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apify-ecommerce

Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.

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E-commerce Data Extraction

Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.

When to Use

  • You need product, pricing, review, stock, or seller data from e-commerce sites.
  • The task involves price monitoring, competitor product comparison, MAP enforcement, or review analysis.
  • You need a guided workflow for extracting marketplace data and summarizing findings.

Prerequisites

  • .env file with APIFY_TOKEN (at ~/.claude/.env)
  • Node.js 20.6+ (for native --env-file support)

Workflow Selection

User NeedWorkflowBest For
Track prices, compare productsWorkflow 1: Products & PricingPrice monitoring, MAP compliance, competitor analysis. Add AI summary for insights.
Analyze reviews (sentiment or quality)Workflow 2: ReviewsBrand perception, customer sentiment, quality issues, defect patterns
Find sellers across storesWorkflow 3: SellersUnauthorized resellers, vendor discovery via Google Shopping

Progress Tracking

Task Progress:
- [ ] Step 1: Select workflow and determine data source
- [ ] Step 2: Configure Actor input
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the extraction script
- [ ] Step 5: Summarize results

Workflow 1: Products & Pricing

Use case: Extract product data, prices, and stock status. Track competitor prices, detect MAP violations, benchmark products, or research markets.

Best for: Pricing analysts, product managers, market researchers.

Input Options

Input TypeFieldDescription
Product URLsdetailsUrlsDirect URLs to product pages (use object format)
Category URLslistingUrlsURLs to category/search result pages
Keyword Searchkeyword + marketplacesSearch term across selected marketplaces

Example - Product URLs

{
  "detailsUrls": [
    {"url": "https://www.amazon.com/dp/B09V3KXJPB"},
    {"url": "https://www.walmart.com/ip/123456789"}
  ],
  "additionalProperties": true
}

Example - Keyword Search

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

Optional: AI Summary

Add these fields to get AI-generated insights:

FieldDescription
fieldsToAnalyzeData points to analyze: ["name", "offers", "brand", "description"]
customPromptCustom analysis instructions

Example with AI summary:

{
  "keyword": "robot vacuum",
  "marketplaces": ["www.amazon.com"],
  "maxProductResults": 50,
  "additionalProperties": true,
  "fieldsToAnalyze": ["name", "offers", "brand"],
  "customPrompt": "Summarize price range and identify top brands"
}

Output Fields

  • name - Product name
  • url - Product URL
  • offers.price - Current price
  • offers.priceCurrency - Currency code (may vary by seller region)
  • brand.slogan - Brand name (nested in object)
  • image - Product image URL
  • Additional seller/stock info when additionalProperties: true

Note: Currency may vary in results even for US searches, as prices reflect different seller regions.


Workflow 2: Customer Reviews

Use case: Extract reviews for sentiment analysis, brand perception monitoring, or quality issue detection.

Best for: Brand managers, customer experience teams, QA teams, product managers.

Input Options

Input TypeFieldDescription
Product URLsreviewListingUrlsProduct pages to extract reviews from
Keyword SearchkeywordReviews + marketplacesReviewsSearch for product reviews by keyword

Example - Extract Reviews from Product

{
  "reviewListingUrls": [
    {"url": "https://www.amazon.com/dp/B09V3KXJPB"}
  ],
  "sortReview": "Most recent",
  "additionalReviewProperties": true,
  "maxReviewResults": 500
}

Example - Keyword Search

{
  "keywordReviews": "wireless earbuds",
  "marketplacesReviews": ["www.amazon.com"],
  "sortReview": "Most recent",
  "additionalReviewProperties": true,
  "maxReviewResults": 200
}

Sort Options

  • Most recent - Latest reviews first (recommended)
  • Most relevant - Platform default relevance
  • Most helpful - Highest voted reviews
  • Highest rated - 5-star reviews first
  • Lowest rated - 1-star reviews first

Note: The sortReview: "Lowest rated" option may not work consistently across all marketplaces. For quality analysis, collect a large sample and filter by rating in post-processing.

Quality Analysis Tips

  • Set high maxReviewResults for statistical significance
  • Look for recurring keywords: "broke", "defect", "quality", "returned"
  • Filter results by rating if sorting doesn't work as expected
  • Cross-reference with competitor products for benchm

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