Product Hunt Scraper — Launches, Makers & Leads (Emails, Socials & Funding)

Extract complete Product Hunt launch data — votes, comments, daily/weekly/monthly ranks, topics, the full product website, every social link, funding, employee size, reviews and the makers behind each launch. Optionally turn every launch into a ready-to-contact B2B lead by crawling the product's own website for contact emails, phone numbers and socials.

No login, no API key, no browser — fast JSON extraction straight from Product Hunt's public pages. Scrape by date range, topic or URL, and switch on monitoring mode to capture only new launches.

Why this Product Hunt scraper?

Most Product Hunt scrapers grab the name, tagline and a vote count, then stop. This actor reads Product Hunt's full embedded data and ships the richest dataset in the category — including the product website and maker contacts that make the data actually actionable for sales and research.

Data	Typical scrapers	This actor
Name, tagline, votes, comments	✅	✅
Daily / weekly / monthly rank	partial	✅
Topics & categories	partial	✅
Product website URL	❌	✅
All socials (X, LinkedIn, GitHub, Instagram, Facebook, AngelList, Threads…)	❌	✅
Funding amount, employee size, "was in Y Combinator"	❌	✅
Followers, review count & rating	❌	✅
Makers (name, username, profile, avatar, badges)	❌	✅
Maker/company contact emails + phone (from the product website)	❌	✅ opt-in
Lead score (0–100) per launch	❌	✅
Monitoring mode — only new launches	❌	✅

Use cases

• Lead generation — every launch is a freshly funded, in-market company. Capture the website, makers and contact emails, score them, and push straight into your CRM or outreach sequence.
• Startup & market intelligence — track new products by topic (AI, dev tools, SaaS, fintech) with votes, funding and YC signals to spot trends before they scale.
• Competitor monitoring — watch your category daily and get alerted the moment a competitor or adjacent tool launches.
• Investor & deal sourcing — surface newly launched, high-traction products with funding and team-size signals.
• Recruiting — find makers and fast-growing startups by topic, with profiles and links straight from each launch.
• Content & newsletters — power "best new products" digests with structured, ranked launch data.

How to use

1. Sign up for Apify — the free plan is enough to try this actor.
2. Open the Product Hunt Scraper, set how far back to scrape (or a date range / topics), and click Start.
3. Watch launches stream into the dataset table.
4. Export as JSON, CSV, Excel, XML or RSS — or pull results programmatically via the Apify API.

Input

{
    "daysBack": 3,
    "topics": ["artificial-intelligence", "developer-tools"],
    "includeProductDetails": true,
    "enrichMakerEmails": true,
    "monitorMode": false,
    "maxItems": 0
}

• daysBack (default 7) — scrape the daily leaderboards for the last N days (including today). The simplest control.
• dateFrom / dateTo (YYYY-MM-DD) — scrape an explicit range of daily leaderboards; overrides daysBack.
• topics — also scrape Product Hunt topic pages by slug (artificial-intelligence, saas, marketing, …).
• startUrls — also scrape specific PH URLs: leaderboards, topic pages, or individual /products/<slug> / /posts/<slug> pages.
• includeProductDetails (default true) — open each launch's product page for website, full description, all socials, funding, employee size, reviews, categories and makers.
• enrichMakerEmails (default false) — crawl each product's own website (home + contact/about) for emails, phone and extra socials. PH never exposes emails — this is the only way to get them.
• monitorMode (default false) — output only launches not seen in previous runs (see Automate & schedule).
• maxItems (default 0 = no limit) — cap the number of launches, handy for quick test runs.
• maxConcurrency (default 8) — parallel page fetches.
• proxyConfiguration — proxy settings (Apify proxy by default).

Output

One record per launch (type: "launch"):

{
    "type": "launch",
    "postId": "1166716",
    "productId": "1131568",
    "name": "Firma.dev",
    "tagline": "E-signatures API for your app averaging ~3¢ per envelope",
    "description": "At €0.029 per envelope, Firma.dev runs ~99% cheaper than legacy e-sign tools…",
    "url": "https://www.producthunt.com/posts/firma-dev-2",
    "productUrl": "https://www.producthunt.com/products/firma-dev",
    "websiteUrl": "https://firma.dev",
    "votesCount": 352,
    "commentsCount": 43,
    "reviewsCount": 12,
    "reviewsRating": 5,
    "followersCount": 210,
    "dailyRank": 1,
    "weeklyRank": 14,
    "monthlyRank": 32,
    "featuredAt": "2026-06-12T00:01:00-07:00",
    "topics": [{ "id": "88", "slug": "api-1", "name": "API" }, { "id": "267", "slug": "developer-tools", "name": "Developer Tools" }],
    "categories": ["Developer Tools", "API"],
    "pricing": "freemium",
    "isFree": false,
    "fundingAmount": null,
    "employeeSize": "1-10",
    "wasInYCombinator": false,
    "makers": [
        { "name": "Chris Davis", "username": "chris_davis23", "profileUrl": "https://www.producthunt.com/@chris_davis23", "avatarUrl": "https://ph-avatars.imgix.net/…" }
    ],
    "socials": { "twitter": "https://x.com/firmadev", "github": "https://github.com/firma-dev" },
    "emails": ["hello@firma.dev"],
    "phones": [],
    "logoUrl": "https://ph-files.imgix.net/…",
    "thumbnailUrl": "https://ph-files.imgix.net/…",
    "screenshots": ["https://ph-files.imgix.net/…"],
    "leadScore": 78,
    "scrapedAt": "2026-06-13T12:00:00.000Z"
}

What to expect (field coverage)

Product Hunt is maker-entered data, so some fields are present only when the maker filled them in.

