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Gabija Fatenaite

Jun 02, 2020 9 min read

Web scraping is somewhat complicated – from the definitions to the possible applications in businesses, as well as the power it has to shape the future of businesses. And of course there is another commonly heard term – web crawling. You may have heard that these terms are used as the same meaning, so it’s important to understand the differences between web scraping vs. web crawling. In this article, we’ll go over this step by step, so let’s get started. 

For easier navigation, you’ll find the main topics of this article below: 

The definitions

It might sound the same, however, there are some key differences between scraping vs. crawling. Nevertheless, these two terms are closely intertwined. Both scraping and crawling go hand in hand in the whole process of data gathering, so usually, when one is done, the other follows. 

Let’s start with the definitions. Essentially, there are a couple of ways to describe the same action that scraping entails:

  • Web scraping  or data scraping

Same goes for crawling:

  • Web crawling or data scraping

Web is anything found on the internet, and data is information, statistics, and facts that can be found anywhere (not only the internet). This helps us to answer the differences between the above-mentioned action descriptions.

What is data scraping?

Data scraping is when you take any publicly available data, whether it is on the web or your computer, and import the found information into any local file on your computer. It is very important to note that data scraping does not require the internet to be conducted.

What is web scraping?

Web scraping is when you take any online publicly available data and import the found information into any local file on your computer. The main difference here to data scraping is that web scraping requires the internet to be conducted.

These definitions also work for crawling too. If it has the word web in it – it involves the internet.

If it consists of the word data – it does not necessarily need to include the internet in the crawling actions. 

What is crawling?

Web crawling (or data crawling) is used for data extraction and refers to collecting data from either the world wide web, or in data crawling cases – any document, file, etc. Traditionally, it is done in large quantities, but not limited to small workloads. Therefore, usually done with a crawler agent.

According to our python developer Bernardas Alisauskas, a crawler is “a program that connects web pages and downloads their contents.” 

He explains that a crawler program simply goes online to look for two things:

  1. Data the user is searching for
  2. More targets to crawl

So if we tried to crawl a real website, the process would look something like this: 

  1. The crawler goes to your predefined target – http://example.com
  2. Discovers product pages
  3. Then finds the product data (price, title, description, etc.)

The product data found by a crawler then will be downloaded – this part becomes web/data scraping.

In this article, you’ll see us using these terminologies interchangeably, as to keep in sync with the examples and outside studies. Just keep in mind that in most of these instances, it will mean web scraping/crawling, rather than data scraping/crawling, turning a blind eye to their precise definitions. 

Web Crawling vs. Web Scraping
Web crawling vs. web scraping

Web crawling vs. Web scraping: the differences

The question arises: how crawling is different to scraping?

To generally understand the main scraping vs. crawling differences, you need to notice that crawling means going through and clicking on different targets, scraping is the part where you take the found data and download it into your computer, etc. Data scraping means you know what you want to take and then take it (e.g., in web crawling/scraping cases usually what can be scraped are product data, prices, titles, descriptions, etc.).

It’s important to understand the main web crawling vs. web scraping differences, but also, in most cases, crawling goes hand in hand with scraping. When web crawling, you download readily available information online. Crawling is used for data extraction from search engines and e-commerce websites and afterward, you filter out unnecessary information and pick only the one you require by scraping it. 

However, web scraping can be done manually without the help of a crawler (especially if you need to gather a small amount of data). In contrast, a web crawler is usually accompanied by scraping, to filter out the unnecessary information. 

So, scraping vs. crawling (or web scraping vs. web crawling) – let’s sort out all of the significant differences between these two to see a clearer picture of both: 

Movement:

  • Web scraping – only “scrapes” the data (takes the selected data and downloads it).
  • Web crawling – only “crawls” the data (goes through the selected targets).

Labour:

  • Web scraping – can be done manually by hand.
  • Web crawling – can be done only with a crawling agent (a spider bot).

Deduplication

  • Web scraping – deduplication is not always necessary as it can be done manually, hence in smaller scales. 
  • Web crawling – a lot of content online gets duplicated, and in order to not gather excess, duplicated information, a crawler will filter out such data.

