Web Scraping: What It Is and How to Use It

Web Scraping: What It Is and How to Use It
Last edit: Jul 12, 2024

Are you tired of manually extracting data from websites? Do you want to save time and effort while gathering valuable information? Look no further than web scraping! This powerful technique uses automated scripts, or web crawlers, to extract specific data from websites quickly and accurately.

This article will explore the ins and outs of web scraping - including its benefits, techniques, tools, use cases, and legal considerations. Whether you're a seasoned developer or new to data science/marketing/finance/investment/etc., this guide is for you. So let's dive in and discover how web scraping can revolutionize your work processes!

What is Web Scraping?

Web scraping is a technique used to extract data from websites using automated scripts, also known as web crawlers or spiders. It involves downloading the HTML code of a website and parsing it to extract specific information such as text, images, links, etc. The extracted data can then be stored in a database for further analysis or manipulation. Individuals and entire companies use web scraping to make smarter decisions.

The main benefit that comes with using web scraping is its ability to process large volumes of data quickly and accurately by automating the entire process with minimal human intervention required on your end. Additionally, it also allows you access to vast amounts of publicly available information, which may be difficult or expensive for you to obtain via other means, such as purchasing datasets.

Furthermore, since most website owners are not aware of their websites being scraped, there are no legal issues related to extracting publically available data from various sites across the internet, provided they follow all applicable laws in their country/region regarding privacy policies & terms & conditions, etc.

Web scraping techniques

If you need to extract data from a website, the two most common techniques are manual and automatic web scraping.

  • Manual web scraping involves manually inspecting the HTML code of a website for specific elements that can be extracted.
  • Automatic web scraping requires specialized software which will automatically navigate through websites and collect information as it goes along.

Both methods have their advantages and disadvantages depending on the type of project being undertaken.

Manual Web Scraping vs. Automated Web Scraping
Manual Web Scraping vs. Automated Web Scraping

Manual Web Scraping

Manual web scraping involves manually copying text or other content from a website page instead of using an automated program to do it for you. This is the easiest method of web scraping, which allows users to choose which specific elements they want to scrape from each page visited. For example, if you only need to find a few phone numbers or addresses, manual data extraction is a good way to do it.

This type of extraction requires no programming knowledge, but it is the slowest and most time-consuming method of web scraping with the risk of human error. And human error can cost you a lot.

Automated Web Scraping

Automated web scraping uses software programs specifically designed to extract data from websites without any human intervention required after setup. These programs will go out onto targeted pages within a given website or multiple sites if desired and “scrape” all relevant information found there before aggregating it into one convenient output file containing exactly what was requested in its most usable form (e.g., Google Sheets, JSON, XLSX, CSV, XML, etc.). An advantage here over the manual methods mentioned above is that automation removes potential user mistakes and makes processes much faster - saving lots of time!

The Basics of Web Data Extraction

Also, you may have encountered not only the words web scraping but also web crawling, data mining, and screen scraping. An unfamiliar person might think that these are the same thing. But here we're going to explain to you how they differ from each other.

Technique Definition Main Purpose Key Features Output
Web Scraping Extracting data from websites using code or software Extracting specific data points from websites Can extract structured and unstructured data Structured data in various formats such as CSV, JSON, or Excel
Screen Scraping Extracting data from a visual display output Extracting data from legacy systems or non-web applications Extracts data from visual display, can handle various file formats Data extracted from GUI
Web Crawling Automated process of gathering web data by following links Indexing and gathering data from multiple websites Can crawl millions of web pages, can be used for search engines Unstructured data such as HTML or XML
Data Mining Process of analyzing large datasets to extract insights and knowledge Analyzing data to identify patterns and relationships Can work with structured and unstructured data, can handle complex algorithms Insights and knowledge extracted from large datasets

Web Scraping vs. Data Mining

The main difference between web scraping and data mining is their purpose: while web scrapers collect specific types of unstructured content from websites for further processing, data miners focus on discovering hidden patterns in already-existing datasets with various tools like natural language processing (NLP), machine learning (ML), artificial intelligence (AI), etc. Additionally, because both processes require different skill sets - coding for web scraping and data analysis/statistics for data mining - the two tasks are often handled by different professionals.

