# Product Hunt Reviews Scraper (`kawsar/product-hunt-reviews-scraper`) Actor Product Hunt Reviews Scraper collects user ratings, written feedback, and reviewer metadata from any Product Hunt product page, so you can track sentiment and run competitive analysis without manual work. - **URL**: https://apify.com/kawsar/product-hunt-reviews-scraper.md - **Developed by:** [Kawsar](https://apify.com/kawsar) (community) - **Categories:** Automation, Developer tools, Other - **Stats:** 3 total users, 2 monthly users, 66.7% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Product Hunt Reviews Scraper Product Hunt Reviews Scraper collects user reviews from any Product Hunt product page. Give it a product slug and it returns reviewer names, star ratings, written feedback, view counts, and helpful vote totals for every review it finds. Works with any product listed on Product Hunt. ### What it collects For each review: - Reviewer name and profile URL - Reviewer avatar URL - Overall star rating (1-5) - "What's great" section text - "What needs improvement" section text - "vs Alternatives" comparison text - Review date (relative, as shown on the page) - Helpful vote count - View count - Product name, slug, and URL - Direct review URL ### How to use it #### Find your product slug The slug is the part of the URL after `/products/`. For example: - `https://www.producthunt.com/products/figma/reviews` → slug is `figma` - `https://www.producthunt.com/products/notion/reviews` → slug is `notion` #### Input | Field | Required | Description | |---|---|---| | Product slug | Yes (or batch) | Single product handle, e.g. `figma` | | Product slugs | Yes (or single) | Multiple handles, one per line | | Max reviews | No | Reviews to collect per product (default 100, max 1000) | | Request timeout | No | Seconds per request (default 30) | #### Example input ```json { "productSlug": "figma", "maxItems": 200 } ```` Batch scraping: ```json { "productSlugs": ["figma", "notion", "chatgpt"], "maxItems": 100 } ``` #### Example output ```json { "reviewId": "413579", "reviewerName": "Stella.W", "reviewerUrl": "https://www.producthunt.com/@stellawwwwwww", "reviewerAvatarUrl": "https://ph-avatars.imgix.net/...", "reviewerReviewCount": 4, "rating": 5, "reviewTextPros": "Figma is fantastic because it enables real-time collaboration and design iteration in a way that fundamentally changes how teams work together.", "reviewTextCons": "Performance can degrade in very large or complex files.", "reviewVsAlternatives": "We chose Figma because it enables real-time collaboration, reduces setup friction, and keeps everything in one place.", "reviewDateRaw": "4mo ago", "helpfulVotes": 1, "viewsCount": 217, "productName": "Figma", "productSlug": "figma", "productUrl": "https://www.producthunt.com/products/figma/reviews", "reviewUrl": "https://www.producthunt.com/products/figma/reviews#413579", "scrapedAt": "2026-04-20T10:30:00+00:00" } ``` ### Common use cases **Competitive analysis** - Pull reviews for competing products and compare what users praise or criticize across the board. **Sentiment tracking** - Monitor how user opinion shifts over time as products ship new features. **Research and reporting** - Export review data to CSV or feed it into your own dashboards and tools. **Lead generation** - Find users who reviewed a competitor's product with low ratings and understand their pain points. ### Pagination The actor fetches pages of reviews automatically, using `?page=N` URL parameters. It stops when it hits your `maxItems` limit or runs out of new reviews. ### Output formats Results are saved to the Apify dataset and can be exported as JSON, CSV, XML, or Excel from the Storage tab after the run completes. ### Error handling If a product slug is not found or a page fails to load, the actor logs the error and continues to the next slug. It never crashes the entire run for a single failure. ### Tips - Product slugs are case-sensitive. Use lowercase as they appear in the URL. - If you get 0 results, double-check the slug against the live Product Hunt URL. - For products with thousands of reviews, set a higher `maxItems` and expect the run to take a few minutes. # Actor input Schema ## `productSlugs` (type: `array`): Scrape reviews for multiple products at once. Enter one slug per line. ## `sortBy` (type: `string`): Order in which reviews are returned. ## `reviewType` (type: `string`): Filter reviews by the type of reviewer. ## `maxItems` (type: `integer`): Maximum number of reviews to collect per product. ## `requestTimeoutSecs` (type: `integer`): Per-request timeout in seconds. ## Actor input object example ```json { "productSlugs": [ "figma", "notion", "chatgpt" ], "sortBy": "most_informative", "reviewType": "all", "maxItems": 25, "requestTimeoutSecs": 30 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "productSlugs": [ "notion" ] }; // Run the Actor and wait for it to finish const run = await client.actor("kawsar/product-hunt-reviews-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "productSlugs": ["notion"] } # Run the Actor and wait for it to finish run = client.actor("kawsar/product-hunt-reviews-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "productSlugs": [ "notion" ] }' | apify call kawsar/product-hunt-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kawsar/product-hunt-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Product Hunt Reviews Scraper", "description": "Product Hunt Reviews Scraper collects user ratings, written feedback, and reviewer metadata from any Product Hunt product page, so you can track sentiment and run competitive analysis without manual work.", "version": "0.0", "x-build-id": "sHb3yCjbDN6gekCsP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kawsar~product-hunt-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kawsar-product-hunt-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kawsar~product-hunt-reviews-scraper/runs": { "post": { "operationId": "runs-sync-kawsar-product-hunt-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kawsar~product-hunt-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-kawsar-product-hunt-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "productSlugs": { "title": "Product slugs (batch)", "type": "array", "description": "Scrape reviews for multiple products at once. Enter one slug per line.", "items": { "type": "string" } }, "sortBy": { "title": "Sort reviews by", "enum": [ "most_informative", "recent", "oldest", "most_positive", "most_negative" ], "type": "string", "description": "Order in which reviews are returned.", "default": "most_informative" }, "reviewType": { "title": "Review type", "enum": [ "all", "founder", "others" ], "type": "string", "description": "Filter reviews by the type of reviewer.", "default": "all" }, "maxItems": { "title": "Max reviews", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of reviews to collect per product.", "default": 25 }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "Per-request timeout in seconds.", "default": 30 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```