Telegram Email Scraper - Keyword & Location Targeting

Telegram Email Scraper 🔍

Telegram Email Scraper helps you automatically extract emails from Telegram using keywords you choose—solving the time-consuming problem of manual email hunting for marketers, recruiters, and sales pros. It’s also a practical telegram email extractor for faster extract emails from telegram and scalable telegram lead generation when you need results quickly.

---

🌟 Key Features of Telegram Email Scraper

Feature	Benefit
✅ Targeted Keyword Search	Reach the exact Telegram audience you need with keyword-driven discovery
✅ Location Filtering	Add location to focus results on a specific city, region, or country
✅ Custom Domain Filter	Extract only @gmail.com-style (or any domains you provide) email addresses
✅ Max Emails Control	Set maxEmails to cap the total emails collected per run
✅ Bulk Export Ready	Results land in your Apify dataset for easy JSON/CSV export workflows
✅ Real-Time Saving	Each discovered result is pushed and saved incrementally as the run progresses
✅ Deduplication of Emails	Avoid repeated emails by tracking seen_emails during the run

Related SEO angles you’ll see in marketing teams include telegram user email scraper and OSINT email extraction—this actor is built for that kind of practical workflow.

---

📥 Input — Telegram Email Scraper Parameters

{
  "keywords": ["manager", "founder"],
  "location": "",
  "customDomains": ["@gmail.com", "@yahoo.com"],
  "maxEmails": 20
}

Parameter	Type	Required	Default	Description
keywords	Array	✅ Yes	—	Search terms to find relevant Telegram profiles and contact mentions for email harvesting from telegram
location	String	No	""	Location to filter search results (useful for telegram channel email scraping with a regional focus)
customDomains	Array	No	[]	List of custom email domains to filter extracted emails (e.g., @gmail.com, @yahoo.com)
maxEmails	Integer	No	20	Cap on total emails to collect per run (helps control scraping time while you do bulk email scraping)

Pro tip: for best results with a telegram email extractor, use focused keywords plus the email domains you actually want.

---

📤 Output — What Telegram Email Scraper Returns

The actor saves each result as a JSON record in your Apify dataset.

{
  "keyword": "founder",
  "title": "Founder @GrowthOps — Telegram community",
  "description": "We connect teams with operators. Contact us for collaborations. hello@growthops.tools",
  "url": "https://t.me/growthops",
  "email": "hello@growthops.tools"
}

Field	Type	Description
keyword	String	The search term that surfaced this result (helps track your telegram email finder queries)
title	String	Telegram profile name or business title shown for the lead
description	String	Bio or profile summary content where the email was found
url	String	Direct link to the Telegram profile/channel for this lead
email	String	Email address extracted from the Telegram content for your outreach list

This dataset is tailored for telegram bot for email collection workflows, where you want clean, structured telegram contacts ready for analysis.

---

💻 How to Use Telegram Email Scraper — Step-by-Step

1. Open the Actor — Find Telegram Email Scraper in the Apify Store: https://apify.com/store
2. Enter Keywords — Add job titles, roles, or themes you want to extract emails from telegram for
3. Set Location (optional) — Use location to narrow where leads are likely to be found
4. Filter by Domain (optional) — Provide customDomains like @gmail.com or @yahoo.com to focus harvesting
5. Set Max Emails — Use maxEmails to cap results and control run duration
6. Run the Actor — Start the run and monitor logs as it collects leads
7. Export Results — Download from your Apify dataset and import into your CRM or outreach tooling

No coding required. Results ready in minutes.

---

💡 Best Use Cases for Telegram Email Scraper

• 🎯 Lead Generation — Build a telegram lead generation list for outreach and partnerships
• 📣 Email Marketing — Enrich campaigns with telegram channel email scraping contacts
• 🤝 Recruitment — Find professionals using data mining telegram contacts workflows
• 🔬 Market Research — Identify industry voices and community operators via telegram user email scraper outputs
• 📊 CRM Enrichment — Improve records with extracted email validation and deduplication-ready fields

If you’re doing OSINT email extraction or regex email detection-based pipelines, this actor’s structured output fits neatly into your process.

---

Disclaimer

Telegram Email Scraper only accesses publicly available data. It does not retrieve private profiles, authenticated content, or password-protected pages. You are responsible for ensuring your use complies with applicable laws and platform policies, including anti-spam rules and privacy regulations such as GDPR and CCPA. This tool is intended for legitimate purposes like lead generation and research, and for automated compliance checks in your own workflows. For data-removal requests, contact 📧 scrapidocontact@gmail.com.

---

🆘 Support & Feedback

Have a question or found an issue with the Telegram Email Scraper? We're here to help.

• 🐞 Bug Reports: Open a ticket in the repository's Issues section
• ✨ Custom Solutions & Feature Requests: Reach out to our team
• 📧 Email: scrapidocontact@gmail.com

Your feedback shapes the roadmap — we read every message.

Multiple Email Types

Email Types replaces the old single Audience Type choice: select as many kinds of mailbox as you want and the run chases all of them together.

Type	What it matches
Personal / free webmail	Gmail, Outlook, Yahoo, iCloud, AOL, Proton, ...
Business / corporate	Company domains - free webmail and institutions excluded
Education (.edu / .ac)	.edu, .ac.uk, .edu.au, .ac.in and other academic suffixes
Government (.gov / .mil)	.gov, .mil, .gov.uk, .gc.ca, ...
Non-profit (.org)	.org, .ngo, .org.uk, ...

Each selected type contributes its own Google dork patterns and its own domain test, so a result is only kept if it genuinely belongs to the type that found it. Every row carries an emailType field recording which one that was.

Suffixes are matched as real domain suffixes, so cs.mit.edu counts as Education while notedu.com does not.

Setting Custom Email Domains still overrides everything: an explicit domain list is a manual override and replaces the type-driven patterns. The legacy audienceType value is still accepted, so saved inputs keep working.