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Gabija Fatenaite

Dec 18, 2019 10 min read

Data scraping has become the ultimate tool for business development over the last decade. It currently has a significant influence in nearly any business area. As data increasingly becomes the prime source of competition, acquiring it becomes exceptionally important.

Web scraping (or data 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. 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: 

Web or data? Crawling or scraping? The definitions

Web crawling and scraping might sound the same. However, there are some key differences between both of the terms. 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 
  • Data scraping

Same goes for crawling:

  • Web crawling
  • Data crawling

Whether you choose to use the definition data scraping or web scraping (same goes with web crawling and data crawling), in fact, it doesn’t make that much of a difference. These definitions are commonly used in the sense of gathering data online and are usually used interchangeably without giving too much thought to it.

However, for the sake of being completely clear on the definitions, we’ll explain the differences between web and data scraping, as well as web and data crawling. 

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) refers to collecting data from either the world wide web, or in data crawling case – 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.

Please take a moment to check out his full article on web crawling. Bernardas goes into detail how web crawling works and its different crawling stages, so if you’re interested in this from a tech side of things, go check his personal blog out.

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

Crawling vs. scraping: the differences

The question arises: how crawling is different to scraping? Our data analyst, Martynas Juravicius, kindly informed us, there are a few ways crawling and scraping can be differentiated. So, please note that we will be going over one of the ways they can be distinguished. 

If 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.).

This means that crawling, in most cases, goes hand in hand with scraping. When web crawling, you download readily available information online. 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 – 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. 
  • 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.

The future of data scraping

Data scraping reigns in the present, but what about its future? According to Oxylabs Research Department’s data analysis based on our clients’ web scraping operations, data gathering has drastically increased over the course of a year. 

In Q2 2019, there was a substantial 53.3% request growth noted via data center proxies, comparing to Q2 2018 recorded metrics. 

data center - Data Scraping: The Powerful Force of the Business World

And, our Real-Time Crawler had an overwhelming 153.5% request growth over the course of a year. 

real time crawler - Data Scraping: The Powerful Force of the Business World

Based on these findings, it is safe to say that data scraping requirements will only continue to grow, and the data acquired will be used as primary source for business insights for future development. 

Data scraping solutions

For any web scraping operation, you’ll need a vast amount of proxies to successfully connect to the desired data source through your automated web scraping script. The proxies you set up will gather the required data from publicly available sources, slipping under anti-scraping measures.

There are two main types of proxies: data center and residential proxies. Both of these proxy types work for most scraping jobs. However, they work better in specific areas. Below you’ll see which proxy type works with which use case:

Data center proxiesResidential proxies
Market research Travel fare aggregation
Brand protectionAd verification 
Email protection

Building your own proxy infrastructure, however, requires a lot more resources and high maintenance. For this reason, it’s a lot more efficient to choose automated data collection tools. At Oxylabs, we have two tools for data scraping:

  • Real-Time Crawler
  • Web Scraper

What is Real-Time Crawler? It is a data collection tool explicitly built for data extraction from search engines and e-commerce websites with a 100% success rate, also known as real-time web scraping solution. It works by you giving us a URL. Once the data is ready, Real-Time Crawler provides you with a URL so you can download the results in HTML or JSON format.

What is Web Scraper? It is a data-gathering tool that allows you to scrape nearly any target. This automated tool will enable you to gather data in an automated way. You simply provide us a URL and receive back the data in HTML format.

The whole process of Real-Time Crawler and Web Scraper is simply a lot more resource-efficient. Making a choice between the two depends on what target sites you’re planning to scrape. If it’s an e-commerce site or a search engine – Real-Time Crawler is the way to go. If you need to scrape a bunch of smaller target sites, Web Scraper is the tool for you. However, for the best results and high success rates, using both interchangeably works best. 

Conclusion

The definitions of data scraping, data crawling, web scraping, and web crawling have become more transparent. To recap, crawling means going through data and clicking on it. 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 have any questions regarding data scraping, data collection tools, or proxy applications in the business world, contact our sales team at [email protected], they will be more than happy to answer any of your proxy related questions. 

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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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