Web Crawler: What It Is, How It Works & Applications in 2023

Have you ever wondered how search engines such as Google and Bing collect all the data they present in their search results? It is because search engines index all the pages in their archives so that they can return the most relevant results based on queries. Web crawlers enable search engines to handle this process.

This article highlights important aspects of what a web crawler is, why web crawling is important, how it works, applications & examples.

A web crawler, also known as a web spider, robot, crawling agent or web scraper, is a program that can serve two functions:

Web crawling is the process of indexing data on web pages by using a program or automated script. These automated scripts or programs are known by multiple names, including web crawler, spider, spider bot, and often shortened to crawler.

Thanks to this flow, web crawlers can index every single page that is connected to others.

Figure 2: An example of a robot.txt file

Since web pages change regularly, it is also important to identify how frequently scrapers should crawl web pages. 

There is no rule regarding the frequency of website crawling. It depends on the frequency with which a website updates its content and its links. If you utilize a pay-as-you-go bot service, revisiting and crawling web pages daily may be costly and consume your crawl budget quickly. 

For example, search engine crawlers use several algorithms to decide factors such as how often an existing page should be re-crawled and how many pages on a site should be indexed.

Figure 3: The image shows a basic steps involved in the web crawling process.

Thanks to the digital revolution, the total amount of data on the web has increased. Global data generation is anticipated to increase to more than 180 zettabytes over the following two years, up until 2025. According to IDC, 80% of worldwide data will be unstructured by 2025. 

the same time period, interest in web scraping has outpaced the interest in web crawling. Possible reasons are: 

Web scraping is using web crawlers to scan and store all the content from a targeted webpage. In other words, web scraping is a specific use case of web crawling to create a targeted dataset, such as pulling all the finance news for investment analysis and searching for specific company names.

Traditionally, once a web crawler has crawled and indexed all of the elements of the web page, a web scraper extracted data from the indexed web page. However, these days scraping and crawling terms are used interchangeably with the difference that crawler tends to refer more to search engine crawlers. As companies other than search engines started using web data, the term web scraper started taking over the term web crawler.

Check out our guide web crawling vs. web scraping to learn more about the differences between them.

Web crawlers are classified into four categories based on how they operate.

 Figure 4: Illustration of the difference between a standard and focused web crawler

Web crawling is commonly used to index pages for search engines. This enables search engines to provide relevant results for queries. Web crawling is also used to describe web scraping, pulling structured data from web pages, and web scraping has numerous applications. It also impacts a website’s SEO (search engine optimization) by providing input to search engines like Google whether your content has relevant information to the query or if it is a direct copy of another content online.

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Bright Data’s Data Collector enables companies to set up and scale web crawling operations rapidly with a SaaS model.

To build your in-house web crawlers, you can use programming languages such as javascript, python, etc. For example, Googlebot is one of the most well-known examples of an in-house web crawler written in C++ and Python.

Depending on your web crawling requirements, you may also utilize open source web crawlers. Open source web crawlers enable users to customize the source code based on their specific purposes.

The architecture of a self-built crawler system comprises the following steps:

Figure 5: An explanation of how a URL frontier works.

If you do not have the technical knowledge or a technical team to develop your in-house web crawler, you can use pre-built (or commercial web crawlers) web crawlers.

Websites’ content is updated regularly. Dynamic web pages, for example, change their content based on the activities and behaviors of visitors. This means that the website’s source code does not remain the same after you crawl the website. To provide the most up-to-date information to the user, the web crawler must re-crawl those web pages more frequently.

Websites employ different techniques, such as crawler traps, to prevent web crawlers from accessing and crawling certain web pages. A crawler trap, or spider trap, causes a web crawler to make an infinite number of requests and become trapped in a vicious crawling circle. Websites may also unintentionally create crawler traps. In any case, when a crawler encounters a crawler trap, it enters something like an infinite loop that wastes the crawler’s resources.

Downloading a large number of irrelevant web pages, utilizing a distributed web crawler, or recrawling many web pages all result in a high rate of network capacity consumption.

Web crawler bots mostly crawl all duplicate content on the web; however, only one version of a page is indexed. Duplicate content makes it difficult for search engine bots to determine which version of duplicate content to index and rank. When Googlebot discovers a group of identical web pages in search result, it indexes and selects only one of these pages to display in response to a user’s search query.

Websites set a crawl rate to limit the number of requests made by web crawler bots. The crawl rate indicates how many requests a web crawler can make to your website in a given time interval (e.g., 100 requests per hour). It enables website owners to protect the bandwidth of their web servers and reduce server overload. A web crawler must adhere to the crawl limit of the target website.

A robots.txt file is a set of restrictions that informs web crawler bots of the accessible content on a website. Robots.txt instructs crawlers which pages on a website they may crawl and index to manage crawling traffic. You must check the website’s robots.txt file and follow the instructions contained within it.

Websites employ different anti-scraping techniques to manage crawler traffic and reduce web scraping activities. For instance, browser fingerprinting is a tracking technique used by websites to gather information about visitors, such as session duration or page views, etc. This method allows website owners to detect “non-human traffic” and block the bot’s IP address. To avoid detection, you can integrate rotating proxies, such as residential and backconnect proxies, into your web crawler.

See our guide top 7 web scraping best practices for more information on web scraping and crawling best practices.

All search engines need to have crawlers, some examples are:

To explore web scraping use cases for different industries, its benefits and challenges read our articles:

If you want to have more in-depth knowledge about web scraping, download our whitepaper:

For guidance to choose the right tool, check out data-driven list of web scrapers, and reach out to us:

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 55% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch like Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Comment *

Hi Cem,

I think there is a misunderstanding regarding the robots.txt role in the crawling context. The web bots can crawl any website when indexing is allowed without having the robots.txt somewhere on their top domain, subdomains and ports and so on. The role of a robots.txt is to keep control of the traffic from web bots so the website is not overloaded by requests.