Reddit Email Scraper

Reddit Email Scraper 📬

Reddit Email Scraper is an Apify actor that scrapes emails from Reddit using your chosen keywords and email-domain filters. Whether you’re looking to build a reddit leads email scraper list, run OSINT reddit email scraper research, or simply extract emails from reddit at scale, this tool helps you turn public web discussions into usable contact data—saving you hours of manual work.

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🚀 Why choose Reddit Email Scraper?

Feature	Benefit
✅ Keyword-driven email discovery	Finds emails associated with Reddit bios and posts related to your keywords
✅ Custom email-domain targeting	Helps you focus results on specific domains (for example @gmail.com) so your outreach stays relevant
✅ Built-in proxy support	Supports reliable scraping runs when websites throttle or block requests
✅ Retries and fallbacks for resilience	Includes retry logic and fallback behavior to improve the chance of successful runs
✅ Structured JSON dataset output	Returns consistent fields like email, title, and url so results are easy to analyze
✅ Designed for scale with limits	Lets you cap collection using maxEmails to control runtime and scraping cost

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🔑 Key features

• 🎯 Targeted email harvesting from public sources: Extracts emails from publicly available Reddit bios and posts tied to your keywords.
• 🧭 Flexible discovery via keywords: Accepts a list of keywords to broaden or narrow what the Reddit Email Scraper searches for.
• 🧩 Email-domain filtering with customDomains: Use customDomains to collect only emails matching your chosen domains.
• 🛡️ Resilient scraping with proxy support: Includes proxy configuration support for more reliable scraping sessions.
• 🔄 Retries and stop conditions: Uses retry and pagination logic, and stops when maxEmails is reached.
• 💾 Real-time dataset saving: Pushes each discovered email record to the dataset as it is found.
• 📊 Deduplication of emails: Avoids pushing duplicate emails across the run using seen_emails.
• 🔁 Progress persistence: Saves progress so you can resume with less risk of losing already collected data.

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📝 Input

Provide input via an input.json file. Example structure:

{
  "keywords": ["founder", "marketing"],
  "location": "",
  "platform": "Reddit",
  "customDomains": ["@gmail.com"],
  "maxEmails": 20,
  "engine": "cost-effective",
  "proxyConfiguration": {}
}

Input Fields

Field	Required	Description
keywords	Yes	A list of keywords to search for. These keywords drive which Reddit bios and posts are considered for email discovery.
location	No	Location to filter search results. Leave empty for no location filtering.
platform	No	Platform selector. This actor supports Reddit (default: Reddit).
customDomains	No	List of custom email domains to target (for example @gmail.com). Emails are filtered to match these domains.
maxEmails	No	Maximum number of emails to collect. The scraper stops once this limit is reached (default: 20, allowed range: 1 to 10000).
engine	No	Choose scraping engine: cost-effective (Cost Effective (New)) or legacy (Legacy). Use cost-effective by default.
proxyConfiguration	No	Proxy configuration for this Actor. You can configure proxies using Apify’s proxy input options.

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📦 Output

The actor saves each discovered email record to the dataset in JSON format using Actor.pushData().

Example output record:

{
  "network": "Reddit.com",
  "keyword": "marketing",
  "title": "No data",
  "description": "No data",
  "url": "No URL",
  "email": "example@gmail.com",
  "proxyGroups": ["cost-effective"]
}

Output Fields

Field	Type	Description
network	string	Source network label (Reddit.com).
keyword	string	The keyword currently being used for the scrape.
title	string	The title of the web result being processed.
description	string	The description/snippet text where the email was found.
url	string	The URL associated with the extracted email (the result link).
email	string	The extracted email address.
proxyGroups	array	Proxy group identifiers used for this run (as provided by the engine/proxy configuration).

Notes:

• The actor deduplicates emails using a seen_emails set before pushing them to the dataset.
• Each pushed record is written immediately (so you can inspect partial progress while the run is still executing).

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🚀 How to use Reddit Email Scraper (via Apify Console)

1. Open Apify Console 🔐
   Log in at console.apify.com and go to the Actors tab.

2. Find Reddit Email Scraper
   Search for Reddit Email Scraper and open the actor page.

3. Set your input parameters ⚙️
   In the INPUT panel, provide:

   • keywords (required)
   • optional filters like customDomains (recommended for tighter results)
   • optional limits like maxEmails

4. Choose proxy options (optional but recommended for scale) 🛡️
   Configure proxyConfiguration if you have specific proxy needs for your scraping run.

5. (Optional) Select the engine
   Keep the default engine as cost-effective, or switch to legacy if you specifically need it.

6. Run the actor ▶️
   Click Run. During execution, you’ll see logs while the actor paginates through results and pushes records to the dataset as it finds new emails.

