Youtube Email Scraper - Multi-Engine, Type Targeted

Youtube Email Scraper

Youtube Email Scraper helps you automate youtube lead generation by extracting emails and profile contact details from publicly available YouTube sources. It also supports an email extractor workflow for marketing email list building and customer prospecting—so you can scale outreach without manual searching.

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What Does Youtube Email Scraper Do? 🤖

Youtube Email Scraper takes your search terms, a source region (All, Channel, Video, Shorts, Posts), and an email audience type (B2C or B2B), then runs an automated extraction job to find and collect matching YouTube contacts. During a run, it scrapes and extracts emails from publicly available sources, filters results using your configured limits, and outputs a structured dataset you can export and analyze. You can use it as a youtube contact scraper or to extract emails from youtube for campaign building. It’s a fast, repeatable way to automate youtube email collection compared to manual prospecting.

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What Can Youtube Email Scraper Extract? 📊

The actor collects both contact and profile context so you can build targeted lists and do downstream analysis.

Data Type	Field Name	Description
Contact	email	Primary email address found for the YouTube profile contact
Identity	title	Profile name or page title associated with the extracted contact
Context	description	Bio, summary, or other profile text that provides context
Discovery	keyword	The search term that surfaced this profile/contact
Navigation	url	Direct URL to the YouTube profile/page

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Key Features of Youtube Email Scraper ⚡

• ✅ Keyword-Driven Search: Uses your searchTerms to target relevant YouTube profiles for lead scraping
• 🌍 Location Targeting: Sets a country to focus extraction results by region
• 📧 B2C / B2B Email Focus: Choose emailType to guide whether you’re targeting B2C or B2B contacts
• 🔄 Engine Choice for Reliability & Speed: Pick engine for either Cost Effective (New) or Legacy extraction behavior
• 📊 Structured Output for Analysis: Saves results in a clean dataset with fields like email_domain and email_type for youtube email extraction workflows
• 💾 Result Limiting via maxEmails: Control volume with maxEmails (1–10000) for predictable runs
• 🗂️ Source Region Control: Target different parts of YouTube via sourceRegion (All, Channel, Video, Shorts, Posts)
• 📤 Ready for CRM & Outreach: Export the dataset and use the results for youtube channel outreach and marketing email list building

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How to Use Youtube Email Scraper 🚀

1. Find the Actor — open the Apify Store and search for Youtube Email Scraper
2. Open the Input Tab — in Apify Console, go to the actor’s Input tab
3. Add Search Terms — fill searchTerms with the queries you want to target (e.g., niche topics)
4. Choose Your Targeting — set country, sourceRegion, and emailType (B2C or B2B)
5. Set a Run Limit — choose maxEmails to control how many email results to collect
6. (Optional) Select an Engine — use engine to choose cost-effective or legacy
7. Start the Run & Monitor — check logs and view progress, then export from the dataset tab

No coding required.

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Youtube Email Scraper Output Format 📦

The actor saves results to your Apify dataset in structured JSON records that are ready to export and enrich further.

⬇️ Input Example

{
  "searchTerms": ["fitness", "yoga teacher"],
  "country": "United States",
  "sourceRegion": "All",
  "emailType": "B2C",
  "maxEmails": 20,
  "engine": "legacy"
}

⬆️ Output Example

{
  "keyword": "fitness",
  "title": "PowerFit Studio",
  "url": "https://www.youtube.com/@powerfitstudio",
  "description": "Strength training, workout programs, and studio updates. Contact us for partnerships and collaborations.",
  "email": "hello@powerfitstudio.com",
  "email_domain": "powerfitstudio.com",
  "email_type": "B2C",
  "scrape_from": "Channel",
  "country": "United States"
}

Note: The dataset output is a table-style dataset with the fields shown in the schema below.

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🎯 Use Cases of Youtube Email Scraper

You can use this youtube lead generation tool for several outreach and research workflows, including:

• B2B Lead Generation: Collect emails from YouTube channels and related pages to power customer prospecting and outreach lists
• Marketing Email List Building: Build a marketing email list from creators and businesses that publish contact details publicly
• Influencer Email Finder: Find and organize contacts for youtube channel outreach without spending hours manually copying addresses
• Contact Information Mining: Extract and filter emails by email_domain and email_type to segment results for campaigns
• Data Enrichment for Teams: Provide analysts and growth teams with structured records (email + profile context) for reporting and CRM import

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How Much Will Youtube Email Scraper Cost You? 💰

Cost is based on Apify’s pay-per-result model. This actor is designed to return up to maxEmails per run, so a higher maxEmails value can increase total billed results. For better budgeting, set maxEmails to the maximum number of email results you actually need. You can also use narrower searchTerms and specific sourceRegion values to improve yield per run.

