What Is Web Scraping?

There are many terms being thrown around, web scraping, data mining, and harvesting, data compilation, and analysis – but what do they actually mean? And more importantly, how can you use what these terms represent to improve your business? Well, we’ll be diving into exactly that subject here.

We’ll also be explaining the basics of how python web scraping works and touch upon some of the other available methods. You’ll also be able to find out why a lot of companies have been resorting to data scraping to improve the way they operate.

Do you know what web scraping is?

There’s a whole universe of data out there that needs to be explored and sorted into neatly organized sections, and that’s where web scraping enters the scene. It is used to gather and compile any data that might be useful or beneficial to you or your business.

To go a bit more into detail of what web scraping is, it can essentially be broken down into a simple concept: pulling data regarding a certain subject from the web and compiling it into a database or spreadsheet, so it’s easily accessible for analysis. Now, this doesn’t sound all that complicated, but the processes behind it certainly are.

Mechanisms of web scraping

There are basically two ways you can go about web scraping that are vastly different even though they serve the same purpose. The two mechanisms that can be utilized are automated and manual web scraping, and even though the names are pretty self-explanatory, we’ll elaborate on the basics of both.

Automated web scraping

As the name suggests, this web scraping method is almost completely automated through the use of programs and applications that do most of the work. Even though they now have pretty user-friendly interfaces, there’s still a need for somebody to enter the search parameters for the type of data that is to be collected. Python web scraping falls into this category and is one of the most commonly used web scraping methods out there. If you’re interested in trying to build a scraper, read this in-depth article on python web scraping.

Manual web scraping

Manual web scraping is basically the same thing, except it is done manually. Because the data is gathered by humans and not AI, the filtering is expectedly much better, as a human can discern if the piece of data in front of them is actually relevant to the data-gathering project he or she is managing. However, this process is much slower, and even though it gets good results, it requires a lot of human resources and time, which isn’t something every company can afford.

How companies can use web scraping

Businesses can use web scraping in a plethora of ways and aim to use the data for various goals. You could be using this approach to compile data on your competitors and companies working in a similar niche to your own and acquire data on what kind of marketing campaigns are getting results right now. It doesn’t stop there, as data can be practically anything on the web, meaning you could theoretically gather text, photos, and even videos about the subject that your business can benefit from.

In-house vs ready-to-use scraping

Once again, there are two ways you could go about data scraping in your company: in-house and ready-to-use (also known as outsourced). In-house web scraping can be excellent because you can finely tune it and relay information to the person in charge of it quickly. However, outsourcing this entire process might actually be more efficient.

A company whose only purpose is to bring data to you, the customer, will work on doing that more consistently and reliably. Also, you won’t have to either hire or train somebody to gain skilled people familiar with data science because the company already has those individuals, and they are ready to get you the data you need. There is also a good chance that a company that’s solely focused on web scraping and data crawling will have better infrastructure than you already do, making the results cleaner and faster.


Hopefully, that was enough for you to get the basics of what web scraping is and how businesses can benefit by using it. Suppose you aren’t already considering implementing it into your operation. In that case, you definitely should, as the results will improve your overall efficiency and presence in the field that your business wants to conquer.

Although it can seem like a non-return investment at the time, think about the long run and how much data you could theoretically gather in even just a year. The amount is almost unimaginable. You can use and analyze that data however you like and work towards bringing your business a step farther on the road to success.