Product Hunt Reviews Scraper

Product Hunt reviews tell you what real users love and hate about a tool, but reading them one card at a time and copying notes into a sheet does not scale. This scraper does the copying for you. Give it a product handle and it walks every review page, pulling the reviewer, the star score, the "what's great" and "what needs improvement" text, the comparison notes, helpful votes, view counts, and post date into one tidy row per review. Run a single product or queue a whole batch.

What you get

Every review becomes one row with the same shape, so your columns line up when you drop the results into a sheet or database. Fields you can read are returned as null when Product Hunt does not show them. Three groups of data per review:

• The review — starRating, likedText, dislikedText, comparisonText, helpfulCount, viewCount, postedAgo
• The reviewer — authorName, authorProfileUrl, authorAvatarUrl, authorReviewsTotal
• The product — productTitle, productHandle, reviewsPageUrl, reviewLink, plus reviewKey and collectedAt

Quick start

1. Hit Try for free and open the input form.
2. Type one or more Product Hunt handles into Product handles (one per line, e.g. linear).
3. Set Order reviews by and Limit to reviewer group if you want to narrow the pull.
4. Press Start, then export the rows as JSON, CSV, Excel, or XML once the run finishes.

Use cases

• Competitor research — pull reviews for rival products and line up what users praise and complain about
• Product feedback mining — read the dislikedText field across hundreds of reviews to find recurring gripes
• Sentiment tracking — re-run on a schedule and watch star scores move as a product ships updates
• Marketing and social proof — gather strong quotes from high-rated reviews for landing pages and decks
• Market analysis — compare ratings and review volume across a category to see who is winning
• Lead research — spot reviewers who flagged a competitor and understand the pain behind a low score

Input

Field	Type	Required	Description
productHandles	array of strings	Yes	Product Hunt handles to scrape reviews for, one per line. Example: slack, linear, raycast.
reviewOrder	string	No	Order reviews come back in: most informative, newest, oldest, highest rated, or lowest rated. Default most_informative.
reviewerFilter	string	No	Keep all reviews or limit to founders or non-founders. Default all.
resultsLimit	integer	No	Cap on reviews gathered per product. Default 50; max 1000.
timeoutSeconds	integer	No	Seconds to wait per request before timing out. Default 45.

Example input

{
    "productHandles": ["slack", "linear", "raycast"],
    "reviewOrder": "most_informative",
    "reviewerFilter": "all",
    "resultsLimit": 50,
    "timeoutSeconds": 45
}

Output

Each review on the page becomes one row, and every field is always present — values Product Hunt does not expose come back as null so your dataset stays rectangular.

Example output

{
    "reviewKey": "413579",
    "authorName": "Stella W.",
    "authorProfileUrl": "https://www.producthunt.com/@stella_w",
    "authorAvatarUrl": "https://ph-avatars.imgix.net/stella-w.png",
    "authorReviewsTotal": 4,
    "starRating": 5,
    "likedText": "Linear keeps the whole team aligned and the keyboard-first flow makes triaging issues genuinely fast.",
    "dislikedText": "The mobile app still lags behind the desktop version on a few power features.",
    "comparisonText": "We moved off Jira because Linear is quicker to set up and far less cluttered day to day.",
    "postedAgo": "4mo ago",
    "helpfulCount": 12,
    "viewCount": 217,
    "productTitle": "Linear",
    "productHandle": "linear",
    "reviewsPageUrl": "https://www.producthunt.com/products/linear/reviews",
    "reviewLink": "https://www.producthunt.com/products/linear/reviews#413579",
    "errorMessage": null,
    "collectedAt": "2026-06-29T12:00:00.000000+00:00"
}

Output fields

Field	Type	Description
reviewKey	string	Numeric ID that uniquely tags this review
authorName	string	Display name of the person who wrote the review
authorProfileUrl	string	Link to the reviewer's Product Hunt profile
authorAvatarUrl	string	Link to the reviewer's profile picture
authorReviewsTotal	integer	How many reviews this person has posted on Product Hunt
starRating	integer	Headline rating from 1 to 5 stars
likedText	string	The reviewer's praise, from the "What's great" block
dislikedText	string	Drawbacks or fixes from "What needs improvement"
comparisonText	string	How the reviewer rates this product against rivals
postedAgo	string	Relative post time as shown on the page, like "4mo ago"
helpfulCount	integer	How many readers marked the review as helpful
viewCount	integer	How many times the review has been seen
productTitle	string	Product name as shown on Product Hunt
productHandle	string	Short URL handle for the product, such as "linear"
reviewsPageUrl	string	Link to the product's reviews page
reviewLink	string	Deep link straight to this review
errorMessage	string	Why a handle failed; null on success
collectedAt	string	ISO 8601 timestamp of when the row was captured

Tips for best results

• Start small. Run one handle with a low resultsLimit first to confirm the output fits your pipeline, then open it up.
• Use the right handle. The handle is the part of the URL after /products/ — producthunt.com/products/linear/reviews means the handle is linear.
• Sort to match the job. Set reviewOrder to lowest rated first when you are hunting for complaints, or highest rated for testimonials.
• Filter by founder. Set reviewerFilter to founders to read maker context, or non-founders for unbiased user opinion.
• Raise timeoutSeconds toward 60 if you scrape large products and see the occasional timeout in the log.

How can I use Product Hunt review data?

How can I use the Product Hunt Reviews Scraper to research a competitor? Add the competitor's handle to productHandles and run it. You get every review with its star score, the liked and disliked notes, and the comparison text in one table. Sort by lowest rated first to surface the pain points your own product can solve, then quote them straight from the dataset.

How can I export Product Hunt reviews to a spreadsheet? Run the scraper, then open the Storage tab and download the dataset as CSV or Excel. Each review is one row with consistent columns — reviewer, stars, the review text, helpful votes, and post date — so it loads cleanly into Sheets, Excel, or any BI tool without cleanup.

How can I track Product Hunt sentiment over time? Schedule the scraper to run on the same handle on a regular cadence. Because starRating, helpfulCount, and postedAgo are captured on every pass, you can chart how a product's ratings and review volume shift after each launch or update.

How can I pull reviews for several products at once? Put one handle per line in productHandles and the scraper works through them in a single run, tagging each row with productTitle and productHandle. That makes it easy to compare ratings and review counts across a whole category in one export.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.