Field group	Always present	Usually present	Present when published
Launch core (name, tagline, votes, comments, ranks, topics, timestamps)	✅	—	—
Product detail (website, description, socials, categories)	—	✅ with includeProductDetails	—
Makers, reviews, followers	—	✅ ~90%	—
Funding, employee size, YC flag	—	—	when the maker added them
emails / phones	—	—	with enrichMakerEmails, when the website lists them

A blank field means the maker didn't publish it — not that scraping failed. Nothing is dropped, so you always get the richest dataset available.

Automate & schedule

Run this actor on autopilot and pull results into your own stack:

• Apify API — start runs, fetch datasets, and manage schedules over REST.
• apify-client for JavaScript and apify-client for Python — official SDKs.
• Schedules — run it daily to capture every new launch in your category for newsletters and lead pipelines.
• Webhooks — trigger downstream actions (CRM import, Slack alert, email sequence) the moment a run finishes.

Monitoring mode + Schedules is the recommended combo: set monitorMode: true and a daily Schedule. The schedule starts each run; monitoring mode remembers which launches were already emitted and outputs only the new ones — so they never conflict, and every run delivers fresh data ready to push to your CRM.

import { ApifyClient } from 'apify-client';

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

const run = await client.actor('scrapesage/product-hunt-scraper').call({
    daysBack: 1,
    includeProductDetails: true,
    enrichMakerEmails: true,
    monitorMode: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} new launches & leads`);

Integrate with any app

Connect the dataset to 5,000+ apps — no code required:

• Make — multi-step automation scenarios.
• Zapier — push new launch leads straight into your CRM.
• Slack — get notified when a monitored topic gets a new launch.
• Google Drive / Sheets — auto-export every run to a spreadsheet.
• Airbyte — pipe results into your data warehouse.
• GitHub — trigger runs from commits or releases.

Use with AI assistants (MCP)

The output is clean, LLM-ready JSON. Call this actor from Claude, ChatGPT, or any agent framework through the Apify MCP server — ask your assistant to "find today's top AI launches on Product Hunt with their websites and maker contacts" and let it run the scraper for you.

More scrapers from scrapesage

Build a complete B2B lead-generation & market-intelligence stack:

• LinkedIn Jobs Scraper — job postings as hiring-intent signals from the companies you find.
• Facebook Ad Library Scraper — competitor ad intelligence on Meta & Instagram.
• Google Ads Transparency Scraper — who's advertising what on Google.
• Eventbrite Scraper — events plus organizer leads (ticket prices, emails, socials).
• Sched Conference Scraper — speakers, sessions and sponsors from conference sites.
• Whova Event Scraper — attendees, sessions, speakers and sponsors from Whova event apps.
• Swapcard Exhibitor Scraper — exhibitor lists, speakers and contacts from Swapcard-powered events.
• Bark Listing Scraper — service-provider leads from Bark.
• Airbnb Scraper — listings, prices and availability.

Tips

• Daily lead pipeline: set daysBack: 1, enrichMakerEmails: true, monitorMode: true and a daily Schedule — you'll get only that day's new launches, complete with contact emails.
• Topic focus: add topics (e.g. artificial-intelligence, saas) to track specific categories instead of the whole leaderboard.
• Cost control: keep enrichMakerEmails off for pure discovery; turn it on only when you need contactable leads (it adds a few requests per product website).
• Backfill: use dateFrom/dateTo to pull months of historical launches in one run.

FAQ

How do I scrape Product Hunt without the API? This actor reads Product Hunt's public pages directly — no API key, OAuth app or login needed. You get the same (and richer) data the website shows.

Where do the emails come from? Never from Product Hunt (it doesn't publish emails). With enrichMakerEmails on, the actor visits the product's own public website and extracts publicly listed contact emails — the same thing a human visitor would see.

Can I export to Google Sheets, CSV or Excel? Yes — one click in the dataset view, or automatically on every run via the Google Drive integration.

How do I get only new launches? Turn on monitorMode and create a daily Schedule. Each run outputs only launches not seen before.

Does monitoring mode conflict with the Apify scheduler? No. The scheduler simply starts runs on a cadence; monitoring mode remembers which launches were already emitted and filters them out. They work together.

A field is null — why? Some makers don't publish a website, funding or socials. Fields are blank only when the data doesn't exist, not because the scraper skipped them.

Is scraping Product Hunt legal? This actor collects publicly available data only. You're responsible for using the data in compliance with applicable laws (e.g. GDPR/CCPA for personal data) and Product Hunt's terms.

Need help?

Open an issue on the actor's Issues tab, or visit the Apify help center. Feature requests are welcome — this actor is actively maintained.