": "full",
  "crawlerType": "http",
  "seedsTotal": 3,
  "pagesCrawled": 39,
  "failedRequests": 2,
  "uniqueEmails": 15,
  "totals": {
    "emails": 24,
    "phoneNumbers": 11,
    "socialLinks": 29,
    "internalLinks": 513,
    "externalLinks": 126,
    "images": 244,
    "files": 19
  },
  "durationMs": 5841
}

## Integrations & Code Examples

### bash (curl)

```bash
curl -X POST \
  "https://api.apify.com/v2/acts/whoareyouanas~website-link-scraper/run-sync-get-dataset-items" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls":[{"url":"https://example.com"},{"url":"https://acme.com"},{"url":"https://startup.io"}],"mode":"emails_only","maxPages":5}'

Python SDK

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("whoareyouanas/website-link-scraper").call(run_input={
    "startUrls": [{"url": "https://example.com"}],
    "mode": "emails_only",
    "maxPages": 5,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item.get("email"))

Node.js SDK

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('whoareyouanas/website-link-scraper').call({
    startUrls: [{ url: 'https://example.com' }],
    mode: 'emails_only',
    maxPages: 5,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.map(i => i.email));

n8n / Make.com pipeline recipe

4-step lead-gen pipeline:

1. Google Maps scraper → extracts business website URLs
2. This actor (website-link-scraper) → crawls each site for emails, phones, socials
3. MillionVerifier or NeverBounce API → validates emails before sending
4. Instantly / Smartlead → pushes verified contacts to cold-email campaign

Use the Apify node in n8n and connect the output directly to an email-verification step. Full integration docs: Apify integrations.

Local development

npm install
npm run build
npm run dev
npm test

Frequently Asked Questions (FAQ)

Does this work on JS-heavy sites (React, Vue, Next.js)? Yes. Set crawlerType: "browser" to switch from the default HTTP crawler to a full Chromium browser. HTTP mode is faster and cheaper; browser mode handles sites that load content via client-side JavaScript.

How fast is bulk extraction? HTTP mode runs 25 concurrent requests by default. On a 1,000-domain list with avg 3 pages each, expect ~5 minutes per run at default settings.

Will sites block me? The HTTP-first crawler sends standard User-Agent headers and is fast enough to stay under most rate limits. For sites that enforce Cloudflare or similar bot protection, use Apify proxy (proxyConfiguration: { useApifyProxy: true }) or switch to browser mode.

Does this validate emails? No — extraction only. The actor finds any string matching an email pattern on each page; it does not ping SMTP or run deliverability checks. Pair with MillionVerifier or NeverBounce in your pipeline to cut bounce rates before sending.

Is this CAN-SPAM / GDPR compliant? Extracting publicly available contact information from a website is generally legal in most jurisdictions. Sending marketing email to extracted addresses is your responsibility — follow CAN-SPAM (US) and GDPR (EU) requirements.

How is this different from ZoomInfo / Apollo / Hunter.io? ZoomInfo and Apollo are pre-built databases — they're expensive ($49–$1,250+/mo) and reflect data that was last crawled months ago. Hunter.io is per-domain-lookup and email-only. This actor crawls the live site right now and returns whatever public contact information is on the page — phones, socials, and emails — at $0.004/row with no monthly minimum.

Can I exclude specific URL patterns? Yes. Use excludeUrlGlobs: ["**/blog/**", "**/news/**"] to skip sections of the site you don't need.

Can I scrape only contact pages? Yes. Use includeUrlGlobs: ["**/contact**", "**/about**", "**/team**"] to restrict crawling to those paths. This dramatically reduces cost on large sites.

Notes

• Invalid start URLs are skipped with a warning.
• 4xx/5xx pages may produce no data but do not crash the whole run.
• Use sameDomainOnly: true for cost-efficient, controlled crawls.

Was this scraper useful?

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