Scraping for eCommerce: Extracting Product Data for Competitive Insights

Reading time: 11 min read
Marco Rodrigues
Written by
Marco Rodrigues

Updated · Aug 21, 2023

Marco Rodrigues
Software Engineer / Python | Joined July 2023 | LinkedIn
Marco Rodrigues

Meet Marco Rodrigues, a trailblazer with a Master's in Nanotechnology and Microelectronics. A Softwa... | See full bio

Lorie Tonogbanua
Edited by
Lorie Tonogbanua

Editor

Lorie Tonogbanua
Joined June 2023 | LinkedIn
Lorie Tonogbanua

Lorie is an English Language and Literature graduate passionate about writing, research, and learnin... | See full bio

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In the rapidly evolving world of eCommerce, staying ahead of the competition is crucial for companies seeking to maintain their edge in the market. One powerful tool that has emerged to provide valuable insights and competitive advantage is web scraping.

By extracting product data and monitoring price changes from competitors, eCommerce giants can gain real-time updates and leverage these insights to enhance their own strategies.

Additionally, via web scraping, eCommerce companies can explore trends and customer preferences on social media platforms, make informed decisions, and adapt their offerings to meet the ever-changing demands of their customers.

All of this information can be crucial to running a successful eCommerce business. However, scraping at scale requires advanced technologies capable of bypassing the intricate defenses put in place by websites to protect their data.

This is where Bright Data’s Scraping Browser comes in. The Scraping Browser is an all-in-one solution that seamlessly integrates a real, automated browser with powerful out-of-the-box unlocker infrastructure and proxy/fingerprint management services.

It is a headful GUI browser compatible with Puppeteer/Playwright APIs, featuring built-in block bypassing technology. 

With its innovative AI-embedded technology, this cutting-edge solution enables seamless scraping at scale, offering eCommerce companies high scalability and a robust foundation to extract valuable data efficiently. 

In the following sections, we will delve into the capabilities of the Bright Data Scraping Browser, exploring how it can revolutionize the way eCommerce companies leverage web scraping for competitive insights.

Before we do that, let’s get some hands-on experience with the Scraping Browser and see for ourselves how it enables us to efficiently extract data at scale, extract valuable insights and get ahead of the competition.

Key Takeaways

  • E-commerce scraping is a valuable data collection activity for businesses to gain market insights and competitive advantage.
  • Bright Data’s Scraping Browser is an all-in-one web scraping solution that any business can take advantage of.
  • Headful browsers have the highest chance of overcoming anti-scraping measures by most websites.
  • Scraping Browser simulates headful browsers with the added advantage of streamlined proxy management and compatibility with other headless browsers.

Getting Started with the Scraping Browser

Headful browsers with a full Graphic User Interface (GUI) stand the best chance of not being detected by anti-bot measures and being blocked, but they are performance intensive. They can’t always be a solution, especially for serverless deployments.

The Scraping Browser is a highly advanced web scraping solution that remedies this by streamlining anonymous web scraping.

It is the best of both worlds – a potentially unlimited number of remote, headful browser instances running on Bright Data’s servers that you can seamlessly integrate with traditional headless Puppeteer/Playwright/Selenium workflows via the Chrome DevTools Protocol (CDP) over a WebSocket connection.

On top of making headful scraping viable, the Scraping Browser uses AI and Bright Data’s powerful unlocker infrastructure to efficiently bypass website blocks and anti-scraping measures. 

The possibility of multiple concurrent remote sessions makes the Scraping Browser an excellent choice for scalable data extraction in the field of eCommerce. Learn more about its capabilities here: 

https://brightdata.com/products/scraping-browser

To begin using the Scraping Browser, you need to first register on Bright Data's website (which is free). Here’s how to do it:

  1. To sign up, go here and click the 'Start Free Trial' button, then enter your information (you can also use your regular email address).
  2. Once you’re done signing up, go to your Dashboard and select Proxies & Scraping Infrastructure.
  3. Select the feature Scraping Browser.

Proxies & Scraping Infrastructure

Proxy solutions on Bright Data

As mentioned, the Scraping Browser comes out of the box with integrated unlocking capabilities and premium quality proxy services for every use case, enabling you to bypass website restrictions when scraping data at scale.

scraping data at scale

Browser Configuration on Bright Data

Activate the Scraping Browser, and you will be able to access and navigate websites via headless browsers such as Puppeteer and Playwright. Bright Data provides a $5 credit to try out without additional costs.

Activate a free trial

Activate a free trial on Bright Data

How to Scrape Amazon Listings with the Scraping Browser (and Playwright) 

As I’m writing this article on my trusty Lenovo, why not gather valuable information about Lenovo’s computers available on Amazon?

