# Gymshark Reviews Scraper (`getdataforme/gymshark-reviews-scraper`) Actor Extract comprehensive customer reviews, ratings, and feedback from Gymshark product pages with this reliable Apify Actor. Features include fast CheerioCrawler-based scraping, customizable inputs, structured JSON output, and data quality assurance.... - **URL**: https://apify.com/getdataforme/gymshark-reviews-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** E-commerce, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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. 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 ## Gymshark Reviews Scraper The Gymshark Reviews Scraper is an Apify Actor designed to extract customer reviews from Gymshark product pages efficiently and reliably. It leverages web scraping technology to gather detailed review data, including ratings, text, and user details, enabling businesses and researchers to analyze customer feedback at scale. This tool is ideal for gaining insights into product performance, customer satisfaction, and market trends without manual effort. ### Features - **Comprehensive Review Extraction**: Captures full review details such as ratings, titles, text, user info, and timestamps from Gymshark product pages. - **High Reliability**: Built on Apify's robust CheerioCrawler for consistent data scraping with error handling. - **Customizable Crawling**: Supports multiple start URLs and limits on requests to tailor extractions to your needs. - **Structured Output**: Delivers clean, JSON-formatted data ready for analysis, export, or integration. - **Fast and Scalable**: Processes reviews quickly, handling up to hundreds of items per crawl. - **No Coding Required**: User-friendly interface for easy setup and execution on the Apify platform. - **Data Quality Assurance**: Includes moderation status and feedback metrics for accurate insights. ### Input Parameters | Parameter | Type | Required | Description | Example | |------------|---------|----------|-----------------------------------------------------------------------------|---------| | startUrls | array | Yes | List of URLs to start scraping reviews from. Each URL should point to a Gymshark product page. | `[{"url": "https://www.gymshark.com/products/gymshark-lift-seamless-leggings-leggings-brown-ss26"}]` | | maxItems | integer | No | Maximum number of requests (reviews) to process during the crawl. Defaults to 100 if not specified. | `50` | ### Example Usage To run the Actor, provide input in JSON format via the Apify platform. Here's an example input: ```json { "startUrls": [ { "url": "https://www.gymshark.com/products/gymshark-lift-seamless-leggings-leggings-brown-ss26" } ], "maxItems": 100 } ```` Example output (array of review objects): ```json [ { "reviewId": "1211249329", "productId": "A3A4P-GB8V", "productName": "Vital 1/4 Zip - GS Light Grey/GS Smokey Grey", "rating": 5, "ratingRange": 5, "qualityRating": 5, "title": "SIZE UP", "reviewText": "SIZE UP i wear a medium, obviously expected this to be tight but its a lot tighter than expected.", "userNickname": "2026gainz", "userLocation": null, "submissionTime": "2026-01-19T07:57:24.000Z", "isRecommended": true, "isFeatured": false, "isSyndicated": false, "helpfulness": 0.8333330154418945, "totalPositiveFeedback": 5, "totalNegativeFeedback": 1, "totalFeedbackCount": 6, "pros": null, "cons": null, "moderationStatus": "APPROVED", "hasClientResponse": false, "clientResponseText": "", "photos": [] } ] ``` ### Use Cases - **Market Research**: Analyze customer sentiment to identify popular products and pain points. - **Competitive Intelligence**: Compare Gymshark reviews with competitors for strategic insights. - **Price Monitoring**: Track feedback on pricing and value for dynamic pricing strategies. - **Content Aggregation**: Collect reviews for blogs, reports, or social media content. - **Academic Research**: Study consumer behavior in the fitness apparel industry. - **Business Automation**: Automate review monitoring for quality control and customer service. ### Installation and Usage 1. Search for "Gymshark Reviews 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 single review. Key fields include: - `reviewId`: Unique identifier for the review. - `productId` and `productName`: Details of the reviewed product. - `rating` and `qualityRating`: Numerical ratings out of the `ratingRange`. - `title` and `reviewText`: Review content. - `userNickname` and `userLocation`: Reviewer information. - `submissionTime`: Timestamp of the review. - `isRecommended`, `helpfulness`, and feedback counts: Engagement metrics. - `moderationStatus`: Approval status. - Additional fields like `pros`, `cons`, and `photos` may be included if available. Data is structured for easy parsing and integration into databases or analytics tools. ### 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: Description Unlock valuable customer insights with the Gymshark Reviews Scraper! Extract detailed reviews, ratings, and user feedback from Gymshark product pages effortlessly. Key features: fast, reliable scraping; customizable inputs; structured JSON output. Perfect for market research, competitive analysis, and business intelligence. Start scraping today on Apify! (248 characters) # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `maxItems` (type: `integer`): Maximum number of requests that can be made by this crawler. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.gymshark.com/products/gymshark-lift-seamless-leggings-leggings-brown-ss26" } ], "maxItems": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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://www.gymshark.com/products/gymshark-lift-seamless-leggings-leggings-brown-ss26" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/gymshark-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 = { "startUrls": [{ "url": "https://www.gymshark.com/products/gymshark-lift-seamless-leggings-leggings-brown-ss26" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/gymshark-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 '{ "startUrls": [ { "url": "https://www.gymshark.com/products/gymshark-lift-seamless-leggings-leggings-brown-ss26" } ] }' | apify call getdataforme/gymshark-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/gymshark-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gymshark Reviews Scraper", "description": "Extract comprehensive customer reviews, ratings, and feedback from Gymshark product pages with this reliable Apify Actor. Features include fast CheerioCrawler-based scraping, customizable inputs, structured JSON output, and data quality assurance....", "version": "0.0", "x-build-id": "4nWsJoWeAgp4rERJC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~gymshark-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-gymshark-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~gymshark-reviews-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-gymshark-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~gymshark-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-gymshark-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "default": [ "https://www.gymshark.com/products/gymshark-lift-seamless-leggings-leggings-brown-ss26" ], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Max Requests per Crawl", "type": "integer", "description": "Maximum number of requests that can be made by this crawler.", "default": 100 } } }, "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 } } } } } } } } } } ```