🚀 Product Hunt Scraper — Daily Launches & Trending Products

Extract product launches from Product Hunt — names, taglines, hunters, launch dates and a trending score — as clean, structured data. Pull the live feed of featured/trending products, grab a day's launches, search the feed by keyword, or browse by topic. It's the launch data startup analysts and growth teams track every morning, returned as one tidy row per product without fighting Cloudflare or a GraphQL token. Export to JSON/CSV/Excel, run on a schedule, call via API, or connect to Make, Zapier or n8n.

🟠 What is the Product Hunt Scraper?

It turns the Product Hunt feed into a structured dataset. Pick a mode — trending, daily, search or topic — and it reads Product Hunt's public Atom feed and returns each launch with its name, tagline, hunter, launch timestamp, Product Hunt URL, product ID and a position-based trending score. Because it uses the official feed it sidesteps Cloudflare and works without an API key, so you can build your own daily launch history hands-free.

What data does it extract?

• Product name and tagline
• Product Hunt URL (product_hunt_url) and product ID (product_id)
• Hunter name (hunter_name) — who posted the launch
• Launch date (launch_date) — published timestamp from the feed
• Trending score (trending_score) — derived from feed position (earlier = higher)
• Scrape timestamp (scraped_at)

The data model also carries engagement fields (upvotes, comments_count, topics, maker_names, featured, reviews_rating) that are returned with default values since the public feed does not expose them — the reliably populated fields are listed above.

⬇️ Input

Run it four ways — trending, a specific day, a keyword search, or by topic:

Field	Description
scrapeMode	trending, daily, search, or topic
searchQuery	Keyword to match against name/tagline (required for search mode)
topic	Topic/category slug (required for topic mode), e.g. artificial-intelligence
date	Date in YYYY-MM-DD format (used with daily mode)
maxResults	Cap the run (1–500)

Example input

{
  "scrapeMode": "trending",
  "maxResults": 50
}

⬆️ Output

Every launch is one clean row (view as a table, or export JSON / CSV / Excel):

{
  "name": "Acme AI Copilot",
  "tagline": "Your AI pair-programmer for data pipelines",
  "url": "",
  "product_hunt_url": "https://www.producthunt.com/posts/acme-ai-copilot",
  "description": null,
  "upvotes": 0,
  "comments_count": 0,
  "reviews_count": 0,
  "reviews_rating": null,
  "topics": [],
  "thumbnail": null,
  "maker_names": [],
  "hunter_name": "Jane Doe",
  "featured": false,
  "launch_date": "2026-06-26T08:01:00-07:00",
  "product_id": "123456",
  "trending_score": 98,
  "scraped_at": "2026-06-26T15:30:00.000Z"
}

💡 Use cases

• 🔭 Startup & VC discovery: spot newly launched products and their hunters early, building a feed of fresh prospects.
• 🥊 Competitor tracking: monitor launches in your space and rank them by trending score.
• ✍️ Positioning research: study high-performing taglines to sharpen your own product messaging.
• 🗓️ Launch history: schedule a daily run to build your own archive of Product Hunt launches over time.

❓ FAQ

How do I scrape Product Hunt launches? Pick a scrapeMode (trending, daily, search or topic), set maxResults, then Run. You get structured launches with name, tagline, hunter, launch date, product URL and a trending score.

Do I need an API key? No. It reads Product Hunt's public Atom feed — no login, token or GraphQL key required, and it isn't blocked by Cloudflare.

Does it return upvote and comment counts? The public feed doesn't expose engagement counts, so upvotes, comments_count and topics come back with default values. The reliably populated fields are name, tagline, hunter, launch date, product URL/ID and the trending score.

How is the trending score calculated? It's derived from each product's position in the feed — products nearer the top score higher (roughly 100 down to 1) — so you can sort by current momentum.

What's the difference between trending and daily mode? Both read the same live feed of currently featured/trending products; daily is intended for a specific date. Search mode filters that feed by keyword and topic mode requests a category slug.

How do I focus on one category? Use scrapeMode: topic with a topic slug such as artificial-intelligence, developer-tools or productivity.

How does search mode work? The feed has no search endpoint, so search mode pulls the current feed and keeps only products whose name or tagline contains your searchQuery (case-insensitive); if nothing matches it returns the full feed so the run is never empty.

How many products can it return? Up to your maxResults cap (1–500), limited by how many entries the feed currently contains.

Can I run it on a schedule or via API? Yes — schedule recurring runs in Apify, call it via the API/SDK, or connect it to Make, Zapier or n8n.

Is scraping Product Hunt legal? It only reads publicly available feed data. Use it responsibly for research, and follow applicable laws and Product Hunt's terms.

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Keywords: Product Hunt scraper, Product Hunt API, daily launches, trending products, startup discovery, product launches data, tagline research, startup leads, tech product tracking, launch history, hunter data, competitor monitoring, market research, no-code startups, SaaS launches.