web scraping

What Is Web Scraping? Best Guide To Extracting Data From The Web

Wult

What is web scraping

Data is one of the most important assets for a modern business. Collecting data, analyzing it, and cleaning it is a powerful way of improving a variety of business functions.

But where does data come from? There are many sources, some public, some private. These datasets sometimes cost money, and sometimes they are traded.

When companies face a problem, they often look for data to solve that problem. We live in a world where information is everywhere, but it’s more prevalent than anywhere on the web.

It is estimated that the total data on the web if combined and mapped, would total one zettabyte. It’s okay if you had to look that up – it’s a monumentally huge number that is difficult to comprehend.

The crucial thing to understand about this data is that it’s mainly public. Anyone with a browser can access it. This is the basis of web scraping. Turning information available on the web into datasets.

 

Why scrape the web

So much information exists on the web that the use cases are potentially limitless with web scraping. Most data types can be extracted from the web, and this can be an excellent asset for businesses to function effectively, from leaden to insights and understanding.

Think of a type of data, and you can probably get it from the web. From email addresses, venue addresses, song lyrics, and categories of fish – the list goes on and on.

All of this information is readily available. Collecting it, structuring it, and analyzing it can have hugely positive effects on a wide range of businesses. We will explore these in more detail before looking at how web scraping works in practice.

 

How does web scraping work?

To understand how web scraping works, we need to understand how web browsers work and understand websites.

When you go to a URL in your browser will send a request to a server, which will then send back a response. This response contains the HTML, CSS, JSON, and JavaScript that the browser will then use to form a visual web page.

The scraper gets this request and based on a set of predefined conditions, and it extracts the relevant data. This is then converted to the correct format.

There are two main ways of scraping the web – we’ll look at this in more detail below.

 

Scraping with python

One way of scraping the web is to use python and build your own scraper to extract the data that you need from the web. However, even for people that are experienced with python can find more complex data extraction tricky, and starting from scratch is an extremely steep learning curve.

However, getting started requires you to install python and a few other tools, and you can get started with just a few lines of code (this will be very basic at first).

Here’s an example:

from bs4 import BeautifulSoup
import requests

url = "<http://www.athleticvolume.com/programming/>"

content = requests.get(url)
soup = BeautifulSoup(content.text)

print(soup)

Here’s what is happening – we’re requesting a URL, and once we receive the response, we put it into an object. This is the same as if we manually went to the site and viewed the page source.

From here, the possibilities are endless, and the more that you practice and run scrapes, the better you will be at getting the information you need. However, there is another way.

 

Using a prebuilt tool to extract data from the web

Another option, instead of building a web scraper from scratch is to use a tool that can adapt to your needs and extract the data you need. Here we’d like to talk about Wult.

Wult has two main components – an extractor (scraper) and a data management solution.

The first part is a powered-up version of what we have already seen. It can extract data from the web, structure the data, and output the data that you need for processing.

It has a few other benefits over a basic web scraper:

  • It can view the web as a human does, rather than just the raw code. This means that it can extract data from JavaScript pages where the data would not be in the source code.
  • It can adapt to changing websites. Wult learns which element you are looking to extract, and it makes smart decisions where it thinks it can see the same data in another place. This means you don’t miss out on relevant data.
  • It can be set up to check for updates. With a basic web scraper, you would have to run the scrape again and then check for changes, and modify your original database.
  • All of this can be set up in a tidy interface, and you don’t need to have any experience with python or coding to make it work.

The second part is the data stream. Think of this as more of a data analytics tool that filters, modifies, and combines the data into a form that works for you. It can then plug this data directly into your current set up. This is where the powerful automation happens, and again, this is all possible without coding experience, and without having to read through all your API integration docs.

 

Use cases for web scraping

Now that you have seen two ways of scraping and extracting data from the web let’s look at what you can do.

Better access to company data

Many sites around the world provide information about businesses and organizations. Collecting and combining these datasets into a single database is a powerful tool.

A natural scrape flow would be to scrape a directory of companies and extract key information about the business, such as the web URL. From here, you can build a smarter data extractor that can use this URL to find public records of the company in other areas of the web, such as social profiles, investor profiles, etc.

Very quickly, you can build a very detailed database that includes more detailed information such as the number of employees, category, markets active, and even revenue.

This is a dream for any sales team to work from. They have a unified database of extensive structured information on every business.

Wult can help businesses to attain this kind of database without any prior coding experience. Wult’s data stream allows businesses to automatically integrate this data into their current setup and even automate outreach.

 

Better sales data and lead generation/prospecting

The above dataset naturally runs into this one. With company data, you can filter out the relevant companies for your business and then build a robust, automated sales machine.

Who wants to manually find prospects and then search countless sites for contact details when you can automate the whole process.

You can build an incredibly detailed scrape that can even filter out leads and qualify them. From here, plug into your outreach solution, and you have a fully automated lead-gen machine.

 

Marketing automation

Web scraping is an incredibly powerful marketing tool that can help to grow your organic channels and build engaged audiences for your business. Web scraping forms an effective part of a B2B marketing strategy.

Here is a web scrape/data extraction and data analysis/action flow that can yield incredible results for marketers and illustrates the true power of web scraping.

Step one – identify competitors with a strong social following that offer the same service/product as you (of course yours is better, but what do social media users know).

Step two – use a smart web scraper to extract the profiles of their followers

Step three – create a flow that follows them and messages them with information about your products

This is just one way that web scraping can help marketers. But it doesn’t just have to be on social channels.

Web scraping can be hugely useful for SEOs looking to find new opportunities and automate a tonne of processes so they can focus on growing their search presence.

 

Brand monitoring

Brand monitoring is becoming a huge part of any business. In the world of e-commerce and retail, routinely checking product reviews and customer feedback is a must.

Brands often miss out on this, as it can be a lengthy process when done manually. Web scraping and data analysis can help to monitor multiple platforms. They can even consider social reviews to build an incredibly powerful business intelligence tool only from public-facing data on the web.

 

Market analysis, big data, and insights

People think that big data is complicated and unattainable for the average business. But it’s not. With a simple web scrape, you can begin to extract powerful data than can help you to analyze the competition and identify new market opportunities.

Scraping competitor prices can give you a substantial competitive advantage. Understanding the growth of new products can also help you buck trends and get there first before the competition.

This can also help you get quick overviews of new areas if you are looking at moving into new, competitive markets. It can also help with financial predictions and stock analysis.

All this is possible from a simple web scrape.

 

Conclusion

Web scraping is a powerful and often untapped tool for businesses that want to be able to speed up complex tasks and processes and automate their business. Extensive information exists on the web. You need to know how to find it.

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