Web Scraping vs. Web Crawling

If you're not a technical person, the words "web crawling" and "web scraping" might sound like they mean the same thing. In reality, they are two very different processes that are often confused with one another.

Web crawlers, also known as "spiders" or "bots", are automated computer programs that use artificial intelligence algorithms to discover and gather information on the World Wide Web automatically. A crawler typically starts with a list of URLs to visit, called the seed set. As the crawler visits these websites, it discovers links to other websites and adds them to its queue. The crawler continues to crawl until it has visited all the websites in its queue or until it reaches a pre-determined stop condition.

web crawling vs. web scraping
Web crawling vs. web scraping

Unlike web crawlers, which automatically follow links to find all of the content on a website, web scrapers extract only the specific data that they are programmed to look for.

Both web crawling and web scraping can be used to collect data from websites. When deciding which tool is best to use in your case, it's important to consider the type of data you need and the source of that data. If you need large amounts of data from multiple sources, a web crawler will likely be your best option. However, if you only need data from a few specific sources, a web scraper will probably suffice.

Web Scraping vs. Screen Scraping

Web scraping and screen scraping are two terms that are often used interchangeably; however, they do have slightly different meanings.

Screen Scraping is a technique focused on extracting visual UI elements like text fields or dropdowns from desktop applications – instead of collecting raw HTML code of a website – then transforming them into machine-readable formats like CSV files. This method was initially developed to convert legacy systems into modern ones by pulling out their user interfaces layer by layer before migrating them over to a new system platform with no disruption in service delivery or downtime at all costs.

Types of Web Scraping Tools

When it comes to selecting a web scraping tool, there is no one-size-fits-all solution; each project requires different features depending upon its complexity and scope, so you should always keep this in mind when choosing the right tool for your needs. The most common types include:

  • Browser Extensions
  • Installable Software
  • Web Scraping API
  • Cloud-Based Scrapers
  • Self-Built Scrapers
  • Robotic Process Automation (RPA)
Tool Type Advantages Limitations Best Use Case Ease of Use
Browser Extensions Easy to use, integrated directly into the web browser Limited in features, cannot run advanced features Small data collection ⭐️⭐️⭐️
Installable Software Advanced features like rotating IP addresses, simultaneous data collection, and scheduling Requires installation and configuration, may be more complex to use Data extraction from multiple pages ⭐️⭐️
Web Scraping API Accurate data extraction, advanced features like JavaScript rendering and CAPTCHA avoidance May require technical expertise to implement and use Advanced data extraction ⭐️⭐️
Cloud-Based Scrapers Scalability, no hardware requirements, can collect data at regular intervals without manual input Requires cloud computing services, may have additional costs Large-scale data collection ⭐️⭐️
Self-Built Scrapers Customizable, no reliance on third-party services, more efficient in terms of time and cost investment Requires technical expertise to build and maintain Custom data extraction ⭐️
Robotic Process Automation
Can automate complex tasks, scalable, and can handle multiple sources simultaneously Requires development and setup time, may not work with all websites Automating complex web scraping tasks ⭐️⭐️

Browser Extensions

These web scrapers are extensions plugged into your browser, such as Google Chrome or Firefox, to collect any web page you visit automatically. The advantage is that they are easy to use and integrated directly into the web browser and are good for those who want to collect small amounts of data. However, they do have limitations in their operation. For example, any advanced features that go beyond your browser cannot be run on browser-based web scrapers extensions.

Installable Software

Web scrapers as installed software, unlike browser extensions, have many additional features, such as rotating the IP address for more efficient data collection, gathering information from multiple web pages simultaneously, running in the background separately from the browser, displaying data in different formats, searching the database, scheduling scraping sessions, and many other functions.

