Web Scraping vs Web Crawling: What You Should Know
Web scraping is somewhat complicated — from the differing definitions to the potential applications in business, as well as the power it has to shape the future of business. And of course, there is another commonly heard term — web crawling. You may have heard these terms used interchangeably, so it’s important to understand the differences between web scraping vs. web crawling. Here’s a quick rundown before we get more in-depth:
Web crawling gathers pages in order to create indices or collections. Web scraping downloads pages in order to extract specific data for analysis purposes.
In this article, we’ll go over both step by step, so let’s get started.
It might sound the same, however, there are some key differences between scraping vs. crawling. Nevertheless, these two terms are closely intertwined. Both scraping and crawling go hand in hand in the whole process of data gathering, so usually, when one is done, the other follows.
What is data scraping?
Data scraping is when you take any publicly available data, whether it is on the web or your computer, and store it into a file. It is important to note that data scraping does not require being connected to the internet.
What is web scraping?
Web scraping is when you take any online publicly available data and import the found information into a file. The main difference here in regards to data scraping is that web scraping, rather obviously, requires one to be online.
These definitions also work for crawling. If it has the word web in it — it involves the internet. If it consists of the word data — it does not necessarily need to include the internet in the crawling actions.
What is crawling?
Web crawling (or data crawling) is used for data extraction and refers to collecting data from either the world wide web, or in data crawling cases — any document or file. Traditionally, this process is done in large quantities but is not limited to small workloads. Therefore, it’s usually performed with a crawler agent.
According to our Python developer Bernardas Alisauskas, a crawler is “a program that connects web pages and downloads their contents.”
He explains that a crawler program simply goes online to look for two things:
- Data the user is searching for
- More targets to crawl
So if we tried to crawl a real website, the process would be similar to this:
- The crawler goes to a predefined target — http://example.com
- It discovers the product pages
- It then finds the product data (price, title, description, etc.)
The product data found by a crawler will then be downloaded — this is the part where it becomes web/data scraping.
Going further, you’ll see us using these terminologies interchangeably to keep in sync with the examples and outside studies. Just keep in mind that in most of these instances, it will mean web scraping/crawling, rather than data scraping/crawling, with us turning a blind eye to their precise definitions.
Crawling vs scraping
The question arises: how is crawling different from scraping?
To generally understand the main scraping vs. crawling differences, you need to know that crawling means going through and clicking on different targets automatically, while scraping is the part where you take the found data and download it into your system. Data scraping occurs when you know what you want to take and then take it. For example, in web crawling/scraping cases, usually what can be scraped are product data, prices, titles, descriptions, etc.
It’s important to understand the main web crawling vs. web scraping differences, but also, in most cases, crawling goes hand in hand with scraping. When web crawling, you download readily available information online. Crawling is used for data extraction from search engines and e-commerce websites, and afterward, you filter out unnecessary information and pick only the one you require by scraping it.
However, web scraping can be done manually and without the help of a crawler (especially if you need to gather a small amount of data). In contrast, a web crawler is usually accompanied by scraping to filter out the unnecessary information.
So, scraping vs. crawling (or web scraping vs. web crawling) — let’s sort out all of the significant differences between these two to see a clearer picture of both:
- Web scraping — only “scrapes” the data (takes the selected data and downloads it).
- Web crawling — only “crawls” the data (goes through the selected targets).
- Web scraping — can be done manually by hand.
- Web crawling — can be done only with a crawling agent (a spider bot).
- Web scraping — deduplication is not always necessary as it can be done manually, hence in smaller scales.
- Web crawling — a lot of content online gets duplicated, and in order to not gather excess, duplicated information, a crawler will filter out such data.
Data scraping for business
Data scraping has become the ultimate tool for business development over the last decade. According to Mckinsey Global Institute, data-driven organizations are 23 times more likely to acquire customers. They are also six times more likely to retain customers and 19 times more likely to be profitable. Leveraging this data enables enterprises to make more informed decisions and improve customer experience.
As the internet and its usability expands, the number of data-driven companies only keep on growing. According to Forrester, the average growth of such businesses is around 30% each year. It is estimated that by 2021, they will overtake their less-informed industry competitors by $1.8 trillion annually.
Data-driven, and consequently, insight-driven businesses outperform their peers. By tracking consumer interaction and gaining an in-depth understanding of their behaviors, companies can improve their customer experience. This, likewise, impacts lifetime value and increases brand loyalty.
It’s evident that data scraping has an influence in almost any business area. As data increasingly becomes the primary source of competition, data acquisition becomes especially important. There are many business areas where data scraping has a strong influence on performance and how it helps make a business more insight-driven:
- Competitor analysis and pricing: for a reliable pricing strategy, web scraping could help you extract the pricing intel of your competitors. You can also track their further pricing tactics, discounts, and other data.
- Marketing and sales: data scraping can help you with conducting market research on your competitors, gathering additional leads, analyzing people’s interests, and monitoring consumer opinion by regularly extracting customer ratings from different platforms. For example, web scraping real estate data helps to remain competitive in the market. Also, automotive industry data supports the predictive analysis of the market.
- Product development: web scraping e-commerce websites can be done for product descriptions or to check your stock status across thousands of marketplaces and retailers’ sites.
- PR, brand, and risk management: with data scraping, you’ll be able to detect ad fraud, improve ad performance, and check advertisers’ landing pages, as well as monitor your brand mentions and take appropriate actions.
- Strategy development: for a strong strategy, you will need substantial facts. Data scraping allows you to carry out an analysis of the latest trends in the industry, allowing you to monitor SEO and the latest news.
Is web scraping legal?
There is no simple answer to the question “is web scraping legal?” as one must answer whether the scraping done does not breach any laws surrounding the said data.
General advices for the best web scraping practices
We advise you to seek legal consultation before engaging in scraping activities of any kind. With that being said, here are some practical basic tips that will help ensure compliance when web scraping:
1. Sometimes, websites provide an API for data collection. If it is possible, use it instead of scraping data on your own. Of course, using a provided API is not the same as web scraping.
2. It is essential to respect the Terms of Service (ToS) for each website.
3. Respect the rules of robots.txt. If you really need the data from a specific website, but ToS or robots.txt forbids any automatic data collection, you can try to ask permission from the site owner.
4. Do not use scraped data without making sure that this information is not copyrighted. If it is necessary to publish this data, you should ask for a written permission from the copyright holder.
The definitions of data scraping, data crawling, web scraping, and web crawling have become more transparent. To recap, the main web crawling vs. web scraping differences: crawling means going through data and clicking on it, and scraping means downloading the said data. As for the words web or data — if it has the word web in it, it involves the internet. If it consists of the word data, it does not necessarily need to include the internet in the crawling actions.
It is now clear that data scraping is essential to a business, whether it is for customer acquisition or business and revenue growth. The future of data scraping also looks busy — as the internet becomes the main starting point for businesses to collect intelligence, more and more publicly available data will be required to scrape in order to get business insights and stay above the competition.