Product Hunt Scraper — Launches, Makers, Votes, Ratings & Reviews

Scrape Product Hunt at scale and turn every launch into clean, structured data. This Product Hunt scraper extracts the full public profile of any product — name, tagline, website, logo, screenshots, upvotes, comment counts, aggregate rating, topics, the makers/founders behind it, and real user reviews — from a product slug, a product URL, a topic page, or a daily leaderboard date. No login, no coding, no API key required.

Export to JSON, CSV, Excel, or API.

Built for startup analysts, VC and angel scouts, growth and competitive-intelligence teams, recruiters sourcing top makers, and newsletter/media operators who need a daily feed of Product Hunt data without touching the website by hand.

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🔎 Why scrape Product Hunt?

Product Hunt is where new software, AI tools, and startups launch first. Every day thousands of makers ship products, collect upvotes, rack up comments, and earn reviews — making it one of the richest public signals of what's being built and what's gaining traction. But that signal is locked inside an infinite-scroll web app with no public bulk export, and Product Hunt deprecated easy access to much of its data behind authentication and rate limits. Copy-pasting launches, makers, and vote counts one page at a time does not scale.

This Product Hunt scraper does it for you. Point it at a topic, a list of product handles, a set of URLs, or a leaderboard day, and it returns a normalized record per product — the same structured fields Product Hunt serves to Google (JSON-LD) plus inline app-state for live vote and comment counts, topics, and makers. You get analysis-ready Product Hunt data in seconds, refreshed whenever you re-run it.

Common reasons people scrape Product Hunt:

• Track daily and weekly launches in a category to spot trending products early.
• Build a startup / product database with taglines, websites, categories, and launch dates.
• Source founders and makers — names, usernames, avatars, and profile URLs — for outreach or recruiting.
• Monitor competitors' upvotes, comments, and rating trajectory over time.
• Mine user reviews (star ratings + full review text) for sentiment and product feedback.
• Power a newsletter or trend report with a fresh feed of top launches and metadata.
• Feed AI/LLM pipelines and market research with clean, deduplicated launch data.

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✨ What this Product Hunt scraper does

• ✅ Four ways to target products — pick topics (categories), list product slugs/handles, paste any Product Hunt URLs, or pull a daily leaderboard date. Mix and match them in a single run.
• ✅ Automatic discovery + pagination — topic pages, leaderboards, and start URLs are crawled for every /products/<slug> link, then each unique product is fetched and parsed. Results are de-duplicated by slug so you never get the same product twice.
• ✅ Rich per-product fields — captures identity (name, slug, Product Hunt URL, website URL, tagline), visuals (logo image + all high-res imgix screenshots), engagement (upvote count, comment count, aggregate rating 1–5 with rating count), categorization (Product Hunt topics + application category + operating system), and launch metadata (date published, date last modified).
• ✅ Makers / founders — name, avatar image, and profile URL for every maker credited on the launch, ready for lead generation and sourcing.
• ✅ User reviews — for each review: star rating, full review body, author name, author profile URL, author avatar, and date. Toggle reviews off for faster, lighter runs.
• ✅ No API key, no login — pure HTTP extraction of the public JSON-LD + app-state. A Firefox TLS fingerprint clears Product Hunt's Cloudflare challenge, with fresh sessions, retries, and optional proxy rotation for reliability.
• ✅ Export anywhere — download as JSON, CSV, or Excel, or pull via the Apify API. Pre-built dataset views unwind makers and reviews into flat, one-row-per-item tables.

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🎯 Use cases

• Startup & product intelligence — maintain a live database of new launches by topic, with taglines, websites, categories, and vote counts.
• Venture capital & angel sourcing — discover founders and their products before they break out; enrich a deal pipeline with maker profiles.
• Competitive monitoring — watch a competitor's Product Hunt page over time: upvotes, comments, rating, and review sentiment.
• Recruiter & talent sourcing — find the makers behind top-rated products in a category and reach them via their profile.
• Growth & marketing research — survey an entire space (e.g. all Artificial Intelligence or Developer Tools launches) to size a market and find positioning gaps.
• Media, newsletters & trend reports — auto-generate a daily or weekly digest of top launches with logos, taglines, and metrics.
• Review & sentiment analysis — pull user reviews and ratings to understand what customers love or dislike about products in your category.
• AI / data pipelines — feed clean, structured Product Hunt data into LLMs, dashboards, or a data warehouse.

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📥 Input

Provide one or more targeting methods. Leave everything empty and the scraper returns a fresh mixed sample of popular launches as a demo.

