How to Use RedScraper
Step-by-step guide to collecting Reddit data with RedScraper.
Overview
RedScraper allows you to collect posts, comments, user profiles, and subreddit data from Reddit using direct links or keyword searches. This guide explains the full scraping process from setup to export.
Step 1 — Choose Scraping Method
RedScraper provides two primary methods for collecting Reddit data. Each method is designed for different research goals, data sources, and analysis scenarios.
Reddit URL method is recommended when you already know the exact location of the content you want to analyze. By providing a direct link, you can extract structured data from a specific subreddit, post, comment thread, or user profile without performing a platform-wide search.
This method is commonly used for monitoring individual communities, tracking ongoing discussions, analyzing competitors, or reviewing specific user activity.
Examples of supported URLs:
• https://www.reddit.com/r/technology/top
• https://www.reddit.com/user/spez
• https://www.reddit.com/comments/abc123
• https://www.reddit.com/r/all/hot
• https://www.reddit.com/r/popular/new
Feed URLs such as /r/all and /r/popular allow you to monitor trending and viral content across multiple communities in real time. They are useful for discovering emerging topics and high-engagement discussions.
Search Term method is designed for discovering relevant content across multiple subreddits using keywords and phrases. Instead of focusing on a single source, this approach scans Reddit for posts and comments related to specific topics.
This method is recommended for market research, brand reputation tracking, trend analysis, audience research, and competitive intelligence.
Examples of search queries:
• AI startup funding
• gaming laptop review
• best VPN 2026
• SaaS pricing strategy
• remote work tools
Using multiple keywords helps refine search results and improves the relevance of collected data. For best results, use clear and specific phrases that match real user discussions.
Choosing the appropriate method depends on your research objective. Use direct URLs for focused analysis of known sources, and search terms for exploring broader conversations and discovering new trends.
Keywords & Topics Monitoring
Keyword-based scraping enables continuous monitoring of discussions related to your brand, products, services, and industry topics across Reddit. This approach helps transform raw conversations into actionable business insights.
By tracking relevant keywords and phrases, you can identify emerging trends, detect shifts in customer sentiment, and respond to market changes faster than your competitors.
- Brand MonitoringTrack what users are saying about your brand, products, and services in real time.
- Market IntelligenceIdentify new business opportunities before competitors discover them.
- Industry InsightsStay up to date with the latest news, technologies, and discussions in your niche.
- Decision SupportAggregate real-time data to support strategic and operational decisions.
- Competitive AnalysisMonitor competitors, campaigns, and community reactions.
- Lead GenerationFind potential customers, partners, and sales opportunities.
- Trend DiscoveryDetect early signals of new trends and market shifts.
- Customer EngagementIdentify users seeking solutions and respond with personalized recommendations.
This workflow is especially valuable for marketing teams, product managers, analysts, and growth specialists who rely on real user feedback and community-driven insights.
Step 2 — Configure Data Fields
In this step, you can configure exactly what data will be extracted from Reddit. RedScraper supports multiple entity types and allows you to collect comprehensive datasets or highly targeted information.
You may enable all available categories to retrieve complete post, comment, subreddit, and user data in a single scraping session. This option is useful for large-scale analysis, data warehousing, and advanced research workflows.
Alternatively, you can select specific entities and customize individual fields within each category. This approach helps reduce processing time, minimize unnecessary data, and optimize export size for focused use cases.
Each category provides detailed field documentation, including descriptions, formats, and availability. Use the links below to review all supported fields and configure your extraction settings accordingly.
Step 3 — Apply Filters and Sorting
Use filters to control which posts will be collected.
- Time FilterAll time, past month, past week, etc.
- SortingHot, New, Top, or Relevance.
- NSFW ContentEnable or disable adult content.
Step 4 — Set Output Options
Configure how much data you want to receive and in which format.
- Output LimitMaximum number of results (1–10,000).
- Export FormatJSON, CSV, Excel, or XML.
Step 5 — Start Scraping
After configuring all options, click the “Start Scraping” button. RedScraper will process your request and generate the dataset.
Viewing and Downloading Results
When scraping is complete, your data becomes available in the Scraper History section. From there, you can preview, download, or re-export the dataset.
Data History and Storage
All completed scraping jobs are automatically stored in your account history. This allows you to access previous datasets at any time without repeating the same request.
Each saved job includes its original configuration, selected fields, filters, and export settings. You can review past setups, re-run scrapers, or download results again when needed.
Keeping historical data helps track trends over time, compare results, and maintain consistent research workflows.
Best Practices
- Use specific keywords for better results.
- Limit large jobs to avoid long processing times.
- Combine filters to improve data quality.
- Export in JSON for API integrations.