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Is It Legal to Scrape Youtube? ⚖️

The actor is designed to collect information from publicly available sources. It does not require logins or access to private profiles. That said, users must still follow YouTube’s Terms of Service, applicable privacy rules (such as GDPR/CCPA where relevant), and anti-spam laws. If you’re using scraped data for outreach, ensure your outreach practices are compliant. If you have concerns related to data handling or removal, contact scrapidocontact@gmail.com.

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Youtube Email Scraper Input Parameters 📋

Below are the input parameters supported by this actor.

{
  "searchTerms": ["fitness"],
  "country": "United States",
  "sourceRegion": "All",
  "emailType": "B2C",
  "maxEmails": 20,
  "engine": "legacy"
}

Parameter	Type	Required	Default	Description
country	string	No	United States	Select the target country/region to guide where results are drawn from
emailType	string	No	B2C	Choose one audience focus: B2C or B2B
engine	string	No	legacy	Choose scraping engine: cost-effective (Cost Effective, new) or legacy
maxEmails	integer	No	20	Maximum number of emails to collect (bounded from 1 to 10000)
searchTerms	array	Yes	—	List of queries to find YouTube profiles
sourceRegion	string	No	All	Choose what part of YouTube to target: All, Channel, Video, Shorts, or Posts

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During the Actor Run ⏱️

You’ll see live logs in the Apify Console while the extraction progresses. Results are saved to the dataset as the run proceeds, so you can check output during long runs. The total time can vary based on your searchTerms, sourceRegion, network conditions, and the selected engine. If you’re not getting enough results, try adjusting searchTerms or increasing maxEmails.

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Final Note ✉️

Get started with Youtube Email Scraper on Apify to automate youtube email extraction for outreach, research, and CRM enrichment. Questions or feature ideas? Email scrapidocontact@gmail.com.

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FAQ — Youtube Email Scraper ❓

How does the Youtube Email Scraper work?

The actor uses your configured searchTerms, country, and sourceRegion to locate relevant YouTube profiles/pages and then extracts publicly available email addresses. It applies emailType and dataset limits (maxEmails) to keep results focused for youtube lead generation and marketing email list building.

What types of YouTube sources can I target?

You can control where the actor focuses with sourceRegion, choosing between All, Channel, Video, Shorts, and Posts. This makes it useful for different youtube contact scraper use cases, from channel outreach to broader content-driven discovery.

What does email_type mean in the results?

The dataset includes email_type. This aligns with the audience focus selected by emailType in the input (either B2C or B2B), helping you segment results for influencer email finder and customer prospecting workflows.

How can I filter results by email domain?

Each record includes email_domain, which lets you segment and validate contacts by domain (for example, isolating company domains vs. consumer domains). This is especially helpful for contact information mining and compliance email scraping workflows where segmentation matters.

How much does it cost to use the Youtube Email Scraper?

Pricing follows Apify’s pay-per-result approach. Since you can cap output using maxEmails, you can control how many results you request per run and estimate spend accordingly. For more predictable costs, start small and expand only after validating your yield.

Is it legal to scrape YouTube for emails?

The actor is intended for extracting information from publicly available sources. Still, legality depends on how you use the data and whether you comply with YouTube’s Terms of Service and relevant privacy and anti-spam regulations. Use extracted emails only for legitimate purposes, and consider adding consent or opt-out mechanisms where required.

What should I do if I’m not getting enough emails?

Try broadening your searchTerms, switching sourceRegion to All, or adjusting emailType (B2C vs. B2B). You can also increase maxEmails (within its allowed range) to request more results. If you use a narrower engine choice (engine), switching to the other option may also improve outcomes.

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🆘 Support & Feedback

Need help with setup, output, or a feature request for Youtube Email Scraper?

• 📧 Email support: scrapidocontact@gmail.com

We’re happy to help you get the most accurate results for your youtube email extraction and youtube channel outreach workflows.

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.