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Website Contact and Email Finder -- Extract Emails, Phone Numbers, and Social Links from Any Website

One agency ran this on 2,400 domains overnight and built a $48K cold-outreach list by Tuesday morning. Crawls company sites and pulls email, phone, physical address, social links, plus auto-detects 25+ tech stack platforms (React, Shopify, HubSpot, Webflow, WordPress, etc.). Drop in domains, get back enriched contact records ready for your CRM.

⏱️ 86% success rate, ~$0.0030/result. Cheaper than Hunter.io + Apollo combos for batch domain-list enrichment, and the tech-stack detection is free on top.

⭐️ Solo developer here, competing with bigger publishers on a feature set that's actually better. A 30-second review is the only thing that lifts ranking. Even a 1-line "worked for X" helps massively.

👁 Sample output: emails, phones, social links and contact pages extracted per domain

Crawl any website to extract publicly listed contact information. The scraper intelligently prioritizes contact pages, about pages, team pages, and footers to find email addresses, phone numbers, physical addresses, and social media profiles. It also detects the site's technology stack, identifying 25+ platforms and frameworks including WordPress, Shopify, React, HubSpot, and more.

Give it a list of domains and get back a clean, consolidated contact record for each one -- ready for CRM import, outreach campaigns, or competitive research.

What data can you extract?

Email verification (built in, free)

Every email this actor finds is verified before it reaches your list — no Hunter.io or ZeroBounce bill on top. Each address is tagged so you know what you can send to:

• valid — passes syntax, is not a disposable/throwaway domain, and the domain has live MX (mail) records. Safe to send.
• risky — deliverable but lower confidence: a role/department address (info@, sales@) or a domain that accepts mail via an implicit A record. Usable, your call.
• invalid — broken syntax, a disposable domain, or a domain that cannot receive mail at all. Drop these and protect your sender reputation.

You get three fields: emails (all of them, best-first), validEmails (just the clean, send-ready ones), and emailsVerified (the full breakdown with a status, a reason, the role-based flag and the MX host per address). Verification runs by default — set verifyEmails to false to skip it.

The checks are syntax (RFC), a 6,900-domain disposable blocklist, role-based detection, and live MX lookups (cached per domain so a 2,000-domain run stays fast). No mailbox is ever contacted, so nothing touches the prospect.

The verification engine is open-source — same logic, zero dependencies: mxverify on npm (source).

Use cases

• Lead generation and outbound sales -- Build verified email lists from company websites. Feed the results directly into your email outreach tools. Filter out generic addresses (info@, support@) to focus on actionable contacts.
• Sales prospecting and pre-call research -- Before reaching out to a prospect, pull their company's contact details, social profiles, and tech stack in one automated step. Know what tools they already use to tailor your pitch.
• Competitive technology analysis -- Discover what platforms and tools your competitors use. Identify which companies in a market run on Shopify versus WooCommerce, use HubSpot versus Intercom, or deploy React versus Angular.
• Business intelligence and data enrichment -- Enrich your existing lead database with phone numbers, social links, and technology data. Pair with the Google Maps Business Scraper to go from a search query to a fully enriched contact list.
• Partnership and PR outreach -- Gather contact details for potential partners, media outlets, or influencers at scale. The smart crawler ensures you find the right contact page even on large, complex websites.

Input parameters

Example output

{
"domain":"stripe.com",
"companyName":"Stripe",
"emails":[
"press@stripe.com",
"support@stripe.com"
],
"phones":[
"+1 (888) 926-2289"
],
"addresses":[],
"socialLinks":{
"linkedin":"https://www.linkedin.com/company/stripe",
"twitter":"https://twitter.com/stripe",
"facebook":"https://www.facebook.com/StripeHQ",
"instagram":"https://www.instagram.com/stripe",
"youtube":"https://www.youtube.com/c/stripe"
},
"contactPageUrl":"https://stripe.com/contact",
"techStack":[
"Cloudflare",
"Google Analytics",
"Next.js",
"React",
"Stripe"
],
"pagesCrawled":10,
"scrapedAt":"2026-03-01T12:00:00.000Z"
}

How much does it cost?

This actor uses a pay-per-result pricing model:

• $0.003 per domain ($3.00 per 1,000 domains)
• Crawling 100 websites costs approximately $0.30
• Crawling 1,000 websites costs approximately $3.00
• Crawling 10,000 websites costs approximately $30.00

There are no monthly fees or commitments. You only pay for the data you extract.

Tips and tricks

• 5-10 pages per domain is the sweet spot for most use cases. The scraper prioritizes high-value pages (contact, about, team, imprint, privacy) first. Increasing beyond 10 pages rarely yields significant additional contact data but does increase run time and cost.
• Disable generic emails to improve lead quality. If you are building a sales prospect list, set includeGenericEmails to false. This filters out addresses like info@, support@, and noreply@ so your list only contains emails more likely to reach a real person or specific department.
• Combine with the Google Maps Business Scraper for a complete prospecting pipeline. First, search Google Maps for businesses in your target industry and location. Then, feed the extracted website URLs into this scraper to get emails, phone numbers, and social profiles for each business.
• The technology stack data is valuable for sales targeting. If you sell a product that competes with or integrates with specific platforms, use the techStack field to segment your prospects. For example, filter for companies using Shopify if you sell e-commerce apps, or target companies using Google Analytics if you offer an analytics alternative.

Using AI to write your outreach / posts / replies?

If you use this scraped data to inform AI-generated cold emails, LinkedIn posts, Reddit replies, etc., modern detectors are catching on. Em-dashes, "delve", parallel bullets, and 9 other patterns get accounts flagged or callout-replied. Built aitells.vercel.app after my own reddit account got 2 "all AI generated" callouts in one day. Free detector + $19 lifetime rewriter that matches your voice.

Found this useful?

If this scraper saved you time, please consider leaving a quick review on the Reviews tab above. Reviews help small developers like me get visibility on the Apify Store, and your feedback is genuinely valuable for improving the actor. Thanks!

Related scrapers

• Google Maps Business Scraper -- Discover businesses by industry and location on Google Maps, then use this contact finder to enrich each result with email and social data.
• Indeed Jobs Scraper -- Identify companies that are actively hiring, then use this contact finder to get their direct contact information for sales outreach.

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Open source family: github.com/Perufitlife