Amazon Listings with the Scraping Browser

Amazon’s Lenovo search

For our first scraping attempt, we can use Playwright, which can be installed using Python’s pip command.

pip install playwright

In the Access Parameters under the Scraping Browser window, you’ll find the API credentials: username (Customer_ID), zone name (attached to username), and password.

Access Parameters

Access parameters on Bright Data

These credentials can create a session in Playwright or any supported headless browser. 

Let’s open a Python file and start by creating some variables with the latter credentials.

import asyncio
from playwright.async_api import async_playwright

#username, password and host provided by the Scraping Browser.
auth = '<username>:<password>'
browser_url = f"wss://{auth}@<host>"
item = "lenovo"
website_to_crawl = f"https://www.amazon.com/s?k={item}"

The browser_url variable makes the remote connection between the client and Bright Data’s server, by using the WebSocket protocol (wss://). The client initiates the request, and the server responds if it accepts the connection.

Once connected, both the client and the server can share data using an API, which, in this case, is composed of the provided username and password (auth).

In the script above, we also specified the item (lenovo) and the website (https://www.amazon.com) we wanted to scrape.

With the help of Bright Data’s comprehensive documentation for seamless integration, I built the following script to scrape the Amazon website.

async def main():
  async with async_playwright() as pw:
      print('connecting')
      # attach Playwright to the Bright Data browser
      browser = await pw.chromium.connect_over_cdp(browser_url)
      print('connected')
      # create a new page
      page = await browser.new_page()
      print('goto')
      # go to Amazon website
      await page.goto(website_to_crawl, timeout=120000)
      print('done, evaluating')
      # extract information about the items
      items = await page.query_selector_all(
          '.a-section.a-spacing-small.a-spacing-top-small')
      for item in items:
          title_element = await item.query_selector(
              'span.a-size-medium.a-color-base.a-text-normal')
          title = await title_element.evaluate(
              '(element) => element.textContent') if title_element else None
          price_element = await item.query_selector('span.a-price')
          price = await price_element.evaluate(
              '(element) => element.textContent') if price_element else None
          rank_element = await item.query_selector('span.a-icon-alt')
          rank = await rank_element.evaluate(
              '(element) => element.textContent') if rank_element else None
          elements = {'title':title, 'price':price, 'rank': rank}
          print(elements)

      await browser.close()

if __name__ == '__main__':
  # create a coroutine object for asynchronous and concurrent programming.
  coro = main()
  asyncio.run(coro)

There’s one key command requiring further explanation:

browser = await pw.chromium.connect_over_cdp(browser_url)

The connect_over_cdp() Python method attaches Playwright to the remote Bright Data browser instance (more about it here) using the Chrome DevTools Protocol, which is only supported by Chromium-based browsers.

Developers use the Chrome DevTools Protocol to automate tests, web scraping, and perform other browser interactions.

The script scrapes the first page of Amazon’s results for Lenovo and extracts information about each item's title, price, and ranking.

{
'title': 'Lenovo 2023 Thinkpad X1 Carbon Gen 9 14.0" WUXGA IPS Low Blue Light Business Laptop, Intel Core i7-1185G7 vPro, 16GB RAM, 512GB PCIe SSD, Intel Iris Xe Graphics, Win11 Pro, Black, 32GB USB Card',
'price': '$1,479.00$1,479.00',
'rank': '4.3 out of 5 stars'
}

This is just a simple example to showcase the power of the Scraping Browser. If I were to perform the same task using my local IP, chances are that Amazon would block me at some point because of:

  • CAPTCHAs and other verification tools can easily block automated scraping.
  • IP Blocking: Excessive requests can be detected from a single IP address resulting in being blocked in an undetermined period of time.
  • Inaccurate scraping: Because of bots, numerous HTTP requests, and errors, the scraping script must be in constant mutation. If not, chances are that the extracted data might be inaccurate and not what we are looking for.
  • Legal consequences: Scraping needs to be performed without violating the terms of service, or you can end up in legal hot water.

Manual scraping has some strategies to bypass the latter obstacles, such as:

  • IP Rotation: Use VPNs and proxy services to change the IP constantly.
  • Add delays to mimic human behavior: This makes the scraping take much longer, and it’s not suitable for Big Data and eCommerce.
  • Deal with HTTP responses: Adjust code to errors and different HTTP responses.
  • Deal with bot blockers and CAPTCHAs: by adjusting the script and using third-party CAPTCHA-solving services.

Helpful Articles: Techjury has valuable and beginner-friendly articles about manual scraping scripts. Check out our articles on How to Crawl and Scrape Websites in Javascript and How to Rotate Proxies in Python.

