How to Use Web Scraping to Extract Product Data From E-Commerce Sites
E-commerce

Web Scraping to Extract Product Data From E-Commerce Sites

Price differentiation has been a classic tried-and-tested strategy for attracting more clients and building brand loyalty. The success of this approach is no surprise considering that nearly 87% of Americans believe that price is the primary factor while making an online purchase decision. Further, 17% claim that they compare the prices from two or more stores before successfully making a purchase.

Web Scraping to Extract Product Data From E-Commerce Sites

However, in the present scenario, the heated competition between various e-commerce platforms has branched out beyond pricing. It now revolves around product data, which impacts everything from sales strategy to inventory management. The data gathered from various sources equips you with all the arms and artillery required to emerge victorious from the e-commerce wars.

And how do you arm yourself with this information?

The answer is web scraping.

Web scraping offers you a bird’s eye view of the pricing data, market conditions, prevailing trends, strategies employed by your competitors, and the challenges faced by them. Accordingly, you can position your product with all the above considerations in mind, which will give you an unfair advantage over the others.

Let’s take a look at how web scraping can extract product data from e-commerce sites, thereby giving you a headstart.

Why Web Scraping is the ideal solution for extracting product information from e-commerce sites

Depending on the product you’re planning to market, your competitors may range upwards of tens and thousands. It isn’t feasible to put humans on the job of extracting product information in bulk by copy-pasting data from web pages. It not only drains your resources but makes the data prone to human errors.

That’s where web scraping is useful.

Web scraping is the process of automating the process of data extraction in a fast and efficient manner. It implements the use of crawlers or robots that automatically scan specific pages on a website and extract the required information.

In this particular case, a web scraping software can browse through thousands of listings of your competitors’ products on an e-commerce site, and capture all the relevant details, like pricing, number of variants, customer reviews, etc., in a matter of few hours.

Not just that, it can even help extract data that is invisible to the naked eye or can’t be copy-pasted. Moreover, it can also take care of saving the extracted data in a meaningful and readable format. Usually, the extracted data is available in CSV format.

As you can see, web scraping can be a lot useful in extracting product data from e-commerce websites, no matter how large the data is.

How can product data be scraped from e-commerce sites on a large scale?

For the extraction of product data on a large scale, you can implement a piece of code (called a ‘web scraper’) that requests a particular product page on an e-commerce website. In return, the website replies with the requested web page.

Once the page is received, the scraper will parse its HTML code and extract relevant data from it. When the data extraction process is completed, the tool finally converts the data into the desired format.

Now, since the web scraper is an automated program, it can repeat this process thousands of times on a large number of product pages, and across several e-commerce websites.

Also Read: The Art of Emotional Branding and Understanding Customer Emotions

How extracting data from e-commerce sites benefits businesses

Now that you know how to scrape product data from e-commerce websites, you must be wondering what you can do with it. Well, here are a few practical use cases:

1.Price Optimization

Price optimization and comparison continues to remain the key highlight of data collected through scraping e-commerce sites. Everyone from eBay to Amazon makes use of this feature to keep an eye on the competition. It collates data from various sources and presents it to the business owner, who can then analyze the pricing patterns and put a competitive price tag on their products. It is a well-known fact that price optimization boosts e-commerce store profits.

2. High-Quality Lead Generation

The growth of a business rests on the shoulders of effective marketing. However, for marketing efforts to take fruit, the business needs to generate leads. Web scraping can collect high volumes of data, which will subsequently trigger lead generation. Through its surgical precision, it can generate lead data quickly and accurately. Plus, this information will be in CSV or similar formats, which can be easily processed or integrated with other tools.

3. Product Launch and Development

When you’re pitching a new product on your e-commerce platform, you need to conduct market research (at least at some level) and learn about the demand for such a product. There are always questions that you need to get answered. How do your competitors price their products? What kind of deals do they offer? Is there any specific time of the year when the demand surges (like holiday season)? Do they target a specific demographic?

On the deeper analysis of these facets, you can formulate a strategy that is near-about perfect for the said product, without having to run it past a trial-and-error method. Through this method, you save a significant amount of time that would have otherwise been wasted in researching and analyzing the market. You are basically smiting the iron while it is hot!

4. Analyze & Predict Market Trends

Sometimes, the market is not as black and white as selling woolens during winters. E-Commerce is transforming rapidly, and you need to keep up with it.

