You can find anything on the internet; information on the financial markets, research studies, books, product releases, and latest news, not forgetting the criminal underworld camped on the dark web.
Perhaps you want to go a step further than just finding the information you were looking for by summarizing it or converting it from its current state, online, to a format that you can readily access even without an internet connection. If you find yourself in such a situation, you can either copy-paste the data or use automated extraction tools. These two forms of data extraction are regarded as web scraping. So, what is web scraping?
It refers to the process of collecting data from (a) website(s). Upon gathering the data, it is converted into a more structured format that is easier to understand and even more useful to a user. Depending on the type of web scraping you use, the final format available is often a spreadsheet (.csv or an Excel worksheet) or API. The latter is common with python web scraping.
Types of Web Scraping
The two main types of web scraping include:
- Manual web scraping
- Automated web scraping
Manual web scraping
Manual web scraping involves copying text from a website to a document on your computer. From the sound of it, it is a slow process, and in reality, it is slow. It can only work if you intend to collect a few kilobytes of data from one or two websites.
However, if you are working with tens of websites and hundreds of webpages, manual web scraping is not viable. It is too inefficient and time-consuming. Furthermore, you need to hire extra pairs of hands to collect data, thereby ballooning the data extraction cost unnecessarily.
Automated web scraping
Automated web scraping tools come in two forms, i.e., ready-to-use applications and in-house applications. In-house automated web scraping tools require a level of programming or technical background for the extraction process to be successful. Examples of such tools include:
- XML Path Language (XPath)
- Google Sheets
- HTML Parsing
- Vertical Aggregation
- Document Object Model (DOM) Parsing
- Text Pattern Matching. This tool is a form of python web scraping.
If you’re interested in building your own web scraper, then check this insightful tutorial and find out more about what python web scraping is.
Uses of Web Scraping
Whether you choose ready-to-use or in-house web scraping tools, the benefits and uses are similar. Here’s a list of how you can use web scraping for you or your business’s operations.
- Review monitoring
- Price monitoring
- Lead generation
- Market research and analysis
- News monitoring
Review monitoring entails searching and extracting data on what social media users and consumers who’ve purchased your products are writing about your brand and products.
This involves collecting data on how competitors have priced their products to come up with better pricing strategies.
You can use web scraping tools to collect contact information from sites such as Craigslist, which you can subsequently use for lead generation.
Also Read: It is All About the Website Help!
Market research and analysis
With web scraping tools, you can collect data from multiple websites belonging to companies in the same industry or sector. Analyzing that information could yield insight into how the market is fairing, enabling you to introduce new products or enter a given market.
You can scour news websites to establish what columnists and journalists have written about your brand. This is crucial if you are to maintain a good brand image and reputation.
Web Scraping and Proxy Servers
Web scraping can significantly benefit your business. However, websites curtail web scraping by integrating anti-scraping tools. Fortunately, with proxy servers, you can solve one of the problems that these anti-scraping tools bring – IP blocking. In the same breath, it is also essential to choose the right type of proxy, namely a rotating proxy, for ultimate success.
Web scraping is a surefire way of gaining information about competitors, understanding the market, and obtaining information that aids in better decision making. However, you cannot use web scraping tools, e.g., python web scraping, in isolation. You have to deploy them alongside rotating proxy servers to bypass anti-scraping restrictions.