What Is Web Scraping? How to Automate Web Data Collection

From research studies to product listings, the internet is a treasure trove of informative content and valuable data.

Scanning through the billions of websites to find accurate data can be a herculean effort. With data extraction software, you can now automate how you collect or extract data from the web. The process of using bots to extract data and content from websites is known as web scraping. You can also work with data extraction services providers with web scraping services capabilities for automating data scraping. 

Web scraping collects and converts unstructured data in hypertext markup language (HTML) format into structured data, which can either be in a spreadsheet or database. Then, you can manipulate or analyze the data for fueling business applications.

Want to learn more about web scraping and its implications for your business? Continue reading the rest of the article to explore techniques, tools, and legal considerations!

How does web scraping work?

To grasp web scraping, it’s important first to understand that web pages are built with text-based markup languages.

A markup language defines the structure of a website’s content. Since there are universal components and tags of mark-up languages, this makes it much easier for web scrapers to pull the information they need. Parsing through HTML is only one-half of web scraping. After that, the scraper then extracts the necessary data and stores it. Web scrapers are similar to application programming interfaces (APIs) which allow two applications to interact with one another to access data.

Check out the step-by-step process of how web scrapers function. 

• Step 1: Making an HTTP request. The first step involves a web scraper requesting access to a server that has the data.
• Step 2: Extracting and parsing website code. After receiving access, a scraper goes through the website’s extensible markup language (XML) or HTML to discover the content structure.
• Step 3: Parsing the code. Now, the scraper breaks down or parses the code to spot and extract pre-defined elements or objects, which may include texts, ratings, classes, tags, or even ids.
• Step 4: Storing the data locally. Finally, the web scraper locally stores the data after parsing the XML or HTML code. 

Too many HTTP requests from scrapers can crash a website, so websites have different rules for bots to follow. 

Web crawling vs. web scraping

Web crawling and web scraping are two techniques for collecting data from the Internet, but they serve different purposes and operate in distinct ways.

Web crawling involves systematically browsing the internet to index content from various websites. Web crawlers, also known as spiders or bots, are designed to navigate through links on web pages and gather data for search engines like Google, which then index the content to improve search results.

Web scraping, on the other hand, is the process of extracting specific information from websites. Unlike crawlers, which collect general data for indexing, scrapers target particular data, such as prices, reviews, or contact information. Web scraping tools are used to automate this extraction process, allowing users to gather and organize data for analysis or use in other applications.

Web scraping techniques

Below are some of the common web scraping techniques. 

• Human copy and paste involve copying specific data from the web and pasting it into a text file or spreadsheet manually.
• Web scraping with Python uses Python’s regular expression-matching abilities to extract information from web pages. Data science professionals and programmers also use programming languages like Ruby, Java, C++, and JavaScript for automated web scraping.
• Document object model (DOM) parsing embeds web browsers to scrape the dynamic content that client-side scripts generate.
• Semantic annotation recognition uses semantic markups or metadata to locate and extract data snippets.
• Computer vision-aided analysis extracts data from web pages with the help of machine learning and computer vision. 

Types of web scrapers

Depending on the ease of use and the tech behind them, web scrapers can be of five types. 

• Self-built web scrapers require advanced programming skills but can offer a lot more features.
• Pre-built web scrapers are customizable scrapers that you easily download and run.
• Browser extension web scrapers are browser-friendly scraper extensions and often offer limited features.
• Cloud web scrapers run on company-side, off-site cloud servers. These scrapers don’t use your computer resources, meaning you can focus on other jobs at the same time.
• Local web scrapers use local resources like your computer’s central processing unit (CPU) or random access memory (RAM) to extract data.

Why might a business use web scraping to collect data?

Below are a few examples of how different industries use web scraping. 

1. Email marketing

You may or may not be aware of it, but somewhere on the web, there’s a good chance your phone number or email address could be extracted. In web scraping, this is called contact extraction. Sales intelligence tools crawl the public web and scrape what they believe to be the correct email address and any available phone numbers. While the information may not be 100 percent accurate, it still makes cold email outreach more efficient.

2. Price comparison

If you’re a “low-price hawk”, you must have interacted with a price comparison tool at some point in the past. By price scraping e-commerce product or service websites, there are tools that are able to offer real-time price comparisons and fluctuations.  

3. Coupon and promo code extraction

Similar to price comparison tools, you can also scrape the web to extract coupons and promo codes. While the success of these tools varies (and companies get more clever with their promo offerings), it’s still worth seeing if you can save money before checking out.

4. SEO auditing

One of the more lucrative ways to apply web scraping is to use it for search engine optimization (SEO) auditing. Basically, search engines like Google and Microsoft Bing Web Search API have hundreds of guidelines when it comes to ranking search results for keywords – some carry more value than others.

SEO software scrapes the web, amongst other things, to analyze and compare content on search engines in terms of SEO strength. Marketers then use this insight and apply it to their day-to-day content strategies.

5. Social media sentiment analysis

More advanced uses of web scraping are actually able to monitor data feeds. Businesses use social listening tools to scrape and extract real-time data feeds from social media platforms like Twitter and Facebook. You can use this information to examine quantitative metrics like subscribers’ comments, mentions, retweets, etc., and also qualitative metrics like brand sentiment and topic affinity.

Web scraping limitations

Web scraping is not a perfect, by-the-books process. Here are some limitations you can face while scraping the web. 

• Longer learning curve. Although web scraping tools ease data collection from the web, you may need to invest time in learning how to use them to their fullest potential.
• Changing website layouts and structures. There are many subtleties and nuances when it comes to building a website. Web designers constantly update their sites for better user experience (UX). Even the smallest changes can mess up the data you collect.
• Complex websites need advanced scraping. You may need advanced skills to fetch data from websites with dynamic elements and infinite scrolling.
• Strict website terms and conditions. In addition to technical barriers, some websites have data and content usage guidelines that may prohibit web scraping; this is most often the case with sites that use proprietary algorithms. To protect their content, these sites may use encoding to make web scraping near-impossible.

Is web scraping legal?

Check out the website's "robots.txt" to know if they allow web scraping. You can easily locate this file by typing in “/robots.txt” at the end of the website URL. If you're looking to scrape the Amazon website, you can look at the www.amazon.com/robots.txt file. Now, look at the ‘allow’ and ‘disallow’ paths to understand what a website spider may or may not let you access from the page source for a scraping project.  

Web scraping tools

Data extraction platforms help you retrieve unstructured, poorly structured, and structured web data for data analysis or business intelligence needs. These tools work in tandem with data quality software and data preparation tools to help you organize and clean data. Businesses also use data extraction tools in conjunction with data integration platforms to gather different data types and sources in one place. 

Ready to discover new opportunities?

Once you scrape and gather data from the web, you need to analyze it for insights. These data insights help you discover new opportunities for business growth. Even though the data is accessible, the challenge lies in figuring out the proper way to analyze and apply it.

Dive into data analysis and unlock a variety of insights from the data you scrape.

This article was originally published in 2019. It has been updated with new information.