When it comes to finalizing sales, timing is everything. Scraping e-commerce sites and monitoring similar or competitor products over several months can help provide insights on a specific market and product trends. These data points can help you predict the best time to launch a product and at the most optimal price. Competitive pricing and in-season launch will result in a magical recipe that will boost sales.

Further, depending on the prevailing or projected market trends, you can effectively manage the stock and inventory of your products.

5. Learn About the Customer

You can also implement web scraping to find out how the customer feels about specific products, preferences, choices, and purchase patterns. Customer feedback can help you identify potential gaps between supply and demand. Customer data also opens up the scope for an improved product line, which addresses customer pain points. At the same time, based on the way customers post their reviews, you can analyze what he or she is looking for in a specific product, what’s their preference, and so on.

Furthermore, customer data offers you a peek into the customer’s world and their behaviour. Accordingly, you can personalize your services to meet their requirements. Providing top-notch customer services will earn you brownie points.

Challenges with large-scale data extraction and product data scraping

When it comes to web scraping, not everything is a bed of roses; it has its fair share of thorns too. E-Commerce websites, especially your competitors, do not want you stealing information from their websites. And as web scrapers get better and more effective at extracting product data, the website admins are also coming up with creative ways of thwarting such attempts.

Here are some of the challenges that might keep you from using web scrapers:

1.Site Design and Layout Changes

A web scraper is based on the structure of the website. However, this structure is prone to changing and that too often, which could be a pain point for web scraping companies. Whether it’s intentional, or just amateur coding standards, an e-commerce website may be difficult to navigate with bots due to the design and structure, or the ever-changing layout of the website. Keeping up with all these changes requires time and effort.

2. Use of Unique Elements

Modern elements in website design can enhance their responsiveness. However, it makes a trade-off as web scraping becomes even more difficult. Design elements introduce complexities that might sometimes slow down or interrupt efficient scraping of data.

In addition to these modern elements, the inclusion of dynamic content that makes use of transitions like lazy loading images, show more info, and infinite scrolling, make it difficult for the scraper to read the data.

3. Use of Anti-Scraping Technologies

Websites may use multiple security protocols and techniques to block potential scraping attempts. Some of these techniques include content copy protection, using JavaScript for rendering content, user-agent validations, etc.

Also Read: How to Bypass Anti-Scraping Tools on Websites

Additionally, websites can track which IP address your requests are coming from. If they flag any request as suspicious (e.g., sending too many requests within a short time), they might ban the particular IP address from sending further requests. The issue worsens with the fact that you cannot mask your IP address because websites can detect and block IP addresses from well-known rotating IP providers as well.

4. HoneyPot Traps

Websites responsible for storing sensitive data ensure the protection of information through HoneyPot traps, which can detect scrapers and crawlers. Through this method, they strategically place invisible links on a webpage that are not meant for visitors but are present for scrapers. These are specially designed to trap and block web scrapers and bots as soon as they attempt to crawl them. On setting off the trigger, the IP address corresponding to the scraper is instantly blocked.

5. Use of CAPTCHAs

Fun Fact: The technology behind CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) is based on the Turing Test, which can test whether a machine can think like humans!

The very role of CAPTCHA is to block automated scripts from performing repetitive actions on a website. It essentially brings an element of randomness into an otherwise predictable workflow. Web scrapers are tasked to decipher images containing distortions and randomness. Solving captchas is something that a robot cannot perform successfully!

How Datahut can help e-commerce stores scrape product data and overcome challenges

Given the challenges posed to web scraping, extracting and leveraging data from E-Commerce sites may appear to be an intimidating task. However, with Datahut, you can easily extract product data from e-commerce sites as per your requirements!

Datahut helps in the implementation of various strategies to bypass anti-scraping mechanisms used by websites and helps you extract the data that you need. Some of the ways through which Datahut gets around anti-scraping tools include:

  • Using rotating, residential IP addresses
  • Using real user-agents
  • Sending requests at various intervals from different IP addresses
  • Pre-detecting and avoiding traps
  • Using Captcha solving services to bypass captchas
  • Keeping up to date with website changes

 At Datahut, we specialize in data extraction and can help you capture product data on a large scale. So go ahead, give Datahut a try for all your data extraction requirements!

About the author

Bhagyeshwari Chauhan

Content creator and Digital Marketing Strategist at Datahut