💬 iRecommend Search Scraper

This actor allows you to scrape product recommendations from iRecommend.ru by providing a search URL. It automatically handles pagination and extracts comprehensive product information including ratings, reviews, votes, and user feedback.

Features

• URL-based Scraping: Extract product recommendations by providing a complete iRecommend search URL
• Automatic Pagination: Automatically navigates through pages and loads more results until reaching the end or max items limit
• Comprehensive Product Data: Extract detailed information about each product including:
  • Product names and detail page links
  • Average ratings and total votes
  • Review counts and links to all reviews
  • Product images
  • Review extracts and summaries
  • User engagement metrics (likes and dislikes)
• Smart Deduplication: Automatically removes duplicate products based on detail page URLs

Input Parameters

Field	Type	Required	Description
searchUrl	string	Yes	Complete iRecommend.ru search URL to scrape
maxItems	integer	No	Maximum number of products to fetch
proxyConfiguration	object	No	Proxy settings for the actor

How to Get Search URL

1. Go to iRecommend.ru
2. Use the search bar to find products or recommendations
3. Copy the complete URL from your browser's address bar
4. Paste it into the searchUrl field

Example search URLs:

https://irecommend.ru/srch?query=iphone
https://irecommend.ru/srch?query=laptop
https://irecommend.ru/srch?query=cosmetics

Output

The output is a dataset of product recommendation objects, each containing:

• searchUrl: The original search URL used
• name: Product name
• detailPageUrl: Direct link to the product detail page
• allReviewsLink: Link to all reviews for the product
• reviewCount: Total number of reviews
• image: URL of the product image
• extract: Review extract or summary text
• extractUrl: Link to the full review extract
• averageRating: Average rating score (e.g., 4.8)
• votes: Total number of votes
• likes: Number of likes
• dislikes: Number of dislikes
• scrapedAt: Timestamp of when the product was scraped

Example output:

[
  {
    "searchUrl": "https://irecommend.ru/srch?query=iphone",
    "name": "Смартфон Apple Iphone 13 Pro Max",
    "detailPageUrl": "https://irecommend.ru/content/mobilnyi-telefon-apple-iphone-13-pro-max",
    "allReviewsLink": "https://irecommend.ru/content/mobilnyi-telefon-apple-iphone-13-pro-max",
    "reviewCount": 145,
    "image": "https://cdn-irec.r-99.com/sites/default/files/imagecache/150o/product-images/10297/7zAaSH9No8RzMu3c2I7rVw.jpg",
    "extract": "использовала айфон 16 pro max и 13 pro max вместе неделю. Плюс общие впечатления о айфоне 13 pro max спустя 3 года использования",
    "extractUrl": "https://irecommend.ru/content/ispolzovala-aifon-16-pro-max-i-13-pro-max-vmeste-nedelyu-plyus-obshchie-vpechatleniya-o-aifo",
    "averageRating": 4.8,
    "votes": 145,
    "likes": 143,
    "dislikes": 2,
    "scrapedAt": "2025-11-10T06:26:31.684Z"
  },
  ...
]

Use Cases

• Product research and comparison
• Consumer sentiment analysis
• Market research and trend analysis
• Review aggregation and analysis
• Product recommendation tracking
• Competitive analysis for brands
• User feedback collection

Notes

• The actor works with iRecommend.ru (Russian product recommendation platform)
• Results are automatically paginated until reaching the end or max items limit
• All ratings and counts are extracted as numbers for easy analysis
• Product images and review extracts provide rich context for each recommendation
• The actor includes delays between actions to ensure reliable scraping

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Start scraping product recommendations from iRecommend.ru today!