Web scraping Amazon can be highly profitable for businesses when done smartly. Consider the story of a website that made $800,000 in just two months by scraping Amazon reviews daily. While overnight riches aren't guaranteed, learning how to extract Amazon data effectively can open up significant opportunities.

In this guide, we'll explore two approaches to scraping Amazon: using a no-code scraper and building a custom Python scraper. But first, let's address the legal questions.

Is It Legal to Scrape Amazon?

The legality of scraping Amazon sits in a gray area. Amazon's robots.txt file outlines what can and cannot be scraped, but this file serves only as an ethical guideline—it isn't legally binding. However, Amazon actively blocks bots with technical measures like CAPTCHA tests and rate limiting.

To scrape Amazon successfully, your tool needs advanced techniques such as user agent spoofing, CAPTCHA solving, or request delays. The key factors determining legality include:

  • Type of data scraped – Public product information is generally safer than data behind a login wall.
  • Scraping methods used – Respectful scraping that doesn't overload servers is more likely to be accepted.
  • Purpose of the data – Reselling or replicating Amazon data can lead to legal trouble.

The Supreme Court has defended a data analytics firm against LinkedIn under the CFAA, ruling that unauthorized web scraping of public data isn't illegal. As long as you avoid overwhelming infrastructure or accessing private areas, scraping typically falls within safe boundaries.

Two Ways to Scrape Amazon

Despite technical challenges, scraping Amazon is accessible. You can choose between no-code tools for beginners or custom Python scripts for more control.

No-Code Amazon Scraper

If you don't have coding skills, no-code scrapers are the way to go. You simply provide product or category page URLs, and the tool extracts all relevant data, offering multiple export formats.

Here's how to use a no-code Amazon scraper:

Step 1: Access the Scraper – Visit the scraper's platform and click "Try for Free." This tool can extract prices, reviews, descriptions, images, and more.

Step 2: Create an Account – Sign up for free using email, Google, or GitHub.

Step 3: Paste Target URLs – Input the URL of the Amazon product or category you want to scrape. You can add multiple links or upload a text file. Set a maximum item limit to control the scope.

Step 4: Enable CAPTCHA Solver – Amazon is aggressive with CAPTCHAs. Enable automatic solving to avoid interruptions.

Step 5: Configure Proxy – Use a proxy to mask your scraping activity. Residential proxies are generally best for bypassing anti-scraping systems.

Step 6: Launch the Scraper – Click "Start" and wait for the status to change from "Running" to "Succeeded."

Step 7: Export Your Data – Download results in CSV, JSON, or Excel format.

Python Amazon Scraper

No-code tools are convenient, but they may struggle with Amazon's blocking. For more reliability, build your own Python scraper.

Step 1: Install Python – Download the latest version from the official site.

Step 2: Import Libraries – You'll need requests, BeautifulSoup, lxml, and pandas. Install them with:

pip install requests beautifulsoup4 lxml pandas

Step 3: Configure HTTP Headers – Amazon blocks automated requests. Mimic a real browser by including headers like User-Agent and Accept-Language. You can find these in your browser's developer tools (F12 → Network tab → Request Headers).

Step 4: Extract Product Information – Use a function that sends a request to the product URL, parses the HTML, and retrieves the title, price, image URL, and description using CSS selectors.

Step 5: Handle Pagination – Navigate through product listings by detecting the "Next" page link and recursively scraping each page. Track visited URLs to avoid duplicates.

Step 6: Save Data – Aggregate all scraped data into a list of dictionaries, convert it to a pandas DataFrame, and export as a CSV file.

Staying Undetected While Scraping

Even with a custom script, Amazon may block your requests. Common issues include CAPTCHAs, rate limits, and request blocks. To avoid these, consider using an anti-detect browser that offers fingerprint spoofing and proxy rotation. These tools make your scraper appear as a genuine user, reducing the chance of detection.

At Masbrowser, we compare various fingerprint browsers that can help you scrape Amazon stealthily. Browse our directory to find the right tool for your needs.

Final Thoughts

Scraping Amazon is straightforward with the right approach. No-code tools offer simplicity, while Python scripts provide more control and reliability. Always respect legal boundaries and use anti-detection measures to ensure smooth operations.

Ready to start scraping? Explore the Masbrowser directory to discover the best tools for your Amazon data extraction projects.