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apify-ecommerce

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by sickn33 · Updated Apr 16, 2026

claude-opus-4-6
14.1Kin2.5Kout
$0.384m 25s

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

apifyecommercescrapingpricingreviewsseller-intelligence

See It In Action

1 turns·claude
The project codebase is in your current working directory. Explore the files to understand the code before making changes. need a same-day snapshot of fitness smartwatch prices on US Amazon + Walmart for this afternoon's growth meeting, incl stock/seller patterns

I'll help you gather fitness smartwatch pricing data from Amazon and Walmart for your growth meeting. Let me first explore the current directory to see what we're working with.

Perfect! This is a structured project for gathering fitness smartwatch pricing data. Let me check the key files to understand the setup.

Let me check if there's a valid Apify token configured:

Perfect! I can see the setup. The actual Apify token is in the root .env file, but the script expects it in .claude/.env. Let me update that and then run the data collection.

No problem, I can use the root .env file directly by setting the ENV_FILE variable. Let me run the snapshot collection:

Excellent! The data collection completed successfully. Now let me analyze the results:

Let me extract the key fields for analysis:

Now let me create a Python script to analyze the data:

I see there are some data quality issues with extreme price outliers. Let me refine the analysis:

Perfect! Now let me create the brief for your growth meeting:

Perfect! I've completed your same-day fitness smartwatch price snapshot. Here's what you have for this afternoon's growth meeting:

Deliverables:

  1. Raw dataset: output/2026-04-14_fitness-smartwatch_us.csv (80 products)
  2. Executive brief: analysis/2026-04-14_fitness-smartwatch_brief.md

Key insights:

Amazon dominates with 95% of search results. The category is heavily third-party driven (85% 3P sellers vs 14.5% Amazon direct), with intense competition in budget segments. The median price is $58.82, but the average is $136.03 - showing a flood of cheap options pulling the median down.

Generic "Smart Watch" listings (29) outnumber established brands like Garmin (6), Amazfit (4), and Fitbit (4). Entry/mid-tier products under $150 represent 77% of listings. Stock availability is excellent at 96% on Amazon.

Walmart data is minimal (only 4 products), suggesting either category underinvestment or data collection limitations - potentially an opportunity gap.

Both files are ready for your meeting.

Claude Sonnet 4.6

External Tools

ToolType
nodebinary

Permissions

ScopeDescription
filesystem:read
filesystem:write
network:outbound
process:spawn
env:read

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.

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 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

FieldDescription
googleShoppingSearchKeywordProduct name to search
scrapeSellersFromGoogleShoppingSet to true to extract sellers
scrapeProductsFromGoogleShoppingSet to true to also extract product details
countryCodeTarget country (e.g., us, uk, de)
maxGoogleShoppingSellersPerProductMax sellers per product
maxGoogleShoppingResultsTotal 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

ErrorSolution
APIFY_TOKEN not foundEnsure ~/.claude/.env contains APIFY_TOKEN=your_token
Actor not foundVerify Actor ID: apify/e-commerce-scraping-tool
Run FAILEDCheck Apify console link in error output
TimeoutReduce maxProductResults or increase --timeout
No resultsVerify URLs are valid and accessible
Invalid marketplaceCheck marketplace value matches supported list exactly

FAQ

What does apify-ecommerce do?

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

When should I use apify-ecommerce?

Use it when you need a repeatable workflow that produces text report, structured table, source code.

What does apify-ecommerce output?

In the evaluated run it produced text report, structured table, source code.

How do I install or invoke apify-ecommerce?

Ask the agent to use this skill when the task matches its documented workflow.

Which agents does apify-ecommerce support?

Agent support is inferred from the source, but not explicitly declared.

What tools, channels, or permissions does apify-ecommerce need?

It uses node; channels commonly include text, table, code; permissions include filesystem:read, filesystem:write, network:outbound, process:spawn, env:read.

Is apify-ecommerce safe to install?

Static analysis marked this skill as medium risk; review side effects and permissions before enabling it.

How is apify-ecommerce different from an MCP or plugin?

A skill packages instructions and workflow conventions; tools, MCP servers, and plugins are dependencies the skill may call during execution.

Does apify-ecommerce outperform not using a skill?

About apify-ecommerce

When to use apify-ecommerce

You need to collect product or pricing data from marketplaces for monitoring or comparison. You want to analyze customer reviews for sentiment, quality issues, or recurring defects. You need to identify sellers or possible unauthorized resellers across stores.

When apify-ecommerce is not the right choice

You need direct browser automation or manual interaction with websites rather than API-driven extraction via Apify. You do not have an Apify token or cannot allow outbound network access.

What it produces

Produces text report, structured table and source code.