Web Scraping API

A Web Scraping API is an automated tool that allows the software to extract data from websites and integrate it into another piece of software through an API call. This type of tool often involves advanced techniques such as rotating IP addresses, JavaScript rendering using a headless browser for capturing dynamic content, CAPTCHA avoidance, and avoidance blocking anti-scrapers. All these features guarantee accurate extraction while avoiding being blocked by anti-scrapping measures set up by website owners.

Read more: Web Scraping vs API: What's the Best Way to Extract Data?

Cloud-Based Scrapers

Cloud-based scrapers utilize cloud computing services like Amazon Web Services (AWS) or Microsoft Azure to run automated scripts that gather data from websites at regular intervals without needing additional manual input from the user aside from configuring the scraper itself initially when setting it up. This type of solution offers scalability since there’s no limit on how much data can be collected at once – plus, it eliminates hardware requirements, so users don’t have to worry about storage space being filled up over time due to excessive usage/scraping activity taking place within one session/period of time).

Self-Built Scrapers

For those with technical knowledge, building their own custom scraper using programming languages like Python or JavaScript is often the most efficient solution in terms of time and cost investment. Self-built scrapers require a bit more effort upfront, but they allow you to customize the results according to your specific needs without relying on third parties services. Popular Python libraries used to create homemade scrapers are Beautiful Soup, Scrapy, Selenium, urllib.request, and lxml. For JavaScript, these are Cheerio, Axios, Puppeteer, NightmareJS, and Request-Promise. These libraries make writing code easier by allowing developers to parse HTML documents faster than if they were writing code from scratch in raw language form alone.

If you are looking to learn more about web scraping using Python and NodeJS, our tutorials can help.

Robotic Process Automation (RPA)

RPA involves using bots or robotic processes which mimic human interactions with websites by automating complex tasks based on predefined rules. RPA bots can extract data from webpages, process and analyze it, and then store the results in a database or other system for further use. These tools have become increasingly popular because they offer low entry barriers, faster development cycles, robust performance scalability, reliability, security compliance, and the ability to handle multiple sources simultaneously.

Read more about Amazon Product Data Scraper

How Do Web Scrapers Work?

The goal of a web scraper is to understand the website's structure in order to extract all the data you need. The effectiveness of your data scraping will depend mostly on clearly defining what elements you want to extract and being able to handle errors.

  1. Making HTTP request to obtain the HTML page content from a target URL;
  2. Parsing the HTML code to extract desired content into a structured format, such as CSV or JSON;
  3. Storing and displaying extracted data in a way that is useful for you.

First, the web scraper gets a specific URL (or several) from which to scrape data. Then the scraper loads the HTML code of the corresponding page. More advanced scrapers process requests, execute JavaScript, load external resources, and apply CSS styles. Once the web page has been loaded and analyzed, the scraper will use software methods to detect and extract either absolutely all data from the page or according to predetermined criteria.

In the end, the web scraper outputs all of the collected data in a structured format – JSON, CSV, XML, or Excel spreadsheets.

Flowchart describing the process of web scraping
Flowchart describing the process of web scraping

What is Web Scraping Used for?

Web scraping is a powerful tool with numerous use cases. Depending on the type of data you need and the nature of your project, web scraping can be used in countless ways to gather information from websites and other online sources.

Data science professionals might employ web scrapers to collect large datasets for machine learning or statistical analysis. Web developers may want to pull content from third-party sites for display on their own pages, while marketers could use it to extract competitor pricing data for comparison purposes.

No matter what industry you’re working in, chances are there’s an application for web scraping that will help streamline processes and make life easier.

Let’s take a look at some of the most common use cases for web scraping:

Market Research

When it comes to market research, web scraping can be used to gather information about competitors' products, pricing strategies, reviews, or any other relevant content that can help you better understand your sector. It also helps gather intelligence on potential customers by extracting emails or phone numbers for further contact purposes. By automating the process of collecting data from multiple sources at once, this technology makes it much easier for companies to get up-to-date insights into their industry and make informed decisions about their strategy.