Or, you can check out our video in the simplified version of the differences between crawling vs. scraping:

Data scraping for business

Data scraping has become the ultimate tool for business development over the last decade. According to Mckinsey Global Institute, data-driven organizations are 23 times more likely to acquire customers. They are also six times more likely to retain customers, and 19 times more likely to be profitable. Leveraging this data enables enterprises to make more informed decisions and improve customer experience.

As the internet and its usability expands, the number of data-driven companies only keep on growing. According to Forrester, the average growth of such businesses is around 30% each year. It is estimated that by 2021, they will overtake their less-informed industry competitors by $1.8 trillion annually. 

Data-driven, and consequently, insight-driven businesses outperform their peers. By tracking consumer interaction and gaining an in-depth understanding of their behaviors, companies can improve their customer experience. This, likewise, impacts lifetime value and increases brand loyalty.

It’s evident that data scraping has an influence in almost any business area. As data increasingly becomes the primary source of competition, acquiring the data becomes especially important. There are many business areas, where data scraping has a strong influence on performance, and how it helps make a business more insight-driven:

  • Competitor analysis and pricing: for a reliable pricing strategy, web scraping could help you extract the pricing intel of your competitors. You can also track their further pricing tactics, discounts, and online behavior. 
  • Marketing and sales: data scraping can help you with conducting market research on your competitors, gathering additional leads, analyzing people’s interests, and monitoring consumer opinion by regularly extracting customer ratings from different platforms. For example, web scraping real estate data helps to remain competitive in the market. Also, automotive industry data supports the predictive analysis of the market.
  • Product development: web scraping e-commerce websites can be done for product descriptions, or to check your stock status across thousands of marketplaces and retailers’ sites.
  • PR, brand, and risk management: with data scraping, you’ll be able to detect ad fraud, improve ad performance, and check advertisers’ landing pages, as well as monitor your brand mentions and take appropriate actions.
  • Strategy development: for a strong strategy, you require substantial facts. Data scraping allows you to carry out an analysis of the latest trends in the industry, allowing you to monitor SEO and the latest news.

If you wish to read more on how to use proxies for business, you can find it in our blog post.

Conclusion

The definitions of data scraping, data crawling, web scraping, and web crawling have become more transparent. To recap, the main web crawling vs. web scraping differences: crawling means going through data, and clicking on it and scraping means downloading the said data. As for the words web or data – if it has the word web in it, it involves the internet. If it consists of the word data, it does not necessarily need to include the internet in the crawling actions. 

It is now clear that data scraping is essential to a business, whether it is for customer acquisition, or business and revenue growth. The future of data scraping also looks busy – as the internet becomes the main starting point for businesses to collect intelligence, more and more publicly available data will be required to scrape in order to get business insights and stay above the competition. 

If you want to find out more about data gathering solutions or you are already interested in web scraping and want to start your web scraping project, check out our other blog posts. You will find answers to all of your questions on proxies, web data gathering and more!

FAQ

Is web scraping legal?

It depends on what purpose web scraping is used for and what data it takes. If web data is publicly available and not copyrighted it’s legal for web scraping. If you want to read more about this topic, check out our blog for scraping cases that set the tone for future scraping legal claims: The Legal Framework of Data Scraping

What is the point of web scraping?

If you need to gather a small or large amounts of data, you can use web scraping in a fast and convenient way. In many cases it’s used to make data gathering process and help extract data from web much more easier and in an efficient way.

What is the meaning of data crawling in Internet?

A web crawler (or a spider tool) is an automated script that helps you browse and gather publicly available data on the web. Many websites use data crawling to get up-to-date data.

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About Gabija Fatenaite

Gabija Fatenaite is a Content Manager at Oxylabs. Having grown up on video games and the internet, she grew to find the tech side of things more and more interesting over the years. So if you ever find yourself wanting to learn more about proxies (or video games), feel free to contact her - she’ll be more than happy to answer you.

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All information on Oxylabs Blog is provided on an "as is" basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Oxylabs Blog or any third-party websites that may be linked therein. Before engaging in scraping activities of any kind you should consult your legal advisors and carefully read the particular website's terms of service or receive a scraping license.