E-commerce Scraping Tool

Extract detailed product and price data from virtually any online store or marketplace with just a product or category URL. Designed for flexibility and accuracy, this scraper makes large-scale price monitoring and catalog analysis easy.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

The E-commerce Scraping Tool automates the extraction of key e-commerce data, saving countless hours of manual research. It’s built for developers, analysts, and businesses that need structured product data across multiple sites.

Why It’s a Game Changer

• Works across global and local e-commerce platforms like Amazon, Walmart, and eBay.
• Handles thousands of product URLs simultaneously for large-scale data collection.
• Supports export to JSON, CSV, Excel, or direct API integration.
• Ideal for dynamic price tracking, competitor analysis, and catalog mapping.

Features

Feature	Description
Multi-site Scraping	Extracts data from global, regional, and local online stores using URLs.
Flexible Input	Accepts product or category URLs individually or in bulk.
Rich Output Data	Captures names, prices, images, descriptions, and identifiers.
API Integration	Seamlessly connects with webhooks, cloud apps, and workflow automation tools.
Format Exports	Export results in JSON, CSV, Excel, XML, or HTML.
Scalable Infrastructure	Supports large datasets and simultaneous scraping sessions.
Pay-per-Event Model	Cost-efficient scraping without overage surprises.

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What Data This Scraper Extracts

Field Name	Field Description
url	The direct product or listing URL.
name	The product title or name as displayed online.
description	Detailed text describing the product.
price	Product price value as listed on the page.
priceCurrency	The currency code of the listed price.
brand	The manufacturer or brand name.
image	URL of the product image.
productID	Unique identifiers such as SKU, MPN, GTIN, or UPC.
variants	List of available variations (e.g., color, size).
category	Product’s category or taxonomy on the site.

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Example Output

[
  {
    "url": "https://www.ebay.com/itm/136217179741",
    "name": "Bamboo Back Scratcher,100% Natural Bamboo Back Scratchers for Itching Relief",
    "offers": { "price": "5.01", "priceCurrency": "USD" },
    "brand": { "slogan": "eBay Home" },
    "image": "https://i.ebayimg.com/images/g/kuoAAeSwAdRog6nh/s-l960.webp",
    "description": "Seller assumes all responsibility for this listing.",
    "category": "Health & Beauty > Massage > Massagers"
  },
  {
    "url": "https://www.amazon.com/Omszte-Scratcher-Natural-Scratchers-Itching/dp/B09XD65K41",
    "name": "Bamboo Back Scratcher,100% Natural Bamboo Back Scratchers for Itching Relief",
    "offers": { "price": "3.99", "priceCurrency": "USD" },
    "brand": { "slogan": "Omszte" },
    "image": "https://m.media-amazon.com/images/I/61uVexsyXSL._AC_SX679_.jpg"
  }
]

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Directory Structure Tree

E-commerce Scraping Tool/
├── src/
│   ├── main.py
│   ├── extractors/
│   │   ├── ecommerce_parser.py
│   │   ├── price_extractor.py
│   │   └── utils_format.py
│   ├── outputs/
│   │   └── exporter.py
│   └── config/
│       └── settings.json
├── data/
│   ├── input_urls.txt
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Market analysts use it to compare prices across marketplaces, gaining real-time competitive insights.
• E-commerce owners track product positioning and pricing trends for strategy refinement.
• Data scientists use it to feed clean retail datasets into AI or analytics models.
• Developers integrate it into automation systems for dynamic pricing or stock monitoring.
• Agencies gather product data for clients needing structured price intelligence.

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FAQs

Can it scrape Amazon, Walmart, or eBay? Yes. The scraper supports a wide range of e-commerce platforms worldwide, including Amazon, Walmart, eBay, and more.

Is it beginner-friendly? Absolutely. You can start scraping by simply adding one or more product URLs and running the tool. No coding experience required.

What formats are supported for export? JSON, CSV, Excel, XML, and HTML formats are supported, ensuring compatibility with most workflows.

Is scraping legal? The scraper only collects publicly available data and does not access login-protected or private information.

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Performance Benchmarks and Results

• Primary Metric: Processes approximately 200 URLs per minute under standard proxy conditions.
• Reliability Metric: Maintains a 97% success rate in consistent scraping runs.
• Efficiency Metric: Lightweight runtime with low memory overhead for batch tasks.
• Quality Metric: Data completeness above 98%, ensuring highly accurate and structured output.

“Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time.” Nathan Pennington Marketer ★★★★★

“Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on.” Eliza SEO Affiliate Expert ★★★★★

“Exceptional results, clear communication, and flawless delivery. Bitbash nailed it.” Syed Digital Strategist ★★★★★