Gofundme Campaign Scraper

Scrape GoFundMe campaign pages to extract fundraising data, donor counts, campaign stories, organizer information, and recent donations. Monitor crowdfunding trends, track campaign performance, or build datasets of fundraising campaigns at scale.

What does GoFundMe Campaign Scraper do?

This actor takes a list of GoFundMe campaign URLs and extracts detailed information from each campaign page. It uses a headless browser with stealth capabilities to reliably access campaign data, including amounts raised, funding goals, donor counts, the full campaign story, and the most recent donations.

Use this scraper to:

• Track fundraising progress across multiple campaigns over time
• Analyze crowdfunding trends by extracting campaign data at scale
• Monitor competitor campaigns for benchmarking and research
• Build datasets of GoFundMe campaigns for academic or market research
• Aggregate donation data to understand giving patterns and donor behavior

Input

Field	Type	Description	Default
urls	Array of strings	Required. List of GoFundMe campaign URLs to scrape. Each URL should point to an individual campaign page (e.g., https://www.gofundme.com/f/campaign-name).	[]
maxResults	Integer	Maximum number of campaign pages to scrape in a single run. Controls cost and execution time.	100
useResidentialProxy	Boolean	Enable residential proxies for improved success rates against anti-bot protection. Recommended for production use.	true

Example Input

{
    "urls": [
        "https://www.gofundme.com/f/example-campaign-1",
        "https://www.gofundme.com/f/example-campaign-2"
    ],
    "maxResults": 50,
    "useResidentialProxy": true
}

Output

Each scraped campaign produces a JSON object with the following fields:

Field	Type	Description
url	String	The GoFundMe campaign URL that was scraped
title	String	Campaign title or headline
organizer	String	Name of the campaign organizer
raisedAmount	Number	Total amount raised so far in USD
fundingGoal	Number	Campaign funding goal in USD
donorCount	Integer	Total number of donors or supporters
category	String	Campaign category (e.g., Medical, Emergency, Education)
story	String	Campaign story text (truncated to 3,000 characters)
createdDate	String	Date the campaign was created
recentDonationsCount	Integer	Number of recent donations extracted (up to 10)
recentDonations	Array	List of recent donations, each with name, amount, and time
error	String	Error code if scraping failed (e.g., 403, 429, REQUEST_FAILED)
errorMessage	String	Human-readable error description
scrapedAt	String	ISO 8601 timestamp of when the data was scraped

Example Output

{
    "url": "https://www.gofundme.com/f/example-campaign",
    "title": "Help John with Medical Expenses",
    "organizer": "Jane Smith",
    "raisedAmount": 15420,
    "fundingGoal": 25000,
    "donorCount": 312,
    "category": "Medical",
    "story": "John was recently diagnosed with...",
    "createdDate": "2025-11-15",
    "recentDonationsCount": 10,
    "recentDonations": [
        {
            "name": "Sarah K.",
            "amount": "$50",
            "time": "2 hours ago"
        },
        {
            "name": "Anonymous",
            "amount": "$100",
            "time": "5 hours ago"
        }
    ],
    "scrapedAt": "2026-02-11T12:00:00.000Z"
}

Proxy Configuration

This scraper supports both residential and datacenter proxies:

• Residential proxies (default): Higher success rates against GoFundMe's anti-bot systems. Recommended for production scraping.
• Datacenter proxies: Lower cost but may experience higher block rates. Suitable for small-scale testing.

Limitations

• Requires valid GoFundMe campaign URLs as input (does not discover or search for campaigns)
• Campaign story text is truncated to 3,000 characters to manage dataset size
• Recent donations are limited to the 10 most recent visible on the page
• Some campaigns may have restricted access or may have been removed
• Rate limiting may occur with large numbers of requests in a short period

Tips for Best Results

1. Use residential proxies for the most reliable scraping results
2. Start with a small batch of URLs to verify output before scaling up
3. Monitor error counts in the status messages to detect blocking patterns
4. Space out large runs to avoid triggering rate limits
5. Check the error field in results to identify campaigns that need re-scraping