You Don't Need Different Scrapers for Each E-Commerce Website: This One Covers Most of Them
Scraping prices from multiple e-commerce sites is usually inefficient: one scraper per site, messy data formats, and incomplete coverage. Category pages help with discovery but miss frequent price updates; product pages capture changes but don't scale.
E-commerce Scraping Tool fixes this. It extracts prices from both category and product URLs in the same run, giving you a single deduplicated dataset across Amazon, Walmart, eBay, Target, Etsy, and dozens of other marketplaces.
Here's how to use it for e-commerce price scraping—and why it's revolutionizing competitive intelligence for online retailers.
Why E-Commerce Price Monitoring Is Critical in 2024
According to Pricefy's 2024 research, 75% of shoppers prioritize competitive pricing as the most crucial aspect influencing their buying decisions. This statistic underscores the importance of adopting price intelligence strategies to stay ahead in a market where prices change rapidly due to intense competition.
The modern e-commerce landscape operates at breakneck speed. Prices fluctuate hourly based on demand, competitor actions, inventory levels, and dynamic pricing algorithms. Retailers who can't keep pace lose sales to competitors who offer better prices—often by just a few cents.
The Problem with Traditional Price Monitoring:
Most businesses approach competitor price tracking in one of three ways:
Manual Checking: Staff manually visits competitor websites, copies prices into spreadsheets. This takes hours daily and misses real-time changes.
Single-Site Scrapers: Building a custom scraper for Amazon, then another for Walmart, then eBay, then Target... Each requires different code, maintenance, and proxy management.
Expensive Enterprise Tools: Solutions like Price2Spy or Minderest cost $500-2,000/month and often have product limits or complicated integrations.
According to a study by Price2Spy, businesses switching to automated competitive intelligence tools save up to 92% of labor costs compared to manual price tracking.
What You Really Need:
A unified scraper that handles multiple e-commerce platforms, extracts both product listings and individual product details, deduplicates results automatically, and costs pennies per thousand products.
That's exactly what Apify's E-commerce Scraping Tool delivers.
How to Scrape Prices from E-Commerce Websites
E-commerce Scraping Tool is one of the thousands of scrapers available on Apify Store—the world's largest marketplace of web data collection tools. You can use it via the UI (natural language or JSON) or programmatically through API. The UI is the fastest way to start, so that's what we'll demo here.
Step 1: Go to E-commerce Scraping Tool on Apify Store
You can find the tool by typing the name in the search bar or looking in the e-commerce category. But let's make things quick: Just click Try for free here.
If you're logged in to your Apify account, you'll be taken to Apify Console—your dashboard for configuring scrapers. Otherwise, you'll be prompted to sign in or sign up first, which you can do easily with your email or GitHub account and without a credit card.
New users receive $5 of free credit every month, which is enough to scrape 10,000+ products to test the tool.
Step 2: Choose Your Input Types
Once you're logged in, you can configure the tool in Apify Console.
The tool supports two main URL types: Category listing URLs and Product detail URLs.
Input Type What It Is When to Use It Category listing URLs Search results or category pages with multiple products Discover many products, monitor whole categories, find new arrivals Product detail URLs URLs pointing directly to a single product page Monitor known SKUs, track specific items for price/stock changes
Example Category URLs:
https://www.amazon.com/s?k=wireless+headphones
https://www.walmart.com/browse/electronics/headphones/3944_133251
https://www.ebay.com/sch/i.html?_nkw=bluetooth+speakers
Example Product URLs:
https://www.amazon.com/dp/B0CX23V2ZK
https://www.walmart.com/ip/Apple-AirPods-Pro/520468661
https://www.ebay.com/itm/234567890123
Pro Tip: You can mix both types in a single run. For example, scrape entire categories from Amazon to discover new products, while monitoring specific SKUs on Walmart and eBay for price changes.
Step 3: Configure Advanced Settings (Optional)
The E-commerce Scraping Tool offers powerful configuration options:
Max Products Per Category: Limit how many products to extract from each listing page (default: 50, max: 10,000).
Proxy Settings: Choose between datacenter proxies (faster, cheaper) or residential proxies (more reliable for anti-bot sites).
Browser Rendering: Enable JavaScript rendering for sites that load prices dynamically (adds cost but ensures accuracy).
Filters: Set minimum/maximum price ranges, filter by brand, exclude out-of-stock items.
For most use cases, the defaults work perfectly. Just add your URLs and hit Start.
Step 4: Run the Scraper and Export Your Data
Click Start to run the scraper.
When the run finishes, open the Storage tab to view results: product name, price, SKU, brand, image, description, and URL.
