You probably know about the numerous benefits of web scraping to advance in business. This research tool is all the rage right now for companies and organizations across all kinds of industries. Information is power, and there’s a lot of information on the world wide web. It’s estimated that, on average, the 4.66 billion global internet users generate 2.5 quintillion bytes of data every day through their preferred devices. The abundance of choice might seem a bit intimidating, but there’s got to be something useful for your business among all that information, right?
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Some sites are considerate enough to provide researchers with the data they need through their own API. However, that’s not the norm. That’s when you should jump on the web scraping bandwagon — if you haven’t already. There are many data extraction methods available. The one you choose will fully depend on your technological resources and business requirements.
Below you’ll find all the information you need to make an educated decision on which web scraping techniques are right for you. Feel free to use the table of contents to jump between sections.
Scraping Techniques To Know About in 2021
Are you extracting and organizing in the most effective way? Web scraping is meant to facilitate your research process so that you can focus on other essential business tasks. To make the most out of it, you must make sure you’re using the best web scraping techniques. Here are the most common methods most users rely on at an enterprise level.
1 . Manual scraping (copy-pasting)
This technique is probably the simplest available, but that’s not necessarily a good thing in some cases. All it takes is for you to copy web content and paste it onto your database. Although this might sound like an easy task, it can become repetitive, tedious, and time-consuming. However, manual web scraping is pretty noble and does have some perks — let’s not be unfair. It lets you bypass a website’s anti-bot defenses.
2 . HTML code review
This method will let you extract data from dynamic and static pages via HTTP requests and allow you to get more entries in a shorter period. To efficiently parse HTML, it typically requires using sockets and pre-made codes. It allows you to target linear or nested HTML pages to collect text and other resources.
3. DOM code review
Scrapers use Document Object Model parsers to see a webpage’s structure in more depth. This method is great for dynamic sites as it provides you with nodes containing the data you need. When using a DOM parser, you’ll need additional tools like XPath to scrape the sites you’re interested in. Furthermore, you can embed some browsers so that you can extract the entire page or just a few segments.
3. Text pattern matching
4. Vertical aggregation
Some companies with large-scale computing power build vertical aggregation platforms to target a specific set of companies or customers in a particular niche. You can run this type of platform on the cloud and create bots to keep tabs on the collected information and extract hight quality data with no human intervention.
5. Google Sheets scraping
The internet giant’s spreadsheet API is a widespread tool more and more web scrapers are taking advantage of. You can use its IMPORT XML (,) function to gather as much data as you need from diverse websites. This comes in particularly handy when you need to harvest specific patterns or data, but it might not be useful otherwise.
Best Practices To Implement Web Scraping Techniques
As we already established, data is a powerful tool to use in your favor when trying to improve your business operations or position your brand to gain a competitive edge. However, most websites are extremely wary of web scrapers and their activity online — and with good reason. Some malicious actors use these techniques to harm servers or steal sensitive information.
When attempting to extract data from the web, you may encounter some sites that have implemented anti-scraping mechanisms to keep hackers at bay. Following the tips below will make your web scraping exercise as successful as possible.
1. Be a courteous scraper
If the site you need to collect data from allows scraping to a certain extent, be polite. Avoid overwhelming their servers by keeping your scraping activities slow. A good rule of thumb is to space out your requests by 10 seconds or more. Extracting data at off-peak hours will ensure you’re not affecting user experience for others.
2. Keep it ethical
A problem many sites face is the presence of hackers with nefarious intentions trying to take advantage of the information they hold. It’s no wonder some of them have implemented CAPTCHA technology or honeypot traps to detect robots and stop them in their tracks. It’s not personal, they’re just protecting their data from fraudulent third parties.
When you conduct web scraping activity on any site, keep things ethical. Use the data you’ve extracted only for the purpose it’s intended and keep it between you and your team. If you scrape social media platforms, for example, stay away from sensitive information that could invade the users’ privacy or promote identity theft. Scraping tools can be unethical too, so make sure you use only trustworthy providers to source your bots and proxies.
3. Avoid copyright infringement
Something you need to keep clear in your mind when web scraping is that the data you collect isn’t yours. Just because you can extract it doesn’t mean you can use it at will. Make sure to always give credit where credit is due, and while you might find it tempting, try not to share more information than you should on social media and other platforms. If you absolutely need to, always link back to the site you scraped.
Common Data Analysis Techniques
Once you’ve successfully gathered the data you need using the methods and best practices described above, you’ll need to analyze it. This will help you figure out where to apply your freshly acquired knowledge to give your business a competitive advantage. Here are the most common data analysis methods available:
1. Descriptive Analysis
This method is widely used to assess a company’s Key Performance Indicators. It helps produce revenue reports or give a clear overview. Knowing this information will help you compare how other companies in your industry are doing and decide whether you need to step up your game in certain areas.
2. Diagnostic Analysis
To dive deeper into the results gathered from descriptive analysis, you’ll need to evaluate the reason behind them. Diagnostic analysis helps you find causes and outcomes of certain data types and allow you to connect them with particular behaviors and patterns.
3. Predictive Analysis
This method is perfect for risk assessment and sales forecasting, as it allows you to use data to understand what’s likely to happen in the industry and estimate future outcomes. It relies heavily on statistical modeling and high-quality data to make accurate predictions.
4. Prescriptive Analysis
This type of data analysis combines the insight from other methods to determine the best course of action to solve a problem or make a decision in business. It relies on state-of-the-art technology and data practices to optimize the decision-making process.
Picking the right scraping techniques for your particular business will significantly simplify your data gathering and analysis endeavors. This guide will arm you with the best and most common web scraping techniques for data science so that you can select what works best for you. Remember that the key to being successful at web scraping is to keep it ethical and use the right tools.
If you’re ready to step up your web scraping game, reach out to us! Our Scraping Robot API will take time off of your web scraping exercise by automating the process. We provide modules to help in the most common types of web scraping and take care of proxy management and rotation for you. All you’ll have to do is use a simple command, and you’ll have the data you need to succeed in no time.
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