Download pre-extracted email address database from millions of websites worldwide. Get verified business emails, contact lists, and lead generation data instantly.
Website Email Extractor Database contains millions of verified email addresses extracted from websites across all industries and countries. Perfect for email marketing, lead generation, B2B sales, and business outreach campaigns.
- 100+ Million Email Addresses: Extracted from 50+ million websites
- 200+ Countries: Global email address coverage
- 50+ Industries: Technology, Healthcare, Finance, Retail, and more
- Daily Updates: 500,000+ new emails added every day
- 95%+ Verified: Email validation and deliverability checks
- Role-Based & Personal: Both generic and individual emails
{
"domain": "example.com",
"emails": {
"general": [
"info@example.com",
"contact@example.com",
"hello@example.com"
],
"sales": [
"sales@example.com",
"enquiry@example.com"
],
"support": [
"support@example.com",
"help@example.com"
],
"executives": [
"ceo@example.com",
"john.doe@example.com"
],
"departments": [
"marketing@example.com",
"hr@example.com",
"finance@example.com"
]
},
"verification": {
"syntax_valid": true,
"domain_exists": true,
"mx_records": true,
"smtp_check": true,
"deliverable": true,
"last_verified": "2024-01-15"
}
}- Syntax Verification: RFC 5322 compliance
- Domain Validation: DNS and MX record checks
- SMTP Verification: Mailbox existence validation
- Disposable Email Detection: Filter temporary emails
- Role-Based Identification: Flag generic addresses
- Spam Trap Detection: Avoid honeypot emails
email,domain,company_name,first_name,last_name,designation,department,phone,city,country,industry,verified,extracted_date
john.doe@techcorp.com,techcorp.com,Tech Corp,John,Doe,CEO,Executive,+1-555-0100,San Francisco,USA,Technology,true,2024-01-15
sales@retailco.com,retailco.com,Retail Co,,,Sales Manager,Sales,+44-20-1234,London,UK,Retail,true,2024-01-15- Executive Emails: CEO, CTO, CMO, CFO, Founder
- Sales & Marketing: Sales reps, Marketing managers
- Support & Service: Customer support, Help desk
- Technical: Engineers, Developers, IT admins
- HR & Recruitment: HR managers, Recruiters
- General Contact: Info, Contact, Hello
- Technology & SaaS
- E-commerce & Online Retail
- Healthcare & Pharmaceuticals
- Financial Services
- Real Estate & Construction
- Manufacturing & Industrial
- Professional Services
- Education & E-learning
- North America (USA, Canada, Mexico)
- Europe (UK, Germany, France, etc.)
- Asia Pacific (India, China, Japan, Australia)
- Latin America (Brazil, Argentina, Chile)
- Middle East & Africa (UAE, Saudi Arabia, South Africa)
email,domain,company_name,designation,city,country,industry,verified
contact@techstartup.com,techstartup.com,Tech Startup,General,Austin,USA,Technology,true
ceo@healthcorp.com,healthcorp.com,Health Corp,CEO,Boston,USA,Healthcare,true
sales@ecommerce.com,ecommerce.com,Ecommerce Ltd,Sales,London,UK,Retail,true
info@fintech.com,fintech.com,Fintech Inc,General,Singapore,Singapore,Finance,true
support@edutech.com,edutech.com,EduTech,Support,Bangalore,India,Education,true- Build targeted email lists by industry
- Segment audiences by company size
- Geographic targeting for local campaigns
- Personalized B2B outreach
- Sales prospecting databases
- Decision-maker contact lists
- Competitor customer identification
- Partnership opportunity discovery
- Direct candidate outreach
- Company HR contact lists
- Talent pool building
- Job posting distribution
- Industry contact mapping
- Competitive intelligence
- Survey distribution lists
- Focus group recruitment
# Download latest email extractor database
wget https://www.whoisextractor.in/website-database/emails-latest.csv
# Filter by country
grep ",USA," emails.csv > usa-emails.csv
# Filter verified emails only
awk -F',' '$8=="true"' emails.csv > verified-emails.csv
# Extract executive emails only
grep -E ",CEO,|,CTO,|,CMO,|,CFO," emails.csv > executive-emails.csvimport pandas as pd
import re
# Load email database
emails_df = pd.read_csv('website-email-extractor-database.csv')
# Filter verified emails only
verified = emails_df[emails_df['verified'] == True]
# Get emails from specific industry
tech_emails = emails_df[emails_df['industry'] == 'Technology']
# Filter by email pattern (sales emails)
sales_emails = emails_df[
emails_df['email'].str.contains('sales|enquiry|business',
case=False, regex=True)
]
# Remove role-based emails (keep personal only)
personal_emails = emails_df[
~emails_df['email'].str.contains('info@|contact@|hello@',
