apify-ecommerce

apify/agent-skills · updated May 29, 2026

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$npx skills add https://github.com/apify/agent-skills --skill apify-ecommerce
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summary

Extract product data, prices, reviews, and seller information from 50+ e-commerce marketplaces.

  • Three workflow modes: Products & Pricing (price tracking, competitor analysis), Customer Reviews (sentiment analysis, quality issues), and Seller Intelligence (vendor discovery via Google Shopping)
  • Supports Amazon (20+ regions), Walmart, eBay, IKEA, Costco, and European retailers; input via product URLs, category URLs, or keyword search
  • Optional AI-powered analysis generates insights
skill.md

E-commerce Data Extraction

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

Prerequisites

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

Workflow Selection

User Need Workflow Best For
Track prices, compare products Workflow 1: Products & Pricing Price monitoring, MAP compliance, competitor analysis. Add AI summary for insights.
Analyze reviews (sentiment or quality) Workflow 2: Reviews Brand perception, customer sentiment, quality issues, defect patterns
Find sellers across stores Workflow 3: Sellers Unauthorized 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 Type Field Description
Product URLs detailsUrls Direct URLs to product pages (use object format)
Category URLs listingUrls URLs to category/search result pages
Keyword Search keyword + marketplaces Search 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:

Field Description
fieldsToAnalyze Data points to analyze: ["name", "offers", "brand", "description"]
customPrompt Custom 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 Type Field Description
Product URLs reviewListingUrls Product pages to extract reviews from
Keyword Search keywordReviews + marketplacesReviews Search 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 benchmarking

Workflow 3: Seller Intelligence

Use case: Find sellers across stores, discover unauthorized resellers, evaluate vendor options.

Best for: Brand protection teams, procurement, supply chain managers.

Note: This workflow uses Google Shopping to find sellers across stores. Direct seller profile URLs are not reliably supported.

Input Configuration

{
  "googleShoppingSearchKeyword": "Nike Air Max 90",
  "scrapeSellersFromGoogleShopping": true,
  "countryCode": "us",
  "maxGoogleShoppingSellersPerProduct": 20,
  "maxGoogleShoppingResults": 100
}

Options

Field Description
googleShoppingSearchKeyword Product name to search
scrapeSellersFromGoogleShopping Set to true to extract sellers
scrapeProductsFromGoogleShopping Set to true to also extract product details
countryCode Target country (e.g., us, uk, de)
maxGoogleShoppingSellersPerProduct Max sellers per product
maxGoogleShoppingResults Total result limit

Supported Marketplaces

Amazon (20+ regions)

www.amazon.com, www.amazon.co.uk, www.amazon.de, www.amazon.fr, www.amazon.it, www.amazon.es, www.amazon.ca, www.amazon.com.au, www.amazon.co.jp, www.amazon.in, www.amazon.com.br, www.amazon.com.mx, www.amazon.nl, www.amazon.pl, www.amazon.se, www.amazon.ae, www.amazon.sa, www.amazon.sg, www.amazon.com.tr, www.amazon.eg

Major US Retailers

www.walmart.com, www.costco.com, www.costco.ca, www.homedepot.com

European Retailers

allegro.pl, allegro.cz, allegro.sk, www.alza.cz, www.alza.sk, www.alza.de, www.alza.at, www.alza.hu, www.kaufland.de, www.kaufland.pl, www.kaufland.cz, www.kaufland.sk, www.kaufland.at, www.kaufland.fr, www.kaufland.it, www.cdiscount.com

IKEA (40+ country/language combinations)

Supports all major IKEA regional sites with multiple language options.

Google Shopping

Use for seller discovery across multiple stores.


Running the Extraction

Step 1: Set Skill Path

SKILL_PATH=~/.claude/skills/apify-ecommerce

Step 2: Run Script

Quick answer (display in chat):

node --env-file=~/.claude/.env $SKILL_PATH/reference/scripts/run_actor.js \
  --actor "apify/e-commerce-scraping-tool" \
  --input 'JSON_INPUT'

CSV export:

node --env-file=~/.claude/.env $SKILL_PATH/reference/scripts/run_actor.js \
  --actor "apify/e-commerce-scraping-tool" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_filename.csv \
  --format csv

JSON export:

node --env-file=~/.claude/.env $SKILL_PATH/reference/scripts/run_actor.js \
  --actor "apify/e-commerce-scraping-tool" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_filename.json \
  --format json

Step 3: Summarize Results

Report:

  • Number of items extracted
  • File location (if exported)
  • Key insights based on workflow:
    • Products: Price range, outliers, MAP violations
    • Reviews: Average rating, sentiment trends, quality issues
    • Sellers: Seller count, unauthorized sellers found

Error Handling

Error Solution
APIFY_TOKEN not found Ensure ~/.claude/.env contains APIFY_TOKEN=your_token
Actor not found Verify Actor ID: apify/e-commerce-scraping-tool
Run FAILED Check Apify console link in error output
Timeout Reduce maxProductResults or increase --timeout
No results Verify URLs are valid and accessible
Invalid marketplace Check marketplace value matches supported list exactly
how to use apify-ecommerce

How to use apify-ecommerce on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add apify-ecommerce
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/apify/agent-skills --skill apify-ecommerce

The skills CLI fetches apify-ecommerce from GitHub repository apify/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/apify-ecommerce

Reload or restart Cursor to activate apify-ecommerce. Access the skill through slash commands (e.g., /apify-ecommerce) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.869 reviews
  • Amelia Desai· Dec 20, 2024

    apify-ecommerce has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Diya Rao· Dec 16, 2024

    apify-ecommerce fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Alexander Gill· Dec 16, 2024

    apify-ecommerce reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Xiao Patel· Dec 12, 2024

    I recommend apify-ecommerce for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Pratham Ware· Dec 4, 2024

    Registry listing for apify-ecommerce matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Yash Thakker· Nov 23, 2024

    apify-ecommerce reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Kiara Liu· Nov 15, 2024

    Solid pick for teams standardizing on skills: apify-ecommerce is focused, and the summary matches what you get after install.

  • Kaira Abbas· Nov 11, 2024

    Useful defaults in apify-ecommerce — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Kiara Li· Nov 7, 2024

    I recommend apify-ecommerce for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kiara Anderson· Nov 7, 2024

    Registry listing for apify-ecommerce matched our evaluation — installs cleanly and behaves as described in the markdown.

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