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Lead Generation

Businesses also widely use web scrapers as part of their lead-generation process. By automatically collecting contact information such as email addresses or phone numbers from different websites, companies can create lists of potential leads that they can target with marketing campaigns or sales efforts more effectively than before. This increases efficiency while decreasing costs associated with lead acquisition since no human resources need to be employed for it all to work properly.

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Price Intelligence

Web scraping allows you to collect product descriptions and pricing data from around the web to make better e-commerce decisions. That way, you can react quickly to general price changes and optimize your own. For example, to outperform competitors in emerging markets while lowering prices elsewhere. You can monitor shopping trends, analyze competitors' marketing strategies, and comply with MAP and other price regulations.

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Finance & Investment

Financial and investment firms use data to make investment decisions. Web scraping helps you analyze current financial market conditions, track emerging trends and analyze their impact, and monitor news affecting stocks and the economy. With scraping, you can analyze company documents and monitor public sentiment about industries.

Real Estate & Property

Using web scrapers, real estate agents and brokers can easily collect detailed listings from multiple websites in just a few minutes. This allows them to keep up with the ever-changing market and stay informed on housing trends without spending hours searching each website individually. Additionally, it ensures that all relevant real estate listings are collected accurately and efficiently, which makes it easier for agents/brokers to make important decisions about their investments or portfolios more quickly than before.

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Current News & Content

With web scraping, you can track current trends related to global and regional affairs or news articles in order to react to them in a timely manner. You can analyze public reactions to trends, make investment or purchase decisions, monitor competitors, and conduct targeted campaigns, such as political ones.

SEO Monitoring

Web scraping can be used to monitor website rankings on search engine result pages (SERPs). This allows businesses to track their progress in organic search results and optimize their content accordingly. Additionally, web scrapers can be used to scan SERPs for competitor sites, allowing businesses to stay informed about their competition's activities. With our Google SERP API companies can easily streamline this process without spending time on developing custom crawlers or worrying about rate limits and other issues associated with manual crawling processes.

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Machine Learning

Web scraping can collect data on people's behavior and Internet communication patterns to later use the information for machine learning projects, training predictive models, and optimizing NLP models.

Consumer Sentiment Analysis

Social media scraping is full of diverse opinions about products and social issues, allowing you to track consumer sentiment and understand the values and desires of the audience you're advertising to and providing your product to. The data collected is useful both in the development of new projects and in the improvement of existing ones.

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Brand Monitoring

A strong brand sets your product apart from the competition and inspires consumer confidence. Analyzing brand mentions provides insight into how you are currently perceived and how you can adjust your customer service and marketing strategies to improve your reputation and awareness.

Web scraping is ubiquitous among both small and large businesses and is already part of many companies’ models. Nevertheless, the legality associated with it is extremely complex. Web scraping is generally not illegal anywhere in the world, but problems arise when people do not respect intellectual property rights and collect personal data and copyrighted material. When you collect information, you need to make sure that your activities are conducted within the law.

Read more: Legal and Ethical Aspects of Web Scraping

Conclusion and Takeaways

In conclusion, web scraping is a powerful technique that can help you extract valuable data from websites quickly and accurately. It offers numerous benefits across various industries, including market research, lead generation, price intelligence, finance and investment analysis, real estate analysis, and monitoring social media for consumer sentiment.

However, despite its benefits, it's important to remember that there are legal considerations when using this technology. Always ensure your activities comply with privacy policies and terms & conditions set out by website owners.

Overall, if used correctly, web scraping can bring significant value to any business process by enabling better decision-making based on accurate insights derived from relevant datasets harvested through automated processes.

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Sergey Ermakovich
Sergey Ermakovich
Sergey Ermakovich’s profile

I am a seasoned marketer with a passion for digital innovation. My expertise lies in creating innovative solutions to present data-driven insights, and I have extensive experience in the web scraping and data analysis industry.