These are time-consuming, difficult, and expensive to implement, and they are definitely not scalable solutions when scraping critical data at an enterprise level.

Let’s take a deeper look into the benefits of using the Scraping Browser over more traditional approaches.

Advantages of Using the Scraping Browser Over Other Approaches

The greater the degree of accuracy, smoothness, and uninterruptedness of the data-gathering process, the faster an eCommerce company can gain insights and get ahead of its competitors. To achieve this, any scraper:

  • Must consistently gather current, up-to-date data from diverse sources, encompassing product details, titles, rankings, prices, reviews, and more.
  • An efficient scraping solution should operate seamlessly, avoiding blocks, minimizing significant delays, and reducing the need for time-consuming and costly additional integrations.
  • As an eCommerce company grows and expands its operations, it becomes essential for the web scraping solution to be viable at scale. This means that the scraper should be capable of efficiently handling large data and concurrent requests.

The Bright Data team checks all the previous points by focusing on three main pillars:

  • Scalability: The Scraping Browser is able to scale horizontally by distributing the scraping workload across multiple servers and instances to ensure optimal performance and avoid bottlenecks – all without any infrastructure required on your part.
  • Support: Bright Data account managers, product managers, and developers bring their expertise to solve any business needs. Companies can rely on strong and on-demand support with Bright Data. 
  • Compliance: Bright Data’s privacy practices comply with data protection laws, including the EU data protection regulatory framework, GDPR, and the California Consumer Privacy Act of 2018 (CCPA).

Helpful Article: Check out Techjury’s article titled Web Scraping VS. API: Which One’s Best For Data Extraction to learn more about the difference between web scraping tools and the official APIs websites provide.

Since the Scraping Browser incorporates all of Bright Data’s advanced features in a complete out-of-the-box solution, you also get the following advantages:

Unlocker Infrastructure

The Scraping Browser incorporates Bright Data's powerful unlocker infrastructure, providing seamless emulation of header information and browser details.

This effectively overcomes IP/device fingerprint-based website blocks and reliably solves CAPTCHAs and other JavaScript-based challenges (Cloudflare etc.) without requiring the integration and maintenance of third-party libraries on your end.

To learn how the unlocker infrastructure helps overcome website blocks in greater detail, give this article a read.

Streamlined Proxy Management and Rotation

The Scraping Browser streamlines proxy management and rotation, automating the process for you. You can concentrate on your core scraping logic while Bright Data takes care of handling proxies.

It automatically rotates a diverse range of proxies, including residential, data center, ISP, and mobile, while also incorporating automatic retries.

This dynamic approach enables you to seamlessly circumvent geo-blocks, ReCAPTCHAs, rate-limiting, and other obstacles.

You can find more about the different proxy services and their use cases in web scraping here.

Overcomes Headless Browser Limitations

Bright Data's Scraping Browser will help you increase the performance of your scraping process and even completely avoid some Puppeteer/Playwright problems.

By automating proxy management and CAPTCHA solving in a best practices manner and leaving nothing to chance, you can ensure that your scraping stack behaves in the most correct, consistent, and fastest manner possible.

Manual web scraping workflows might work for less demanding websites or when dealing with a small volume of data. However, it is crucial to acknowledge that there exists a cost threshold when scraping a website.

This necessitates frequent proxy rotation, implementing anti-bot blocking measures, and requiring continuous script modifications.

Discover how proxy networks works from this video by the data scientist Greg Hogg in partnership with Bright Data.

The manual approach might actually end up being more burdensome in terms of both time and financial resources. That’s where the Scraping Browser can help.

Conclusion

In conclusion, Bright Data’s Scraping Browser is a comprehensive zero-to-low infra solution with advanced technology, seamless integration with automated browsers, and powerful unlocker infrastructure enabling efficient data extraction at scale.

Migrating from your local scraping script to the Scraping Browser is very simple, thanks to its compatibility with Puppeteer/Playwright and other developer-friendly features.

Also, when you factor in its compliance with major data protection laws, the Scraping Browser is a superior choice compared to manual scraping and other solutions, empowering eCommerce businesses to thrive in a highly competitive landscape. 


Sign up for the Scraping Browser today (it’s free!) and harness the power of uninterrupted web scraping at scale to gain the insights you need, stay ahead of competitors, and drive your eCommerce business to greater achievements.

FAQs.


How can I scrape data from an eCommerce store?

You can create web scraping scripts using libraries like Puppeteer or Playwright. To avoid IP blocks, you can integrate scraper APIs like the Scraping Browser from Bright Data.

What is scraping in marketing?

Businesses can scrape valuable data for marketing purposes, such as search engine results from relevant keywords to their brands; or influencers' names and contact information for potential affiliate partnerships.

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