With a share of over 45% of the US eCommerce market, scraping Amazon reviews can be a process by which you can extract valuable information from customer reviews. Product development, market research, and competitive analysis can benefit from this data. Amazon disrupts well-established industries with its technological innovations. We can also gather useful information since it is the world’s largest online retailer.

You can obtain data from different websites in several ways. You can browse any website, copy and save the information you want to your local hard drive, and then you can access it later. That may sound simple, but what if you need to browse hundreds or even thousands of pages to find the information you seek? It is no longer feasible to carry out the task manually. As they say, modern problems demand modern solutions.

An easy and effective method of obtaining data from a website is to scrape it. Using this technique, you can extract data from a web page and store it in local storage or a database. This article aims to illustrate why you should scrape Amazon reviews, the benefits of scraping Amazon customer reviews using Node, and Amazon review scraping with Node.js code.

Why Scrape Amazon?

Without a doubt, Amazon is the world’s leading e-commerce platform. Nevertheless, they continue to provide the most valuable data and analytics for anyone selling online due to the sheer volume and variety of products they offer.

Female giving review

eCommerce platforms like Amazon contain vast data crucial to online retailing. Many businesses benefit from scraping Amazon data because it is easily accessible, and anyone can access it. You can develop an accurate business strategy and make decisions by gathering data on competing products. Additionally, you can analyze product reviews for your product or a competitor to evaluate its performance and determine ways to improve the customer experience.

For the most part, consumer reviews provide a different viewpoint when evaluating various eCommerce business decisions. Therefore, scraping Amazon reviews can provide a wealth of inspiration, insight, and data.

How Does Web Scraping Work?

Scraping a website is using bots and extracting the content and data from a website using web scraping programs. In contrast with screen scraping, web scraping ads data to a database by extracting underlying HTML code. It is then possible for the scraper to replicate the entire website content elsewhere.

Benefits of Scraping Amazon Reviews

As e-commerce evolves, intelligent and targeted marketing is becoming increasingly important. Most shoppers now shop online, and the same is true for sellers who build portfolios through platforms such as Amazon, Flipkart, eBay, Ali Baba, etc. Approximately 225,000 sellers had a sale of $100K in 2019. The number of sellers had seen an increase of 12% since 2018.

Amazon sellers sales

Amazon sellers machine learning and artificial intelligence significantly predict the next big shopping trend and influence consumer preferences.

E-commerce dealers must use data analytics to optimize their offerings to convert their typical online consumer into a customer. You can benefit from Amazon reviews in the following ways:

  • Analyzing Competitors

The analysis of competition is one of the most important aspects of business decisions. By comparing and monitoring similar products of competitors, you can compare your products with those of your competitors.

Amazon dealers can develop proper marketing strategies by scraping Amazon’s data for competing products’ data. Online dealers can leverage web data for competitive pricing analysis, repricing, cost management, and seasonality tracking.

  • Manage Customer Satisfaction

Your business’s success depends on satisfying your customers. There is no doubt that keeping up with all of your reviews is a challenging task, especially if you’re a fairly big brand.

However, you can manage your reviews more efficiently using a review scraper. Using the right scraper, you will be able to identify any specific aspects of your product that need improving and assess your customers’ overall satisfaction with your product.

With the number of Amazon price trackers in the market, it is evident that it is the marketplace where everyone checks prices. The design, fit, or price may be a problem. For example, a footwear vendor can scrape his reviews to identify recurring complaints about certain product features. Using these insights, he could provide his customers with a more satisfying user experience.

  • Understanding Customers’ Demands

A seller’s ability to gauge the upcoming market trends can be tricky, even for the most experienced sellers. However, a customer’s product review can help identify new growth areas. Customer reviews often include product requests and recommendations. Smart sellers address these demands quickly and gain an edge over their competitors.

  • Identify the Highest-Rated Reviews

eCommerce businesses have their niche, and scraping customer profiles would have been an excellent way to generate leads. However, when it comes to protecting its customers personal information, Amazon’s policy on web scraping is stringent.

Sellers on Amazon switch strategies to obtain consumer databases. Increase sales by observing their shopping patterns. Another option is to scrape the top Amazon reviewers’ list.

If you launch a new product, you can ask these people to review it. We can use web scraping to obtain the data we need by scraping the list of top reviewers.

  • Monitoring Your Online Reputation

The reputation of small retailers and online product sellers is crucial to the success of their businesses. Using web scraping for Amazon reviews can provide small retailers with relevant data about the reputation of their products in the eyes of their customers, allowing them to monitor the reputation of their products. Incorporating Amazon data into key decision-making processes is possible by scraping Amazon data.

Best Tool to Scrape Amazon Reviews

Crawlbase is the best web scraping tool for automation features, user interface design, cost, and automation features. Regarding Amazon review scrapers, Crawlbase is a perfect option because it has a starting price of $29 a month and is cloud-based, meaning you don’t have to download anything to your computer to use it.

It is important to note that Crawlbase is one of the largest Amazon scraper on the market, and with its tools, you’ll be able to access a whole lot more than just Amazon product reviews. As a scraping provider, they have a wide variety of products that are tailor-made specifically for businesses looking to scrape content from the web and would like to ensure that their data is safe and protected. You can easily scrape Amazon product reviews with Node.js and Crawlbase.

With its features, you’ll also be able to access all publicly available data about a particular product on Amazon. As it is extremely easy to use, we think it would be a great option for anyone just starting with their web scraping needs and looking for a quick, easy, reliable option.

Why Use Crawlbase to Scrape Amazon Reviews?

The first step before you can start getting Amazon reviews is building a scraper, and there are various ways to do it. If you are not a programmer, however, do not worry. You have a product you can use for whatever needs you may have regarding web scraping. Amazon review scraping using Node.js is really simple, and you can easily use Crawlbase’s API as the foundation for a scraping tool.