Example Output:
{ "title": "Sony WH-1000XM5 Wireless Headphones", "price": 329.99, "currency": "USD", "availability": "In Stock", "brand": "Sony", "sku": "WH1000XM5/B", "url": "https://www.amazon.com/dp/B0CX23V2ZK", "imageUrl": "https://m.media-amazon.com/images/I/...", "rating": 4.6, "reviewsCount": 12847, "category": "Electronics > Headphones", "seller": "Amazon.com", "shippingPrice": 0, "originalPrice": 399.99, "discount": 70.00
}
Choose the format of the dataset from the options provided: JSON, CSV, XML, Excel, HTML Table, RSS, JSONL.
If you only want prices in your dataset, select only the offers field during export to create a lean price-tracking spreadsheet.
Download Options:
CSV for Excel: Perfect for manual analysis and pivot tables
JSON for APIs: Feed directly into your backend systems
Google Sheets Integration: Auto-sync results to spreadsheets for real-time dashboards
Real-World Use Cases for E-Commerce Price Scraping
Use Case 1: Dynamic Repricing for Amazon Sellers
Scenario: You sell electronics on Amazon and need to stay competitive with 50+ competitors who change prices multiple times daily.
Solution:
Add your competitors' product URLs (ASINs) to E-commerce Scraping Tool
Schedule the scraper to run every 2 hours
Export results to your repricing software via API
Automatically adjust your prices to stay within 5% of the lowest competitor
Result: One Amazon seller reported a 23% increase in Buy Box wins after implementing automated price monitoring, leading to a $47K monthly revenue increase.
Use Case 2: Market Research for Product Launches
Scenario: You're launching a new line of yoga mats and need to understand the competitive landscape across multiple marketplaces.
Solution:
Scrape category pages:
amazon.com/yoga-mats,walmart.com/yoga-equipment,ebay.com/yoga-matsExtract 500 products across all platforms
Analyze: average price ($28.50), price range ($15-$89), top brands (Gaiam, Manduka, Liforme)
Identify pricing sweet spot: $32-$39 for premium quality
Result: Armed with competitive intelligence, you launch at $34.99—positioned as premium without pricing out of market. First-month sales exceed projections by 34%.
Use Case 3: Brand Protection and MAP Monitoring
Scenario: You're a brand manufacturer selling through authorized retailers. You need to enforce Minimum Advertised Price (MAP) policies to protect brand value.
Solution:
Scrape all authorized retailer URLs for your SKUs
Set up alerts when prices drop below MAP ($99.99)
Identify violators automatically
Send automated warning emails via integration
Result: MAP compliance increased from 67% to 94% within 3 months. Brand perception improved, and authorized retailers stopped complaining about price undercutting.
Use Case 4: Inventory Arbitrage for Resellers
Scenario: You're an e-commerce arbitrage seller looking for price discrepancies across platforms to flip products for profit.
Solution:
Scrape the same products across Amazon, eBay, Walmart, and Target
Calculate price spreads (e.g., product costs $45 on Walmart, sells for $68 on Amazon)
Filter for products with >30% margin and high sales volume
Automate purchase orders when opportunities appear
Result: Identified 23 profitable arbitrage opportunities weekly. Average profit per flip: $12.40. Monthly arbitrage revenue: $1,200-1,800 with minimal effort.
Use Case 5: Historical Price Tracking for Deal Sites
Scenario: You run a deal aggregation website (like Slickdeals or Honey) and need to track historical prices to identify genuine deals vs. fake discounts.
Solution:
Scrape product prices daily across major retailers
Store historical data in time-series database
Calculate: average price, lowest price, price volatility
Flag deals as "genuine" only if current price is <90% of 30-day average
Result: User trust increased 41% after implementing verified deal badges. Affiliate conversion rates improved 28% because users knew they were getting real deals.
Pricing: What E-Commerce Price Scraping Actually Costs
E-commerce Scraping Tool uses a pay-per-event pricing model. You pay for:
Run start ($0.00007)
Listings scraped (per page: $0.00026)
Product details extracted (per product: $0.00100)
Optional: Proxy use ($0.00080 per product)
Optional: Browser rendering ($0.00051 per product)
Example: Scraping 1,000 Listing Pages (~20,000 Products)
Without Proxies or Browser Rendering:
Actor start = $0.00007
Listings = 1,000 × $0.00026 = $0.26
Product details = 20,000 × $0.00100 = $20.00
Total ≈ $20.26
With Proxies + Browser Rendering:
Actor start = $0.00007
Listings = $0.26
Product details = $20.00
Residential proxy = 20,000 × $0.00080 = $16.00
Browser rendering = 20,000 × $0.00051 = $10.20
Total ≈ $46.46
Key Takeaway
Costs remain very low relative to data volume. A large run with proxies + browser rendering comes to about $46.46 for 20,000 products. That's $0.0023 per product—less than a quarter of a cent.
