The world of data collection is undergoing a huge change. Web scraping and web crawling are often used interchangeably. They are both used for data mining, right?
Yes, but they are not the same thing. Web scraping does not always require the use of the internet. Extracting information from a database, local system or using data scraping tools can be referred to as data collection.
In the interim, web crawlers are primarily instructed to copy all accessed sites for later processing by search engines, which will index the saved pages and search for the unindexed pages quickly.
In this article, we will look through the key differences between web scraping and web crawling and help you decide which is relevant to you and your business.
What is Web Scraping?
Web scraping is the automated process of collecting structured information from the internet. This process is also known as data extraction, and it covers a wide array of techniques and uses cases involving the modus operandi of Big Data.
On a most basic level, web scraping refers to the process of copying data from a website. Then, users can import the scraped data into a spreadsheet or a database or utilize software to perform additional processing.
Who benefits from web scraping? Anyone in need of any information concerning any particular subject. If you want to research any topic or subject, the first thing you would likely do is to manually copy and paste data from sources to your local database.
Today, thanks to automation tools, anyone can easily use web scraping techniques. What used to take many weeks to complete can now be done in hours with complete accuracy.
One can save lots of time changing from manual to automated scraping. It also provides an economic advantage to individuals or teams. The data collected by web scrapers can later be exported to CSV, JSON, HTML, or XML format.
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What is Web Crawling?
We all know and use Bing, Google, Yahoo or other search engines. Using them is very simple — you ask them for anything, and they search the web to provide you with an answer. Search engines such as Google use web crawlers to scan and search the internet for pages matching the keywords you input and also index the pages for easy remembrance the next time you search the same keyword.
Crawlers also help search engines in gathering website data: URLs, meta tags, hyperlinks, and written content, and the inspection of the HTML text.
You do not have to worry about the bots getting stuck in an endless loop of visiting the same websites because they keep track of what they already accessed. Also, their behavior is determined by many criterias such as:
- re-visit policy
- selection policy
- deduplication policy
- courtesy policy
Web crawlers encounter many obstacles, including the ever-changing and vast public internet and content selection. Umpteen pieces of information are posted daily. As a result, they would have to sift through millions of pages and keep refreshing their indexes to get accurate results. However, web crawlers are vital parts of the systems that examine website content.
Web Scraping vs. Web Crawling
Web scraping is frequently confused with web crawling. Web scraping is quite different from web crawling in that it extracts and duplicates information from any page it accesses, while web crawling navigates and reads web pages for indexing. Crawling checks for pages and content, and scraping ensures the data gets to you.
It is a misunderstanding that web scraping and crawling work simultaneously, this is not the case. Web scraping is a technique one can use to extract data from web pages.
Whether they are crawled pages, all pages behind a particular site, or pages in digital archives, while web crawling can generate an URL list for the scraper to collect. For example, when a business wants to gather information from a website, it will crawl the web pages and then scrape the pages that hold valuable data.
Combining web scraping and web crawling leads to more automation and less hassle. You may produce a link list through crawling and send it to the scraper, so it knows what to extract. The benefit is collecting data from anywhere on the internet without human labor.
Use Cases
Web scraping and web crawling make an extremely good combination to quickly collect and process data that a human would not be able to analyze in the same timeframe. Here are some instances where these two can help your business:
Brand Protection
You can make use of tools to quickly find harmful online content to your brand (like trademark infringement, patent theft, or counterfeiting) and take record of them so you can take legal action against the responsible parties.
Brand Monitoring
The process of brand monitoring is a lot simpler and easier when using a web crawler. The crawler can discover mentions of your company in the online environment and categorize them so that they are easier to understand, such as news articles or social media posts. Use web scraping to complete the process and you have access to valuable information.
Price Control
Companies use scraping to extract product data, analyze how it affects their sales model, and develop the best marketing and sales strategy. On the other hand, crawlers can also look for new product pages with valuable info.
Email Marketing
Web scraping can gather websites, forums, and comment sections at breakneck rates and extract all the email addresses you need for your next campaign. Email crawling can also look through chat groups and forums, checking for emails that are hidden but can be found in the headers.
Lead Generation
Special offers and advertisements are useless if they do not reach the right people. Businesses use scrapers and crawlers to find those people, whether it is on business registries or social media. The bots can find and gather contact information that will then be sent to the marketing or sales team.
Conclusion
Now that you know the difference between web crawling and web scraping, you must choose which of them is most effective for your specific use case. You need to determine if your available budget and in-house staff can be able to manage your data collection process or if you would rather outsource this to a data collection network.
