Clarks Review Scraper ## Introduction The Clarks Review Scraper is a powerful Apify Actor designed to extract customer reviews from Clarks product pages efficiently and reliably. It leverages PlaywrightCrawler to scrape detailed review data, including ratings, comments, and metadata, enabling businesses and researchers to gather valuable insights from Clarks' e-commerce platform. This tool streamlines data collection for market analysis, sentiment tracking, and competitive intelligence without manual effort. ## Features - Comprehensive Review Extraction: Captures full review details such as product name, SKU, brand, aggregate rating, review count, author, date, and rating value. - High Reliability: Built on Apify's robust infrastructure with error handling to ensure consistent data retrieval from Clarks' dynamic web pages. - Scalable Performance: Handles multiple URLs concurrently, making it ideal for batch processing of product reviews. - Structured Output: Delivers clean, JSON-formatted data ready for integration into databases, analytics tools, or reports. - Customizable Inputs: Supports flexible start URLs to target specific Clarks products or categories. - No Coding Required: User-friendly interface for non-technical users to run extractions directly from the Apify platform. - Real-Time Monitoring: Provides logs and progress tracking for transparent operation. ## Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | startUrls | array | Yes | An array of URLs pointing to Clarks product pages from which to scrape reviews. Each URL should be a valid product page on clarks.com. | [{"url": "https://www.clarks.com/en-gb/clarks-pace/26184425-p"}] | ## Example Usage To run the Clarks Review Scraper, provide the input parameters in JSON format. Here's an example: Input JSON: json { "startUrls": [ { "url": "https://www.clarks.com/en-gb/clarks-pace/26184425-p" } ] } Example Output JSON: json [ { "productName": "Clarks Pace Navy", "sku": "26184667", "brand": "Clarks", "aggregateRating": "4.1", "reviewCount": "21", "url": "https://www.clarks.com/en-gb/clarks-pace/26184667-p", "reviewBody": "Pedí mi talla habitual y la zapatilla me quedaba muy pequeña, demasiado pequeña. Hay que pedir un número más al menos.", "author": "Gregorio CaravacaTorres", "datePublished": "2025-10-26T08:49:09.801Z", "ratingValue": "2" } ] ## Use Cases - Market Research: Analyze customer sentiment and trends for Clarks products to inform product development. - Competitive Intelligence: Compare review data across similar brands to identify strengths and weaknesses. - Price Monitoring: Track reviews alongside pricing data to understand value perceptions. - Content Aggregation: Collect reviews for content creation, such as blog posts or social media campaigns. - Academic Research: Gather data for studies on consumer behavior in the footwear industry. - Business Automation: Automate review monitoring for e-commerce dashboards and reporting. ## Installation and Usage 1. Search for "Clarks 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 data in JSON format as an array of objects. Each object represents a single review and includes fields like productName (the name of the product), sku (unique product identifier), brand (always "Clarks"), aggregateRating (overall product rating), reviewCount (total number of reviews), url (product page URL), reviewBody (the full text of the review), author (reviewer's name), datePublished (ISO 8601 timestamp), and ratingValue (individual review rating). This structured format ensures easy parsing and integration. ## 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! ---