A Product Hunt launch is ranked within its day, yet its points keep climbing after the day closes. Our Product Hunt scraper records rank, points and comments as they change.
Plans from €169/month · Free project assessment · Reply within 1 business day
Tell us the slice of Product Hunt you need - every launch on the daily leaderboard, the products in chosen categories and topics, or a watchlist of products and their rivals - and how often to refresh it. We build the crawler, run it on your schedule and repair it when the layout changes. Product Hunt draws much of each page with scripts and screens automated traffic, so we take care of rendering, pacing, proxy rotation and CAPTCHAs ourselves instead of leaving them to you.
You receive one row per launch and one per product, keyed on the product slug, with field documentation. Plans start from EUR 169 a month, or EUR 199 for a one-time extract.
Product Hunt separates the product from its launches. A product lives at /products/ plus a slug and keeps one page for its whole life; each launch is a dated event under it. A long-lived product such as Notion lists a long run of them, each with its own name, tagline and rank, so we keep both levels and join them on the slug.
Makers, hunters, reviewers and commenters are people with public profiles. Their names, usernames and comment texts are left out by default; products, companies and launches stay the subject.
The leaderboard is the spine of the dataset. It runs as Daily, Weekly, Monthly and Yearly views with a Featured or All switch, and every period has its own address: a daily board under /leaderboard/daily/ with year, month and day, a weekly one numbered by week of the year. Each row carries rank, name, tagline, launch tags, comment count and points, so walking the archive day by day rebuilds the launches of any period you pick.
The rank is fixed by the score at the end of the period, while the points beside it keep moving, so a launch can sit below one with fewer points. Both are stored, and neither is derived from the other.
Category pages such as No-code Platforms and topic pages such as Open Source list products with rating, review count, categories, platform tags and the Used by count, under a short AI-written summary of the field. Product pages add Alternatives, Awards, Built with and a Forum space under /p/.
Repeat runs matter because points and comments keep rising after launch day. A daily refresh through the first week, then weekly, captures the curve.
Product Hunt is where makers of software, AI tools and some hardware put a new product in front of an early-adopter audience on a single day. The site describes itself as products ranked daily by the community: launches go live, collect upvotes and comments, and each day closes into a ranked leaderboard. Its About page names Ryan Hoover as founder.
The site is organised around products, not posts. One product page gathers every launch its team has made, so a single record can hold years of launches, ranks and awards. Around it sit Best Products, a tree of categories from Productivity and Engineering & Development to AI Agents, LLMs and Physical Products; topics that work as tags; Launches, with the leaderboard, the Launch archive and the Launch Guide; News, with the newsletter and Stories; and Forums, where a product can have its own space.
Recognition comes in layers: daily, weekly and monthly launch awards, the Top Product badge, and the annual Golden Kitty Awards, whose categories change from year to year. Reviews stand apart from launches, split into Founder Reviews and Other Reviews, each counted separately, and every review is rated on Ease of use, Reliability, Value for money and Customization.
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →Product Hunt is an early read on what is being built and how the first audience reacts. Its fields turn that into numbers.
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ScrapeIt is a managed data collection company. We write and maintain the crawlers, run them on your schedule and hand over the result, so your team works with the data rather than the scraper. Launch platforms and community sites suit the way we work: dated events, counters that move, and records that need history to mean anything. Ask for a free project assessment or a sample, and take delivery as CSV, Excel, JSON, a JSON feed, Amazon S3 or Google Drive.
Yes. The ScrapeIt Product Hunt API returns product name, tagline, launch tags, points, comment count and Day Rank as JSON from an endpoint we host, updated as often as your plan schedules it. The same rows come as CSV or XLSX files, a JSON feed or a load into your database. An MCP server is available on request.
Yes. Product pages, launches, the leaderboards, category and topic listings and reviews are open to any visitor without an account. We collect only publicly available data - everything a visitor can see on Product Hunt - and we collect it legally. Personal details of makers and commenters are left out by default.
Yes. Points and comment counts keep rising after launch day, and a product collects new launches, awards and reviews for years. Scheduled runs store every launch with its capture date, so you get the points curve over the first days, the final Day Rank and the place on the weekly leaderboard, and each later launch of the same product joined on its slug.
Yes. We deliver each product's average rating and review count, the pros and cons tags with how often each is mentioned, and per review the four category ratings, the What's great, What needs improvement and vs Alternatives text, the Helpful count and the age of the review. Reviewer names are left out by default; whether a review sits under Founder Reviews or Other Reviews is kept as a column.
Every product the category or topic lists, with rating, review count, categories, platform tags and Used by count, followed into each product page for launches, awards, Similar Products and the Built with stack. For No-code Platforms that means one table running from Notion, Bubble and Zapier down the list. It arrives as CSV, Excel or JSON, or in Amazon S3, SFTP or Google Cloud Storage.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Product Hunt data from €169/month. Free project assessment, reply within 1 business day.
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