regex=True)
]
# Export filtered data
tech_emails.to_csv('technology-emails.csv', index=False)import dns.resolver
import smtplib
import re
def validate_email(email):
"""Validate email address format and deliverability"""
# Syntax validation
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
if not re.match(pattern, email):
return False
# Extract domain
domain = email.split('@')[1]
try:
# Check MX records
mx_records = dns.resolver.resolve(domain, 'MX')
mx_host = str(mx_records[0].exchange)
# SMTP verification
server = smtplib.SMTP(timeout=10)
server.connect(mx_host)
server.helo()
server.mail('verify@example.com')
code, message = server.rcpt(email)
server.quit()
return code == 250
except:
return False
# Validate emails from database
df = pd.read_csv('emails.csv')
df['deliverable'] = df['email'].apply(validate_email)
df.to_csv('validated-emails.csv', index=False)import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
import pandas as pd
# Load email list
emails_df = pd.read_csv('website-emails.csv')
# SMTP configuration
smtp_server = "smtp.gmail.com"
smtp_port = 587
sender_email = "your-email@example.com"
password = "your-password"
# Email template
def create_email(recipient_name, recipient_email):
msg = MIMEMultipart()
msg['From'] = sender_email
msg['To'] = recipient_email
msg['Subject'] = f"Hello {recipient_name}"
body = f"""
Dear {recipient_name},
Your personalized email content here...
Best regards,
Your Name
"""
msg.attach(MIMEText(body, 'plain'))
return msg
# Send emails
server = smtplib.SMTP(smtp_server, smtp_port)
server.starttls()
server.login(sender_email, password)
for _, row in emails_df.iterrows():
email = create_email(row['first_name'], row['email'])
server.send_message(email)
print(f"Sent to {row['email']}")
server.quit()- Daily Updates: 500,000+ new emails every day
- Fresh Data: Extracted within 24 hours
- Verified: 95%+ deliverability rate
- Format: CSV, JSON, Excel
- Download: Get Daily Database
- 100+ Million Emails: Complete historical database
- All Industries: Full coverage since 2011
- Bulk Download: Single compressed file
- Format: CSV with all fields
- Download: Get Complete Archive
- Monthly Snapshots: Historical email data
- Trend Analysis: Track email changes over time
- Data Retention: 10+ years of archives
- Format: Monthly CSV files
- Download: Access Archives
# Search emails by domain
curl -X GET "https://www.whoisextractor.in/api/emails?domain=example.com"
# Filter by industry
curl -X GET "https://www.whoisextractor.in/api/emails?industry=Technology"
# Get verified emails only
curl -X GET "https://www.whoisextractor.in/api/emails?verified=true"
# Search by designation
curl -X GET "https://www.whoisextractor.in/api/emails?designation=CEO"{
"status": "success",
"total_results": 1250,
"page": 1,
"per_page": 100,
"data": [
{
"email": "john.doe@example.com",
"domain": "example.com",
"company_name": "Example Corp",
"first_name": "John",
"last_name": "Doe",
"designation": "CEO",
"verified": true,
"verification_date": "2024-01-15"
}
]
}- Email Validity: 95%+ pass all validation checks
- Bounce Rate: Under 5% hard bounces
- Spam Trap Free: Automated honeypot detection
- Update Frequency: Daily verification runs
- Duplicate Removal: Advanced deduplication
All email addresses are extracted from publicly visible websites and comply with:
- GDPR: Right to erasure upon request
- CAN-SPAM Act: Commercial email regulations
- CCPA: California privacy requirements
- PIPEDA: Canadian privacy laws
Email removal requests: privacy@whoisextractor.in
Q: How are emails extracted from websites? A: Using automated web crawlers that scan public web pages for email addresses.
Q: What is the email verification process? A: Multi-step validation including syntax, DNS, MX records, and SMTP checks.
Q: Can I target specific industries? A: Yes, filter by 50+ industries including Technology, Healthcare, Finance, etc.
Q: Are the emails CAN-SPAM compliant? A: Yes, all data is from public sources. Include unsubscribe links in your campaigns.
Q: What formats are available? A: CSV, JSON, Excel (XLSX), and SQL database dumps.
Q: Do you offer API access? A: Yes, RESTful API with rate limits of 1000 requests/hour.
- Documentation: API Documentation
- Sample Download: Sample Email Database
- Email: support@whoisextractor.in
- Live Chat: 24/7 on website
Start building your email marketing lists with verified email addresses:
Download Website Email Extractor Database
Power your email marketing campaigns with 100+ million verified email addresses from websites worldwide.