Product Hunt Daily Scraper — Extract Launches, Votes & Maker Data

Scrape daily Product Hunt launches including product names, taglines, vote counts, topics, and maker info. Get structured data about every product launched on any given day — no API key needed.

Uses Product Hunt's frontend GraphQL API to fetch launch data. No authentication, no rate limits.

Key Features

• No API key required — bypasses Product Hunt's official API restrictions
• Daily launches — scrape any date's top products sorted by votes
• Rich data — names, taglines, votes, comments, topics, makers, thumbnails
• Date selection — scrape today's launches or any historical date
• Structured JSON output — clean data ready for analysis
• Export to any format — JSON, CSV, Excel, XML, or RSS

Use Cases

1. Trend Tracking & Market Intelligence

Monitor daily launches to spot emerging product categories, technology trends, and market shifts. Track which types of products consistently receive high vote counts.

2. Competitive Intelligence

Get alerted when competitors or similar products launch on Product Hunt. Analyze their positioning, taglines, and community reception.

3. Startup Research & Investment Screening

Build datasets of Product Hunt launches for deal flow analysis. Track which categories attract the most engagement and identify promising early-stage startups.

4. Content Creation & Newsletters

Curate daily or weekly product roundups for newsletters, blogs, or social media. Automate the discovery of interesting new tools to write about.

5. Launch Timing Research

Analyze historical launch data to determine the best day and time to launch your own product. Study vote patterns and ranking dynamics across different dates.

Input Parameters

Field	Type	Required	Default	Description
date	string	No	today	Date to scrape in YYYY-MM-DD format
maxProducts	integer	No	5	Maximum products to scrape (max 100)

Input Examples

Today's top launches:

{
    "maxProducts": 20
}

Specific date:

{
    "date": "2026-03-28",
    "maxProducts": 50
}

Output Format

Field	Type	Description
id	string	Product Hunt product ID
name	string	Product name
tagline	string	One-line product description
slug	string	URL slug on Product Hunt
url	string	Full Product Hunt URL
website	string	Product's external website URL
votesCount	integer	Total upvotes received
commentsCount	integer	Number of comments
topics	array	Category tags
makers	array	Names of product makers
thumbnailUrl	string	Product thumbnail image URL
rank	integer	Daily ranking position
date	string	Launch date

Sample Output

{
    "id": "456789",
    "name": "AI Code Reviewer",
    "tagline": "Automated code review powered by GPT-4",
    "slug": "ai-code-reviewer",
    "url": "https://www.producthunt.com/posts/ai-code-reviewer",
    "website": "https://aireviewer.dev",
    "votesCount": 487,
    "commentsCount": 52,
    "topics": ["Developer Tools", "Artificial Intelligence"],
    "makers": ["Jane Smith"],
    "thumbnailUrl": "https://ph-files.imgix.net/...",
    "rank": 1,
    "date": "2026-03-28"
}

Code Examples

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("cryptosignals/producthunt-daily-scraper").call(run_input={
    "date": "2026-03-28",
    "maxProducts": 20,
})

for product in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"#{product.get('rank', '?')} {product['name']} ({product['votesCount']} votes)")

Track launches over multiple days:

from apify_client import ApifyClient
from datetime import datetime, timedelta

client = ApifyClient("YOUR_API_TOKEN")

for i in range(7):
    date = (datetime.now() - timedelta(days=i)).strftime("%Y-%m-%d")
    run = client.actor("cryptosignals/producthunt-daily-scraper").call(run_input={
        "date": date,
        "maxProducts": 5,
    })
    products = list(client.dataset(run["defaultDatasetId"]).iterate_items())
    top = products[0] if products else None
    if top:
        print(f"{date}: #1 {top['name']} ({top['votesCount']} votes)")

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('cryptosignals/producthunt-daily-scraper').call({
    date: '2026-03-28',
    maxProducts: 20,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();

for (const product of items) {
    console.log(`#${product.rank} ${product.name} (${product.votesCount} votes)`);
}

cURL

curl -X POST "https://api.apify.com/v2/acts/cryptosignals~producthunt-daily-scraper/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"date": "2026-03-28", "maxProducts": 20}'

Integrations

• Google Sheets — export daily launches to spreadsheets
• Zapier — trigger workflows when top products match your criteria
• Make (Integromat) — build automated trend monitoring pipelines
• Slack / Email — get daily digests of top Product Hunt launches
• Webhooks — send results to any HTTP endpoint in real-time

Pricing

This actor uses pay-per-result pricing. You only pay for products successfully extracted.

Usage	Estimated Cost
20 products	~$0.25-$0.50
50 products	~$0.50-$1.50
100 products (max)	~$1.00-$3.00

Free tier available: Apify's free plan includes $5/month in platform credits.

FAQ

Do I need a Product Hunt API key?

No. This scraper uses Product Hunt's frontend GraphQL API, which doesn't require authentication.

Can I scrape historical dates?

Yes. Provide any past date in YYYY-MM-DD format.

How are products ranked?

Products are returned sorted by vote count (highest first), matching Product Hunt's daily leaderboard.

How often should I run this?

For daily monitoring, schedule a daily run. Product Hunt launches reset each day.

Related Actors

• cryptosignals/google-search-scraper — Search for product reviews
• cryptosignals/linkedin-profile-scraper — Research founders and makers
• cryptosignals/youtube-comments-scraper — Scrape comments on product review videos

---

⭐ Like this actor? Leave a review!

If this scraper saved you time, please leave a quick review on the Apify Store listing. Even a one-line review helps other developers find this tool.

How to review: Go to the actor page -> scroll to Reviews -> click Write a review.