apify-ecommerce
Verifiedby sickn33 · Updated Apr 16, 2026
Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.
See It In Action
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:
- Raw dataset:
output/2026-04-14_fitness-smartwatch_us.csv(80 products) - 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.
External Tools
| Tool | Type |
|---|---|
| node | binary |
Permissions
| Scope | Description |
|---|---|
| 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
.envfile withAPIFY_TOKEN(at~/.claude/.env)- Node.js 20.6+ (for native
--env-filesupport)
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 nameurl- Product URLoffers.price- Current priceoffers.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 relevanceMost helpful- Highest voted reviewsHighest rated- 5-star reviews firstLowest 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
maxReviewResultsfor 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 |
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.