Extract product data and reviews from e-commerce sites

This skill extracts product data, prices, reviews and seller information from e-commerce platforms using Apify's E-commerce Scraping Tool (Actor apify/e-commerce-scraping-tool). It offers three workflows and a guided path to pick between them:

• Workflow 1, Products and Pricing: extract product data, prices and stock status to track competitor prices, detect MAP violations, benchmark products or research markets. It suits pricing analysts, product managers and market researchers.
• Workflow 2, Customer Reviews: extract reviews for sentiment analysis, brand perception monitoring or quality issue detection. It suits brand managers, customer experience teams, QA teams and product managers.
• Workflow 3, Seller Intelligence: find sellers across stores, discover unauthorized resellers and evaluate vendors. It suits brand protection, procurement and supply chain teams. This workflow uses Google Shopping, because direct seller profile URLs are not reliably supported.

Inputs for products are product page URLs in detailsUrls (object format), category or search result URLs in listingUrls, or a keyword combined with marketplaces. An optional AI summary is enabled with fieldsToAnalyze (for example name, offers, brand, description) and a customPrompt. Output fields include name, url, offers.price, offers.priceCurrency, the brand name (nested under brand.slogan), the image URL, and extra seller and stock info when additionalProperties is true. Currency can vary even for US searches because prices reflect different seller regions.

For reviews, inputs are reviewListingUrls or keywordReviews with marketplacesReviews, with maxReviewResults and a sortReview option: Most recent (recommended), Most relevant, Most helpful, Highest rated or Lowest rated. The Lowest rated sort may not work consistently across marketplaces, so for quality analysis collect a large sample and filter by rating afterwards. Tips: set a high result limit for statistical significance, look for recurring words such as broke, defect, quality and returned, and cross-reference with competitor products.

For sellers, googleShoppingSearchKeyword with scrapeSellersFromGoogleShopping, an optional scrapeProductsFromGoogleShopping, countryCode (us, uk, de) and limits on sellers per product and total results.

Use it when you need product, pricing, review, stock or seller data from e-commerce sites, for price monitoring, competitor comparison, MAP enforcement or review analysis. Do not use it for direct seller profile URLs, which are not reliably supported. It is not a substitute for environment-specific validation or expert review, and it stops to ask for clarification when inputs, permissions, safety boundaries or success criteria are missing.

The marketplace list is explicit and must match exactly: about 20 Amazon regional sites, Walmart, Costco (US and Canada), Home Depot, European retailers (Allegro, Alza, Kaufland, Cdiscount), IKEA in 40+ country and language combinations, and Google Shopping for seller discovery. Results are shown in chat, or exported to CSV or JSON with a date-prefixed file name. The summary reports the number of items, the file location and insights by workflow: price range, outliers and MAP violations for products, average rating, sentiment trends and quality issues for reviews, and seller count and unauthorized sellers for sellers.

{
  "keyword": "Samsung Galaxy S24",
  "marketplaces": ["www.amazon.com", "www.walmart.com"],
  "additionalProperties": true,
  "maxProductResults": 50
}

Errors: a missing APIFY_TOKEN, an unknown Actor ID, a failed run (check the Apify console link), a timeout (reduce maxProductResults or raise --timeout), no results (verify the URLs), or an invalid marketplace value.

It runs through Node.js with the run_actor.js script in the skill's reference scripts folder and the Apify platform.

Pricing analysts, brand protection teams, product managers, procurement and CX teams who need structured marketplace data without writing scrapers.