Compare to Alternatives:
Solution Monthly Cost Products Tracked Cost Per Product Manual Tracking $1,200 (80 hrs @ $15/hr) 500 $2.40 Price2Spy $500/month 10,000 $0.05 Minderest $1,500/month 50,000 $0.03 Apify E-commerce Tool $46.46 (one-time) 20,000 $0.0023
For frequent large-scale runs, Apify's Business plan offers volume discounts and priority support.
Integrate E-Commerce Scraping Tool with Your Workflows
If you want to automate, scale, or integrate scraping into your existing workflow, you can run E-commerce Scraping Tool programmatically with the Apify API.
API Integration Options:
Python Example:
from apify_client import ApifyClient client = ApifyClient("<YOUR_API_TOKEN>") run_input = { "urls": [ "https://www.amazon.com/s?k=wireless+headphones", "https://www.walmart.com/browse/electronics/headphones/3944_133251" ], "maxProducts": 100
} run = client.actor("apify/e-commerce-scraping-tool").call(run_input=run_input) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"{item['title']}: ${item['price']}")
JavaScript/Node.js Example:
const { ApifyClient } = require('apify-client'); const client = new ApifyClient({ token: '<YOUR_API_TOKEN>',
}); const input = { "urls": [ "https://www.amazon.com/dp/B0CX23V2ZK", "https://www.walmart.com/ip/520468661" ]
}; const run = await client.actor("apify/e-commerce-scraping-tool").call(input); const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => { console.log(`${item.title}: $${item.price}`);
});
Integration with Business Tools:
Zapier: Connect scraped data to 5,000+ apps (Google Sheets, Slack, HubSpot, etc.)
Make.com (Integromat): Build complex workflows with conditional logic and multi-step automations
n8n: Self-hosted automation for custom data pipelines
Google Sheets: Auto-sync results for real-time dashboards
Snowflake/BigQuery: Feed into data warehouses for advanced analytics
Custom Webhooks: Push results to your backend in real-time
For more details about using the API, go to the API Documentation or the Apify API docs.
Advanced Features That Set This Scraper Apart
1. Automatic Deduplication
When scraping multiple category pages or combining results from different sources, you often get duplicate products. E-commerce Scraping Tool automatically deduplicates based on SKU, product URL, or title matching—giving you clean datasets without manual cleanup.
2. Multi-Marketplace Support
Unlike specialized scrapers that only work on Amazon or eBay, this tool handles:
Amazon (all domains: .com, .co.uk, .de, .fr, etc.)
Walmart
eBay
Target
Etsy
AliExpress
Best Buy
Home Depot
Wayfair
And 50+ other major e-commerce sites
No need to manage multiple scrapers or learn different APIs for each platform.
3. Structured Data Extraction
The scraper uses intelligent parsing to extract structured fields:
Product identifiers: SKU, UPC, EAN, ASIN
Pricing data: Current price, original price, discount percentage, currency
Availability: In stock, out of stock, limited quantity, pre-order
Seller information: Primary seller, marketplace sellers, third-party sellers
Product attributes: Brand, category, color, size, weight, dimensions
Customer feedback: Rating, review count, review snippets
Media: Primary image, gallery images, video URLs
This structured format makes downstream analysis and integration seamless.
4. Rate Limiting and Respect for robots.txt
The scraper respects rate limits and robots.txt directives to avoid overloading target sites. This ensures:
Lower risk of IP bans
Compliance with website terms of service
Sustainable long-term scraping without interruptions
5. Proxy Rotation and Browser Fingerprinting
For sites with aggressive anti-bot protections, enable residential proxies and browser rendering. The scraper automatically:
Rotates through thousands of residential IPs
Mimics real browser fingerprints (Chrome, Firefox, Safari)
Handles CAPTCHA challenges (when possible)
Manages cookies and sessions intelligently
According to research on web scraping best practices, residential proxies combined with browser fingerprinting achieve 95%+ success rates even on heavily protected e-commerce sites.
Track Competitor Prices at Scale
For e-commerce pricing data, you can collect information from both listing and detail URLs across multiple websites and store it in one dataset. This lets you discover many products, track known SKUs, and get maximum coverage in one deduplicated dataset.
You can run the scraper via UI for simplicity, or programmatically via API for integration into your workflow.
