How to Scrape Reviews from Popular eCommerce Websites?


Getting information from online stores is helpful for businesses to compete better online. This data includes details about products, how much they cost, and what customers think of them.  Experts can scrape reviews from popular eCommerce websites that are vital for businesses. These reviews are honest opinions from people who have bought and used the products. So, if a company wants to understand how well its product is doing or what people think, they can check these reviews on ecommerce websites. However, collecting these reviews automatically from different websites can be tricky. Not all companies have the right tools or knowledge to do it efficiently. Using special automated tools to get this information is much faster and easier. With this data, companies can see what their competitors are selling, how they price their items, and what customers like or don’t like about them.

What is eCommerce Review Scraping?

Ecommerce review scraping is a tool used to gather customer reviews from online shopping websites. Instead of reading each review individually, the tool automatically visits the website, finds the reviews, and collects them for you. This protocol contains awareness on customer sentiments, tastes, and opinions about merchandise or solutions administered through these online sites. The sourced data can be filtered, organized, structured, and stored in a repository for subsequent analysis – for instance, market research, competitive analysis, and sentiment analysis. On the other hand, E-commerce Review Scraping must be done in the right way that supports the terms of use, robots.txt rules, and moral practices which will always keep the business on the right side of the law and ethics.

Tools for Scraping E-commerce Websites:

There are various tools available to scrape reviews from popular eCommerce websites  that can be easily utilized in strategic business decisions.


Scrapy is the scraping package which is open sourced and written in the Python language. It is meant to garner and not just any kind of data, but from websites in the most swift, competent and numerous manner possible. Scrapy is designed to help you get your data faster through an automated toolset that includes libraries for website scraping and structured data extraction. It can visit web pages, click on links, and grab data. It’s good at finding its way through big websites with many pages. It is best for large projects where you need to gather a lot of data from many different pages on a website.

Beautiful Soup:

A Python module termed Beautiful Soup is used to gather information from HTML or XML pages on the internet for the purpose of web scraping. It offers a collection of user-friendly tools for perusing and finding content within XML documents. The user can search for a specific text within the web page documents with the help of these tools. It can look at a webpage’s code and find the parts you’re interested in, like prices or product names. It is best for simple tasks where you want to find specific details on a webpage without doing a lot of complex navigation.


Web browser automation is the main use for Selenium, a potent open-source technology. Developers and testers may interact with web browsers programmatically with the help of a set of tools and libraries it offers, automating operations like form filling, button clicking, web page navigation, and content scraping. It can open web pages, click buttons, fill out forms, and even scroll down pages. It’s like having a virtual assistant browsing the web for you. It is best for websites with many advanced features that require you to log in to see the data you want.


Google created the Node.js module Puppeteer, which offers a high-level API for controlling Chromium or Chrome through the DevTools Protocol. It enables automated execution of many online-related tasks by developers, such as web scraping, automating browser activities, and creating screenshots. Puppeteer is similar to Selenium but works with the Chrome browser. It can do everything a browser can do, like open pages, click links, and take screenshots. It’s especially utilized at working with websites that use modern web technologies. It is best for websites built with new technologies or frameworks like React or Angular.

Key Highlights of the Web Scraping Tools:

When choosing a tool, think about the kind of website you’re scraping and what you want to do with the data. Each tool has its strengths, so picking the right one can make your scraping project much easier and more successful. These tools can be helpful for businesses when they leverage web scraping services from experts:

  • Scalability:

If you’re planning to scrape many pages or websites, Scrapy or Puppeteer might be your best choice for a smooth review scraping process. They can handle big tasks without getting overwhelmed.

  • Ease of Use:

Beautiful Soup is a great starting point if you’re new to scraping or want something straightforward. It is the beginner-friendly option that gets the data extraction process done.

  • Flexibility:

If you need a tool to handle tricky tasks or work with complicated websites, both Selenium and Puppeteer are flexible and can adapt to different situations.

How to Scrape Reviews from e-Commerce Websites?

The steps for scraping product and customer reviews from e-commerce websites to ensure smooth data extraction process:

  1. Choose the Right Tool:

Pick a tool that helps collect data from websites which includes some popular choices are Scrapy, Beautiful Soup, and Selenium. Experts should choose the most suitable tool and technologies suitable for project requirements.

  1. Identify the Target Website:

Choose an e-commerce website, like Amazon or eBay, where you want to scrape reviews. Check the website’s terms of service to make sure scraping is allowed. It also requires ethical practices to ensure a smooth extraction process.

  1. Inspect the Website:

Use the browser’s “Inspect” tool to see where the reviews are on the webpage. Experts can look for labels or names like “review” or “rating” in the website’s code. They can extract the reviews by using automated methods.

  1. Write the Scraping Code:

Write instructions for the tool to find the product pages, load reviews, and copy the review details to ensure a smooth extraction process.

  1. Handle Pagination:

Some websites have many pages of reviews which makes it tough to extract reviews in one go. Experts can use the tool where it becomes easy to go to the next page to get all reviews.

  1. Implement Delays:

To ensure a safe extraction process, make the tool wait a bit between actions to avoid being blocked by the website.

  1. Store the Data:

After the extraction process, this data can be saved in the required format. Experts can save the scraped reviews in files like Excel or in a database for easy access and analysis.

  1. Respect Robots.txt:

Check if the website has a “robots.txt” file to see if scraping is allowed or restricted.

  1. Test Your Script:

Before scraping many pages, test your tool on a few pages to make sure it works correctly.

Applications of E-commerce Product Review Scraping:

Ecommerce review scraping can be done by using modern tools and techniques. A variety of web scraping services are available to extract popular e-commerce websites, providing useful information to companies in the e-commerce industry. These are a few important uses:

  1. Understanding Customer Preferences:

E-commerce websites have a lot of product reviews written by customers. By scraping these reviews, businesses can learn what customers like or dislike about products.

  1. Brand Monitoring:

Businesses can keep an eye on what customers say about your brand or products. It helps businesses know if there are any problems or complaints that need to be addressed.

  1. Competitor Analysis:

It becomes easy to look at what customers say about your competitors’ products and services. It helps businesses spot opportunities to improve their own products or offer something better.

  1. Natural Language Processing (NLP):

NLP is using technology to understand and analyze human language. NLP helps in developing voice assistants, translation services, and other smart technologies. The text from scraped reviews can be used to train NLP systems to better understand customer feedback.

  1. Fraud Detection:

It is finding and stopping counterfeit or fake products on the website. It is important that counterfeit products can harm a brand’s reputation and sales. It helps businesses by Negative reviews might hint at fake products. By scraping reviews, businesses can identify sellers who might be selling inauthentic items and take action.


Web scraping services can be helpful in gathering information, but it’s essential to do it legally, ethically, and respectfully of the website’s rules and users’ privacy. Always check the website’s terms and follow best practices when scraping.  These tools also give companies unique insights they wouldn’t easily find on their own. For instance, companies can decide on the best prices to make more money by checking how prices change over time. This helps them make better decisions, make their products look better online, and keep up with the competition onlineEcommerce review scraping helps businesses listen to customers, improve products, protect their brand, stay competitive, advance technology, and fight against fake products.

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