# Downy Review Scraper (`getdataforme/downy-review-scraper`) Actor Extract detailed customer reviews from Downy product pages with this reliable Apify Actor. It captures ratings, text, and metadata using residential proxies for seamless, scalable scraping. Features include customizable URLs, structured JSON output, and error-resistant performance.... - **URL**: https://apify.com/getdataforme/downy-review-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Agents, E-commerce - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.09 / actor start This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ### PART 1: README.md ## Downy Review Scraper The Downy Review Scraper is a powerful Apify Actor designed to extract customer reviews from Downy product pages efficiently and reliably. It leverages web scraping techniques to gather detailed review data, including ratings, text, and metadata, enabling users to analyze consumer feedback for insights into product performance. This tool is ideal for businesses, researchers, and marketers seeking to monitor brand sentiment and trends without manual effort. ### Features - **Comprehensive Review Extraction**: Captures full review details such as title, text, rating, author, date, and helpfulness metrics from Downy product pages. - **High Reliability**: Uses residential proxies to avoid IP blocks and ensure consistent data retrieval. - **Customizable Crawling**: Supports multiple start URLs and configurable request limits for targeted scraping. - **Structured Output**: Delivers clean, JSON-formatted data ready for analysis or integration into databases. - **Fast and Scalable**: Built on CheerioCrawler for efficient parsing, handling up to thousands of reviews per run. - **Error-Resistant**: Includes built-in handling for common scraping challenges like dynamic content. - **Apify Integration**: Seamlessly runs on the Apify platform with easy export options to JSON, CSV, or Excel. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | startUrls | array | Yes | URLs to start the scraping process. Each URL should point to a Downy product page. | `[{"url": "https://downy.com/en-us/fabric-softener/rinse-and-refresh/cool-cotton"}]` | | proxyConfiguration | object | No | Configures proxy servers to mask the scraper's origin and avoid blocks. Defaults to Apify's residential proxies. | `{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}` | | maxRequestsPerCrawl | integer | No | Limits the number of HTTP requests made during the crawl to control costs and scope. | `10` | ### Example Usage To run the actor, provide input parameters in JSON format: ```json { "startUrls": [ { "url": "https://downy.com/en-us/fabric-softener/rinse-and-refresh/cool-cotton" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }, "maxRequestsPerCrawl": 10 } ```` Example output in JSON: ```json [ { "productUrl": "https://downy.com/en-us/fabric-softener/rinse-and-refresh/cool-cotton", "productId": "Downy_Rinse_and_Refresh_Cool_Cotton", "reviewId": "245182145", "title": "Doesn't remove odors; just masks them", "text": "I have several tees that have \"perma-stink\" from sweat, and nothing has worked to remove it. So, I decided to try this product, despite the high price. Of course, it doesn't work, either. It doesn't remove the odor; only masks it with a perfume that is so strong it makes my eyes water. Now my shirts smell like perfume AND perma-stink. Very disappointed.", "rating": 1, "author": "DaleyO", "date": "2025-10-12T13:18:39.000+00:00", "isFeatured": false, "helpful": 0, "notHelpful": 0, "verified": false } ] ``` ### Use Cases - **Market Research**: Analyze customer sentiments to identify strengths and weaknesses in Downy products. - **Competitive Intelligence**: Compare review trends with competitors for strategic insights. - **Price Monitoring**: Track feedback related to pricing and value perceptions. - **Content Aggregation**: Collect reviews for content creation, such as blog posts or reports. - **Academic Research**: Study consumer behavior and product reception in studies. - **Business Automation**: Automate data collection for dashboards or CRM integrations. ### Installation and Usage 1. Search for "Downy Review Scraper" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The actor outputs an array of JSON objects, each representing a review. Key fields include: - `productUrl`: The URL of the product page. - `productId`: Unique identifier for the product. - `reviewId`: Unique review identifier. - `title`: Review headline. - `text`: Full review content. - `rating`: Numerical rating (e.g., 1-5). - `author`: Reviewer's username. - `date`: ISO-formatted timestamp. - `isFeatured`: Boolean indicating if featured. - `helpful`/`notHelpful`: Vote counts. - `verified`: Boolean for purchase verification. Data is clean and structured for easy parsing. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** ### PART 2: Concise Description Unlock valuable consumer insights with the Downy Review Scraper! This Apify Actor extracts detailed reviews from Downy product pages, including ratings, text, and metadata, using reliable residential proxies for seamless scraping. Key features include customizable URLs, structured JSON output, and scalable performance. Perfect for market research, competitive analysis, and sentiment tracking. Start scraping today and gain actionable data effortlessly! (148 characters) # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `proxyConfiguration` (type: `object`): Specifies proxy servers that will be used by the scraper in order to hide its origin. ## `maxRequestsPerCrawl` (type: `integer`): Maximum number of requests that can be made by this crawler. ## Actor input object example ```json { "startUrls": [ { "url": "https://downy.com/en-us/fabric-softener/rinse-and-refresh/cool-cotton" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] }, "maxRequestsPerCrawl": 10 } ``` # 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 = { "startUrls": [ { "url": "https://downy.com/en-us/fabric-softener/rinse-and-refresh/cool-cotton" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/downy-review-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 = { "startUrls": [{ "url": "https://downy.com/en-us/fabric-softener/rinse-and-refresh/cool-cotton" }], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("getdataforme/downy-review-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 '{ "startUrls": [ { "url": "https://downy.com/en-us/fabric-softener/rinse-and-refresh/cool-cotton" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call getdataforme/downy-review-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/downy-review-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Downy Review Scraper", "description": "Extract detailed customer reviews from Downy product pages with this reliable Apify Actor. It captures ratings, text, and metadata using residential proxies for seamless, scalable scraping. Features include customizable URLs, structured JSON output, and error-resistant performance....", "version": "0.0", "x-build-id": "TuDQGmCtJ0HFP4zYs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~downy-review-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-downy-review-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~downy-review-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-downy-review-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~downy-review-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-downy-review-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Specifies proxy servers that will be used by the scraper in order to hide its origin.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }, "maxRequestsPerCrawl": { "title": "Max Requests per Crawl", "type": "integer", "description": "Maximum number of requests that can be made by this crawler.", "default": 10 } } }, "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 } } } } } } } } } } ```