Product Hunt Leaderboard Scraper

A web scraper for extracting structured product launch data from Product Hunt's daily, weekly, monthly, and yearly leaderboards. It's built for automation, lead generation, and market analysis.

Overview

This actor programmatically collects data from Product Hunt leaderboards. You specify a time period (day, week, month, year) and optionally a date, and it returns a list of featured products with their performance metrics, topics, and community engagement data. It's useful for tracking trends, analyzing competitor launches, or gathering market intelligence.

Key Features

• Period-Based Scraping: Target daily, weekly, monthly, or yearly leaderboards. Supports historical data back to 2013.
• Core Product Data: Retrieves product name, tagline, vote/comment counts, rank, launch date, topics, and URLs.
• Optional Detailed Scrape: Enable Scrape product details for full descriptions, pricing models, media galleries, and hunter information.
• Optional Maker Profiles: Enable Scrape maker details for founder names, badges, follower counts, and portfolio links.
• High Performance: Handles pagination and uses concurrent requests for speed. Includes retry logic for reliability.
• Structured Output: Returns clean JSON, ready for analysis, dashboards, or data pipelines.

How to Use

Configure the actor run with the following input parameters. Only the period is required to start.

1. Period (Required): Choose daily, weekly, monthly, or yearly.
2. Date Filter (Optional): Specify a date for the leaderboard (e.g., 2024-01-15). If left blank, it defaults to the most recent period.
3. Scrape Product Details (Optional): Set to true to fetch extended product info (description, pricing, gallery, hunter).
4. Scrape Maker Details (Optional): Set to true to fetch profiles of the product makers/founders.
5. Max Items (Optional): Limit the total number of products to scrape.

The actor will process the leaderboard, handling pagination automatically, and deliver the dataset.

Input/Output

Input Example (Configuration):

{
  "period": "daily",
  "date": "2025-07-28",
  "scrapeProductDetails": true,
  "scrapeMakerDetails": false,
  "maxItems": 50
}

Output Example (Dataset Item):
The primary output is an array of product objects. With details disabled, you get core metrics:

{
  "name": "Clueso",
  "slug": "clueso",
  "tagline": "Create stunning product videos in minutes with AI",
  "latestScore": 1492,
  "launchDayScore": 1226,
  "votesCount": 1530,
  "featuredAt": "2025-07-08T00:01:00-07:00",
  "commentsCount": 314,
  "dailyRank": 1,
  "weeklyRank": 1,
  "monthlyRank": 1,
  "topics": ["SaaS", "Artificial Intelligence", "Video"],
  "thumbnail": "https://ph-files.imgix.net/5db96420-68ff-4d26-81ce-0635d1637bf9.png",
  "url": "https://www.producthunt.com/products/clueso"
}

Enabling scrapeProductDetails adds nested fields like description, pricing, gallery, and hunter. Enabling scrapeMakerDetails adds a makers array with profile data.