Scheduling for Continuous Monitoring:
Set up automated runs to track prices continuously:
Hourly: For dynamic categories like electronics where prices change frequently
Daily: For most consumer goods and retail products
Weekly: For less competitive niches or slow-moving inventory
Email Alerts:
Configure notifications to alert your team when:
Competitor prices drop below yours by >5%
New products appear in tracked categories
Products go out of stock or return to availability
Price changes exceed threshold (e.g., >10% increase/decrease)
Common Pitfalls and How to Avoid Them
Pitfall 1: Scraping Too Aggressively
Problem: Setting up hourly scrapes of 10,000 products can trigger rate limits and IP bans.
Solution: Start with daily runs and scale gradually. Use proxy rotation for high-volume scraping. Monitor error rates and adjust frequency accordingly.
Pitfall 2: Ignoring Data Quality Issues
Problem: Not all scraped data is perfect—out-of-stock products return null prices, promotional prices are temporary, bundle deals complicate comparisons.
Solution: Implement post-processing filters:
Remove products with null or zero prices
Flag promotional prices separately (check for "originalPrice" field)
Normalize pricing for bundles (calculate unit price)
Pitfall 3: Not Scheduling Regular Updates
Problem: E-commerce prices change rapidly. One-time scrapes become stale within hours or days.
Solution: Use Apify's scheduling feature:
Save your scraper configuration as a "Task"
Set up a schedule (hourly, daily, weekly)
Enable email notifications on completion
Connect to webhooks for real-time data pipeline updates
Pitfall 4: Exceeding Budget Without Realizing
Problem: Scraping 100,000 products daily with proxies and browser rendering can rack up costs quickly.
Solution:
Test with small runs first (50-100 products)
Monitor usage in Apify Console dashboard
Set budget alerts
Disable proxies/rendering for low-protection sites
Use datacenter proxies instead of residential when possible
Pitfall 5: Not Leveraging Historical Data
Problem: Scraped prices are only useful if you track changes over time.
Solution: Build a historical database:
Export results to time-series database (InfluxDB, TimescaleDB)
Track: min price, max price, average price, price volatility
Visualize trends with dashboards (Grafana, Tableau)
Use historical data for demand forecasting and seasonal pricing strategies
FAQ
Q: Can I scrape Amazon without getting blocked?
Yes. E-commerce Scraping Tool uses advanced anti-detection techniques including residential proxy rotation and browser fingerprinting. Success rates exceed 95% when proxies are enabled. For ultra-high-volume Amazon scraping, we recommend using datacenter proxies for listing pages and residential proxies only for product details to optimize costs.
Q: Does this work for international e-commerce sites?
Absolutely. The scraper supports Amazon domains across 20+ countries (.co.uk, .de, .fr, .ca, .au, etc.) and major international marketplaces like AliExpress, Mercado Libre, and Rakuten. Simply provide the full URL including country-specific domain.
Q: How often should I run price monitoring?
It depends on your industry:
Electronics/Tech: Every 2-6 hours (prices change rapidly)
Fashion/Apparel: Daily (seasonal changes and promotions)
Home Goods: Weekly (slower-moving inventory)
Groceries/Consumables: Daily during promotional periods
Q: Can I get historical price data?
The scraper captures current prices only. To build historical tracking, set up scheduled runs and store results in a database or Google Sheets with timestamps. Many users export to BigQuery or Snowflake for long-term analysis.
Q: Is this legal?
Scraping publicly available pricing data is generally legal under US law (based on precedent like hiQ Labs v. LinkedIn). However, you must respect rate limits, not violate Terms of Service for commercial purposes without permission, and avoid scraping personal user data. Consult legal counsel for your specific jurisdiction and use case.
Q: What if the scraper breaks due to website changes?
Apify maintains the E-commerce Scraping Tool continuously. When target sites update their layouts, the scraper gets updated within 24-48 hours. You don't need to modify anything—just keep using it.
Conclusion
E-commerce price monitoring is no longer optional—it's a competitive necessity. But managing dozens of custom scrapers for different marketplaces, dealing with anti-bot protections, and cleaning messy data doesn't have to be your reality.
Apify's E-commerce Scraping Tool provides a unified solution that works across Amazon, Walmart, eBay, Target, and 50+ other platforms. Extract product listings and individual product details in the same run. Get deduplicated, structured data for pennies per product. Integrate seamlessly with your existing workflows via API, Zapier, Make.com, or webhooks.
Whether you're a solo Amazon seller monitoring 50 competitors, an e-commerce agency managing price intelligence for multiple clients, or an enterprise brand protecting MAP policies across thousands of SKUs—this tool scales to meet your needs.
Ready to start tracking competitor prices at scale? Sign up for Apify here with $5 free monthly credit and start scraping e-commerce data in minutes.
Your competitors are already using automated price intelligence. It's time to level the playing field.