Field	Type	Description
topicSlugs	array	One or more Product Hunt topics (categories) to pull the newest launches from — e.g. artificial-intelligence, productivity, developer-tools, saas, fintech. Great for surveying an entire space.
productSlugs	array	Specific product handles — the last part of a product URL (e.g. notion, linear, vercel). Look up as many as you like.
startUrls	array	Advanced. Any Product Hunt links — product pages, topic pages, or daily leaderboards. The scraper collects products from each.
leaderboardDates	array	Advanced. Top products launched on specific days, in YYYY/M/D format with no leading zeros (e.g. 2026/5/17).
scrapeReviews	boolean	Include each product's user reviews (rating, text, author). Default true; turn off for faster runs.
maxRecords	integer	Maximum number of products to collect. Default 100; set 0 for no limit.
requestDelay	integer	Advanced. Milliseconds to pause between page requests (default 800).
maxConcurrency	integer	Advanced. How many pages to fetch in parallel (default 4).
proxyConfiguration	object	Apify Proxy settings. Datacenter proxy is used by default; switch to Residential (US) only if you hit challenges.

Example input

{
  "topicSlugs": ["artificial-intelligence", "productivity"],
  "productSlugs": ["notion", "linear", "vercel"],
  "scrapeReviews": true,
  "maxRecords": 100,
  "proxyConfiguration": { "useApifyProxy": true }
}

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📤 Output

Each product becomes one structured record. Here is a realistic output item (trimmed):

{
  "slug": "vercel",
  "productUrl": "https://www.producthunt.com/products/vercel",
  "name": "Vercel",
  "tagline": "Vercel provides the developer tools and cloud infrastructure to build, scale, and secure a faster, more personalized web.",
  "websiteUrl": "https://vercel.com",
  "image": "https://ph-files.imgix.net/593ff5e2-....jpeg?auto=format",
  "screenshots": [
    "https://ph-files.imgix.net/0c9e21f4-....webp?auto=format&fit=crop",
    "https://ph-files.imgix.net/642e3dec-....png?auto=format&fit=crop"
  ],
  "applicationCategory": "Design Tools",
  "operatingSystem": "Web",
  "datePublished": "2022-04-14T07:51:27-07:00",
  "dateModified": "2026-10-25T05:25:16-07:00",
  "aggregateRating": { "ratingValue": 4.97, "ratingCount": 1102, "bestRating": 5, "worstRating": 1 },
  "votesCount": 341,
  "commentsCount": 160,
  "topics": [
    { "slug": "design-tools", "name": "Design Tools" },
    { "slug": "graphics-design", "name": "Graphics & Design" }
  ],
  "makers": [
    { "name": "Railly Hugo", "image": "https://ph-avatars.imgix.net/....jpeg", "profile": "https://www.producthunt.com/@railly_hugo" }
  ],
  "reviews": [
    {
      "rating": 4,
      "body": "I choose Vercel when I want the fastest path from a Next.js repo to a live product...",
      "author": "Abhishek Patel",
      "authorProfile": "https://www.producthunt.com/@abhishekpatel",
      "authorImage": "https://ph-avatars.imgix.net/....jpeg",
      "datePublished": "2025-08-12T10:04:00-07:00"
    }
  ],
  "scrapedAt": "2026-10-25T16:00:00.000Z"
}

Field reference

Field	Description
slug	Product Hunt product handle (last path segment).
productUrl	Canonical Product Hunt product URL.
name	Product name.
tagline	Short product tagline / description.
websiteUrl	The product's external website.
image	Product logo (imgix CDN URL).
screenshots	Array of high-res screenshot URLs.
applicationCategory	Application category label.
operatingSystem	Supported OS/platform tag — present when set (e.g. Web, iOS).
datePublished	When the product was first launched/listed.
dateModified	When the Product Hunt page was last updated.
aggregateRating	Object: ratingValue (1–5), ratingCount, bestRating, worstRating. Present when the product has ratings.
votesCount	Current upvote count.
commentsCount	Current comment count.
topics	Array of { slug, name } Product Hunt topics/categories.
makers	Array of makers: { name, image, profile } (plus username when sourced from app-state).
reviews	Array of reviews: { rating, body, author, authorProfile, authorImage, datePublished }. Empty when scrapeReviews is off or the product has no reviews.
scrapedAt	ISO timestamp of when the record was scraped.

In a verification run, core fields (slug, productUrl, name, tagline, websiteUrl, image, screenshots, applicationCategory, datePublished, dateModified, aggregateRating, votesCount, commentsCount, topics, makers, reviews) populated at 100%; operatingSystem is data-dependent (populated only when the product sets a platform tag).

The dataset also ships with ready-made Makers and Reviews views that unwind those arrays into flat, one-row-per-item tables — ideal for CSV exports and CRM imports.

