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SKILL FILE

Scrape Product Hunt with AI

Extract Product Hunt launches, upvotes, maker profiles, and trending products using Apify and Claude Code.

500K+ products launched on Product Hunt
800 products scraped per minute
$0.20 per 1,000 products extracted
Download Skill File ↓

How scraped Product Hunt data flows across your company

One scrape generates intelligence for every department — automatically

Scrape Product Hunt Launches, upvotes, makers, categories
1 Configure Search
2 Apify Actor Runs
3 Data Analyzed
4 Stored in CRM
Sales
  • Find new competitors early
  • Identify potential partners
  • Track maker outreach targets
  • Monitor launch announcements
Marketing
  • Launch strategy research
  • Category trend analysis
  • Community feedback mining
  • Launch timing optimization
Growth
  • New market entrant tracking
  • Category growth monitoring
  • Upvote pattern analysis
  • Maker network mapping
CRM
  • Product profiles stored
  • Maker contacts indexed
  • Launch data catalogued
  • Category trends logged
Competitor Tracker
Launch Strategy Guide
Market Map
Category Trend Report
Events Tracked
Product launches tracked
Maker networks mapped
Category trends scored
Replaces PH Pro Subscription
$20/mo $1/mo
$228/yr saved
Scrape Product Hunt Launches, upvotes, makers, categories
1
Configure Search Categories, date ranges, or keywords defined
2
Apify Actor Runs PH scraper extracts launches and maker data — $0.20/1K
3
Data Analyzed Launches ranked, categories trended, makers profiled
4
Stored in CRM Startup intelligence pushed to Neon database
Sales
  • Find new competitors early
  • Identify potential partners
  • Track maker outreach targets
  • Monitor launch announcements
Marketing
  • Launch strategy research
  • Category trend analysis
  • Community feedback mining
  • Launch timing optimization
Growth
  • New market entrant tracking
  • Category growth monitoring
  • Upvote pattern analysis
  • Maker network mapping
CRM
  • Product profiles stored
  • Maker contacts indexed
  • Launch data catalogued
  • Category trends logged
Content Outputs
Launch Strategy Guide from marketing
Competitor Tracker from sales
Category Trend Report from growth
Market Map from marketing
Everything Tracked
Product launches tracked
Maker networks mapped
Category trends scored
Replaces PH Pro Subscription
$20/mo $1/mo
$228/yr saved

Cancel your Product Hunt Pro subscription

CANCEL THIS

Product Hunt Pro

$20/mo
  • × Subscription fees
  • × Data locked in their dashboard
  • × Per-seat pricing
  • × Export limits
vs
BUILD THIS

SoloStack + Claude Code

$1/mo
  • Pay-per-use, no subscription
  • Your data in your repo
  • Zero vendor lock-in
  • Unlimited exports
Save $228/year

What this skill file teaches Claude

Drop one markdown file into your repo. Claude Code learns how to run this entire workflow.

1

Product Launch Data

Extract product name, tagline, description, website URL, upvotes, comments, and launch date.

2

Maker Profiles

Pull maker/founder profiles with Twitter handles, websites, and other products launched.

3

Category Trends

Track which product categories are trending — AI tools, developer tools, marketing, etc.

4

Comment Analysis

Extract comments to understand community reception and identify feature requests.

5

Launch Pattern Analysis

Identify optimal launch days, upvote velocity patterns, and what makes a #1 Product of the Day.

Apify Actor: apify/producthunt-scraper · ~$0.20 per 1,000 products

Build it with plain English

Tell Claude Code what to do. It handles the rest.

claude — solostack/
you: |
Scraping CRM & Sales launches (6 months)...

✓ 234 product launches found
✓ Average upvotes: 189
✓ #1 launch: AICloser (2,345 upvotes)
✓ Most common features: AI-powered, free tier, integrations
✓ 67% launched on Tuesday-Thursday

Launch data saved to ph-crm-sales.json
you: |
Extracting top 100 launches this month...

✓ 100 products extracted
✓ Top category: AI/ML (38 products)
✓ 2nd: Developer Tools (22 products)
✓ Average upvotes: 567
✓ #1 of the month: 4,123 upvotes

Top launches saved to ph-top-100.json
you: |
Finding AI tool makers with 500+ upvotes...

✓ 156 qualifying launches
✓ 134 unique makers
✓ Most prolific: @alexbuilds (4 AI launches)
✓ Average maker followers: 890
✓ 89 have Twitter profiles

Maker list saved to ph-ai-makers.json

What you can build with this

Competitive early warning

Monitor Product Hunt for new launches in your category. Catch competitors before they gain traction. Track weekly launches and get alerts for relevant products.

Launch strategy research

Analyze successful launches in your category — optimal day, tagline patterns, maker promotion strategies, and comment engagement tactics.

Maker outreach

Build lists of founders who launched products in related categories. Extract Twitter handles and websites for partnership or cross-promotion outreach.

Market sizing

Count launches per category over time to identify growing markets. Categories with increasing launch volume signal rising founder interest and market demand.

Things to know

!

Product Hunt's API has rate limits. The Apify actor handles pagination and rate limiting, but very large historical scrapes may take time.

!

Upvote counts can be inflated by launch day promotion campaigns. Use comment count and comment quality as a secondary engagement signal.

!

Product Hunt skews heavily toward B2B SaaS, developer tools, and AI products. Consumer products and non-tech categories have lower coverage.

Get the full skill file

Everything above is 80% of the skill file. Download the complete version with full implementation details, agent prompts, and ready-to-run scripts.

Common questions

Product Hunt provides a public API for accessing launch data. Using the API is explicitly allowed. Scraping the website directly is a gray area but Product Hunt's data is publicly accessible. Use data for market research and competitive analysis.
Yes. Product Hunt has data going back to 2013. The scraper can access historical launches by date range. This is useful for analyzing long-term category trends and identifying when competitor products launched.
Upvote counts are real but can be inflated by organized upvoting campaigns. Products with high upvotes but low comments may have artificial engagement. The comment count and comment quality are more reliable engagement signals.
Schedule weekly scrapes of your product categories. Track new launches, average upvotes, and recurring makers. Build a dashboard in your CRM to visualize category trends over time. This gives you early warning of new competitors and market shifts.
Product Hunt profiles often include Twitter handles, personal websites, and sometimes email addresses. The scraper extracts all available profile data. For outreach, Twitter DMs or website contact forms are the most effective channels for PH makers.

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