It will be easier to scrape Amazon reviews using the Crawling API and help protect web crawlers against blocked requests, proxy failures, CAPTCHAs, etc. Efficient. Thousands of datacenter and residential proxies worldwide are also integrated into Crawlbase’s products, ensuring the best data results on the market.

Scraping Amazon Product Reviews with Crawlbase & Node.js

This article will demonstrate how to construct a scraper using Node.js to take advantage of Crawlbase’s API-based structure. The project efficiently scrapes product reviews from a list of Amazon URLs and saves them directly to a CSV file.

Rather than complicating this process, here is a list of things we need to accomplish.

  1. Crawlbase Account

To use the API, we need this. Your first 1,000 API calls are free. This will allow you to test the service and see if it meets your expectations. You can use the normal token instead of the Javascript token in this case.

  1. List of Amazon URLs to Scrape

Create a text file with one URL per line of Amazon product review links. This guide will refer to this file as “amazon-products.txt.”

List of Amazon URLs to Scrape
  1. Crawlbase’s NodeJS library

Crawlbase’s website provides free access to its libraries. You can find Nodejs under the libraries section once you log in.

  1. Github Node Cheerio Library

Look for cheeriojs/cheerio on Github

Utilizing Node.js Cheerio+Crawlbase

With everything you need for this project in hand, let’s get started. Start your favorite code editor. Use Visual Studio Code, one of Microsoft’s most popular free source-code editors that you can use on most platforms.

To start, we’ll need to install Crawlbase’s dependency-free module and the Cheerio Nodejs library. Enter the following lines in the terminal:

npm i cheerio

npm i proxycrawl

After installing the library, create a project folder and a file AmazonScraper.js inside it. Remember to include the amazon-products.txt file that you created earlier. Here is an example of our project structure:

Amazon products structure

Identifying constants in the function scope makes our code cleaner and more understandable. Let’s use the Crawlbase node library as the backbone of our scraper, utilizing the Crawling API. We must also use the Node Cheerio library to extract reviews from our URLs’ full HTML code.

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const fs = require('fs');
const { ProxyCrawlAPI } = require('proxycrawl');
const cheerio = require('cheerio');

Additionally, let us load the text file containing the URLs and the line that will allow us to insert your Crawlbase token.

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const file = fs.readFileSync('amazon-products.txt');
const urls = file.toString().split('\n');
const api = new CrawlbaseAPI({ token: 'YOUR_TOKEN' });

Now, we must insert a few more lines for the scraper to automatically send the reviews directly into a CSV file since we do not want this to display the results in the console. Fs.createWriteStream() is a function that creates a writable stream containing the path to the file in its parameters.

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const writeStream = fs.createWriteStream(‘Reviews.csv’);

//csv header
writeStream.write(`ProductReview \n \n`);

There is an excellent, fast, and flexible implementation of jQuery known as cheerio, which you can use to find out the section of users’ reviews on the Amazon web page, so that you can write these reviews into a CSV file. This function will parse the returned HTML code.

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function parseHtml(html) {
// Load the html in cheerio
const $ = cheerio.load(html);
// Load the reviews
const reviews = $('.review');
  reviews.each((i, review) => {
    // Find the text children
    const textReview = $(review).find('.review-text').text().replace(/\s\s+/g, ”);
    console.log(textReview);
    // write the amazon reviews into csv
    writeStream.write(`${textReview.replace(/Read more/, ”)} \n \n`);
});
}

In our final piece of code, we will make use of the scheduling timer setInterval(callback[, delay[, ...args]) method. Node.js uses this construct to call functions after a time period. Node.js script for Amazon review scraping is very simple and easy to understand. Using this method, our scraper can crawl the URLs in our list and scrape them. In this way, we can scrape the API 10 times per second.

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const requestsPerSecond = 10;
var currentIndex = 0;
setInterval(() => {
  for (let i = 0; i < requestsPerSecond; i++) {
    api.get(urls[currentIndex]).then(response => {
      // Make sure the response is success
      if (response.statusCode === 200 && response.originalStatus === 200) {
        parseHtml(response.body);
      } else {
        console.log(‘Failed: ‘, response.statusCode, response.originalStatus);
      }
    });
  currentIndex++;
  }
}, 1000);

Depending on whether you close or terminate the program, the code will run in a loop for a period of time, so add as many URLs as you want into the amazon-products.txt file, and the crawler will run through each URL and add all the users’ reviews in your CSV file that it can find.

It is important to note that the Crawling API will return a response or status code to the crawler each time it requests a specific URL. For pc_status and original_status, a successful request will return the value 200 in the case of a successful response.

The console log should show any errors our code encounters. There are no fees for failed requests with Crawlbase, meaning you will only pay for successful requests towards your API consumption.

If everything goes according to plan, you will have results that look like this:

Amazon product review

Conclusion

The code is ready, and once it runs, you can easily scrape 10 Amazon reviews simultaneously. For this post, we’re logging the results in the console, but you can replace the console.log with anything you wish. You can save it in a database, file, etc. It’s up to you.

The World Wide Web makes data accessible anytime, anywhere. Crawlbase makes it easy to build a web scraper, which is one of the best tools to farm data. This scraper will work with any Amazon URL containing a product review and save it to your CSV file. Alternatively, you can extract product prices and availability from the Cheerio library.

You can use a scraper on any website, not just Amazon. With Crawlbase’s flexibility, users can make it work with the most popular programming languages today. The API structure makes integration easy.

We hope you enjoyed this Node.js tutorial for Amazon review scraping and understand how to use Node.js for scraping Amazon reviews. Look forward to seeing you soon in our Crawlbase community. Have fun crawling! 😄