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🔁 Pagination & scale

You do not manage pages manually. For every topic, leaderboard date, and discovery start URL, the scraper fetches the listing and harvests every /products/<slug> link, then visits each unique product page to extract the full record. All slugs are de-duplicated, so a product discovered from multiple sources is scraped only once.

Scale is controlled by maxRecords (default 100, set 0 for unlimited) together with the number of topics, slugs, URLs, and leaderboard dates you supply — so you can pull anything from a single competitor to thousands of launches across many topics. maxConcurrency and requestDelay tune throughput against Product Hunt's rate limits. An empty run is safely capped to a 100-product sample so it stays fast and cheap.

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⚙️ How to use

1. Open the actor on the Apify Console and fill in the input — pick topics, paste product handles/URLs, or a leaderboard date.
2. (Optional) Toggle scrapeReviews, set maxRecords, and adjust concurrency/delay.
3. Click Start and watch records stream into the dataset in real time.
4. Download results as JSON, CSV, or Excel, or fetch them from the Apify API.
5. Run it on a schedule (e.g. daily) to keep a fresh feed, and integrate via Make, Zapier, Google Sheets, or a webhook to push new launches straight into your stack.

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💡 Tips

• Combine topicSlugs + leaderboardDates for the widest coverage of a space on a given day.
• For a single competitor lookup, pass one entry in productSlugs and set maxRecords: 1.
• Need historical data? Loop several leaderboardDates — each day yields a batch of that day's top launches.
• Turn scrapeReviews off when you only need launch metrics and makers — runs are noticeably faster and lighter.
• Datacenter proxy handles Product Hunt's basic Cloudflare challenge; only switch to Residential (US) if you run very large jobs and start seeing challenges.
• Use the pre-built Makers and Reviews dataset views to export flat lead lists without post-processing.

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❓ FAQ

Is scraping Product Hunt legal? This scraper collects only public data that Product Hunt already exposes to search engines and anonymous visitors (JSON-LD and page app-state). It does not log in or access private data. As always, review Product Hunt's Terms of Service and use the data responsibly and in compliance with applicable laws.

Do I need a Product Hunt API key or account? No. There is no login and no API key. The actor fetches public product pages directly over HTTP.

Is there a Product Hunt API, and why use a scraper instead? Product Hunt's official API is gated behind authentication, OAuth, and strict rate limits, and it does not give you a simple one-click bulk export to CSV/Excel. This Product Hunt scraper gives you clean, deduplicated records with no setup.

How many products can I scrape and how fast? As many as you target. Throughput depends on maxConcurrency and requestDelay; a typical run returns dozens to hundreds of fully enriched products in under a minute, and you can lift maxRecords to 0 for larger jobs.

Do I need proxies? Apify's datacenter proxy is enabled by default and clears Product Hunt's basic Cloudflare challenge thanks to a Firefox TLS fingerprint with automatic retries. Switch to Residential (US) only if you hit challenges on very large runs.

What export formats are supported? JSON, CSV, Excel, and the Apify API/webhooks. The dataset includes flattened Makers and Reviews views for easy spreadsheet exports.

How fresh is the data? It's scraped live each run, so vote counts, comment counts, ratings, and reviews reflect the product page at the moment of scraping (scrapedAt records exactly when).

Can I filter by topic or category? Yes. Use topicSlugs to pull launches from a specific topic (AI, Productivity, Developer Tools, SaaS, Fintech, and more), or leaderboardDates to target a specific day.

Why did one of my product slugs return nothing? The handle may be misspelled or the page may not expose product JSON-LD. The scraper gracefully skips non-matching slugs and continues with the rest — check the slug against its Product Hunt URL.

Can I get the makers and reviews separately? Yes — the dataset's Makers and Reviews views unwind those arrays into one-row-per-item tables, perfect for lead lists and sentiment datasets.

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🔗 Related scrapers

Pair this with our other developer-intel and lead-generation scrapers:

• GitHub Developer Scraper — Find Devs by Location & Language
• GitHub Repository Scraper — Search Repos by Topic & Stars
• GitHub Repo Audience Scraper — Forkers, Watchers, Contributors
• GitHub Followers Scraper — Developer Leads
• WordPress Plugin & Theme Scraper — Installs, Downloads, Ratings
• npm Package Scraper — Downloads, Maintainers & Metadata

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Ready to turn Product Hunt into structured data? Hit Start, pick a topic or paste a few product handles, and export clean Product Hunt data — launches, makers, votes, ratings, and reviews — in seconds.

📅 Changelog & Maintenance

Last updated: 2026-10-25 — Actor verified against the live site (all core fields at 100% coverage). Topic/maker name decoding hardened so labels like "Graphics & Design" render cleanly. Data pipeline tested for structure, quality, and freshness.