Expert Tutorial

How to Use E-Commerce Scraping Tool to Extract Data (2026 Guide)

A step-by-step guide on how to use E-Commerce Scraping Tool to extract data and export it to Excel or CSV without coding.

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What is E-Commerce Scraping Tool?

Extract product details, prices, reviews, and seller information from global online retail platforms and marketplaces like Amazon, Walmart, and eBay.

E-commerce Scraping Tool is an all-in-one solution that extracts product and price data, category details, reviews, and seller information from online retail platforms and marketplaces - including Amazon, Walmart, Target, Shopify stores, and eBay - using only a product or category URL. It supports global marketplaces as well as regional and local e-shops, making it highly suitable for competitor price monitoring, market research, and building product comparison engines. It features built-in proxy rotation and CAPTCHA bypass to stay undetected.

Key Features

  • Scrape almost any e-commerce site globally
  • Extract multiple e-commerce sites simultaneously in a single run
  • Built-in robust proxy rotation to avoid blocks
  • Full data extraction (price, identifiers, images, reviews, brand)
  • Schedule runs to track price changes over time
  • Select specialized views (e.g., product details, reviews, seller info)

How to Extract Data (Step by Step)

Extracting data using the E-Commerce Scraping Tool is incredibly straightforward. It runs entirely in the cloud, meaning you don't need to install any desktop software.

  1. Log into your Apify account or click 'Try for Free'.
  2. Input the specific product or category URLs you want to scrape.
  3. Alternatively, enter search terminology into the appropriate input field.
  4. Click 'Start'. The actors will intelligently handle CAPTCHAs and scrape the page.
  5. Go to the Storage tab and view results in standard product view, review view, or seller view.
  6. Export the structured data into Excel, JSON, or CSV formats.
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What does the exported data look like?

You can export the results into Excel, CSV, JSON, or HTML. Here is a sample of what the raw JSON data looks like:

{
  "url": "https://example-shop.com/product/123",
  "title": "Wireless Headphones Pro",
  "brand": "TechAudio",
  "price": {
    "value": 199.99,
    "currency": "USD"
  },
  "rating": 4.8,
  "reviewsCount": 342,
  "availability": "In Stock",
  "images": [
    "https://example-shop.com/img/123-front.jpg"
  ],
  "seller": "TechAudio Official Store"
}