7. Review results in the Dataset 📊
   After the run completes (or while it’s running), open the OUTPUT tab and inspect the dataset.

8. Export your data
   Export the dataset in your preferred format (for example JSON/CSV) from the dataset UI.

No coding required—get structured reddit email scraper results in minutes.

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⚙️ Advanced features & SEO optimization

• 🔍 Engineered for email harvesting from Reddit bios and posts: The Reddit Email Scraper is designed to excel at “scrape emails from reddit” and “reddit leads email scraper” workflows.
• 🧱 Keyword + domain targeting: Use keywords plus customDomains to narrow down results, which improves relevance for your reddit email outreach list.
• 🕒 Timeout and scale awareness: Large searches or high maxEmails can take longer; plan accordingly and increase run timeout settings in Run Options if needed.
• 💾 Progress persistence for long runs: The actor persistently saves progress (cursor and already seen emails), helping you avoid unnecessary rework during extended runs.

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🎯 Best use cases

• 📈 Growth teams building outreach lists: Generate a starting dataset of emails connected to relevant Reddit discussions for faster lead sourcing.
• 🧠 Market researchers analyzing community niches: Identify contact domains tied to keywords and community themes for targeted analysis.
• 🎓 Recruiters sourcing talent signals: Use targeted keywords and domains to build candidate outreach lists from public profile content.
• 🏢 B2B marketers running lead-gen campaigns: Collect domain-filtered emails to feed email marketing workflows and CRM enrichment.
• 🧾 Data analysts creating contact-enriched datasets: Combine keyword, title, url, and email fields into clean tables for downstream modeling.
• 🛠️ Developers automating OSINT pipelines: Pull dataset output into scripts and automation systems for repeatable reddit email list scraper runs.
• ✉️ Sales ops streamlining prospecting research: Quickly compile prospects associated with specific topics and email domains.

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🔧 Technical specifications

• Supported Input Formats

  • ✅ keywords as an array of strings
  • ✅ customDomains as an array of email-domain strings (e.g. @gmail.com)
  • ✅ platform supports Reddit

• Proxy Support

  • ✅ Supported via proxyConfiguration
  • ✅ Engine selection available via engine (cost-effective or legacy)

• Retry Mechanism

  • ✅ Built with retries and fallback behavior
  • ✅ Stops when maxEmails is reached

• Dataset Structure

  • ✅ JSON records pushed via Actor.pushData() with fields: network, keyword, title, description, url, email, proxyGroups

• Rate Limits & Performance

  • ✅ Paginates through results and supports higher limits with longer runtimes
  • ✅ Designed to keep saving progress as it finds new emails

• Limitations

  • ❌ Only uses emails discoverable from publicly available sources and associated content
  • ❌ Does not guarantee finding the exact number requested—use maxEmails as a cap, not a promise of results volume

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❓ FAQ

✅ What does Reddit Email Scraper do?

Reddit Email Scraper extracts email addresses from publicly available sources related to Reddit profiles, using the keywords you provide and filtering by your chosen customDomains.

❓ How does the tool decide which emails to collect?

It uses your keywords to guide discovery and then extracts email addresses found in the associated Reddit bios/posts content, matching them against the email-domain filters you provide in customDomains.

❌ Do I need to specify every input field?

No. Only keywords is required. You can optionally add customDomains, location, maxEmails, and proxyConfiguration depending on how targeted you want the output to be.

💡 Can I limit how many emails I collect?

Yes. Use maxEmails to cap the maximum number of emails the actor will collect before stopping.

💻 Can I use this from an API or code workflow?

Yes. This is an Apify actor, so you can run it through Apify’s platform workflows and read the dataset output. The actor pushes structured JSON records with fields like email, url, and keyword.

🌐 What platforms are supported?

This actor is configured with platform set to Reddit.

⚖️ Is this for legal/ethical use?

✅ The actor collects information from publicly accessible sources. It’s your responsibility to follow applicable laws and platform policies, including GDPR/CCPA and spam regulations.

🧹 How do I request data removal?

For data removal requests, contact dataforleads@gmail.com.

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🤝 Support & feature requests

Have questions about Reddit Email Scraper or want to improve your reddit email scraper results? We’d love to hear from you.

• 💡 Feature Requests: Want enhancements like additional export formats, more control over filtering, or output adjustments? Tell us what would help your bulk email extraction from reddit workflow.
• 📧 Contact: Reach out at dataforleads@gmail.com.

Your feedback helps shape future improvements to Reddit Email Scraper.

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🧾 Closing CTA / Final thoughts

If you need a reliable, SEO-friendly way to run a Reddit email outreach list workflow, Reddit Email Scraper is built for that—using structured output and practical controls for scale.