What is Web Scraping? A Beginner’s Guide

Imagine collecting web data without spending hours copying and pasting data to your spreadsheet. If you’re thinking, “I wish this were true!” you might want to try your hand at web scraping.
But what is web scraping?

While the internet overflows with vast quantities of data, accessing this in a structured and efficient way can be challenging. Web scraping provides a streamlined, automated method to extract this data from websites.

And with a web scraping tool, you can collect thousands (or even millions) of web pages on autopilot.
This guide will tell you everything you need to know about web scraping, exploring what it is, how it works, and why it has become a significant part of fields like data analytics, machine learning, and artificial intelligence.

Let’s get started.

What is Web Scraping, and What is it Used For?

Web scraping is extracting and converting data from web pages to usable information. You may have also heard of web scraping as data scraping, data extraction, and web data extraction.
So why should you scrape data, anyway?

Let’s say you’re a real estate agent. You need to know every house on the market in your area, so you head to Zillow for a list of homes.

Typically, you’d have to copy and paste every listing to an Excel spreadsheet, which can take hours. But if you use a web scraping tool, it will automate the process for you. Once you’ve collected the data, it can be downloaded as a CSV, JSON, or XML file.

You’ll never have to collect large chunks of data ever again manually!
So how else can you use web scraping?

Popular Use Cases of Web Scraping

Web Scraping can be used for extracting data for many different purposes. Some of these include:

1. Price monitoring
2. Location Intelligence
3. Real Estate Market Analysis
4. Marketing and lead generation
5. News Monitoring

Price Monitoring

If you’re in the eCommerce space, you might want to uplevel your product strategy with price monitoring. Web scrapers can collect prices, inventory levels, and reviews from retailers like:

• Amazon
• eBay
• Target
• eCommerce stores

You could use this data to compare your products with competitors and improve your online sales.

1. Achieving Competitive Pricing

Web scraping enables businesses to reduce prices in response to competition, thereby gaining customer attention. For instance, if a company sells beauty products and the data points out that competitors’ prices are higher, lowering prices can boost sales.

2. Capitalizing on Low Competition

During seasons of low competition for specific products, price monitoring can identify these opportunities. Recognizing this situation allows a company to increase its prices and maximize profits.

3. Understanding Customer Preferences

Price monitoring can also help understand customer preferences. If the demand for a product decreases consistently, it may indicate shifting consumer interests. With this knowledge, businesses can adapt and introduce these new products to their inventory.

4. Scheduling Timely Promotions

Running promotions at the wrong time can be detrimental, especially if competitors have recently reduced prices. With price monitoring, businesses can strategize their promotions based on market conditions. They can plan the timing, ensuring they offer competitive prices that attract customers.

5. Monitoring New Entrants in the Market

Online price monitoring can provide insights into new sellers entering the product category. Awareness of new sellers can help businesses adjust their strategies accordingly to maintain competitiveness. Web scraping can inform businesses of these new competitors, allowing them to adjust their pricing and marketing strategies effectively.

Location Data

Not sure where to start your new business? Web scrapers can collect location data from publicly available sources for industries like

• Restaurants
• Hotels
• Franchisees
• Retailers
• Warehouse management

When you interpret each data set and decide what factors affect each business, you can choose the best location.

Real Estate Market Analysis

Real estate is one of the most popular industries for web scraping. And it doesn’t stop at collecting a list of houses. You can also scrape:

• Foreclosures
• Estate agents
• Construction permits
• Recorded deeds

Use cases of real estate data include:

1. Strategic Real Estate Investing:

Investors can spot potential hotspots for lucrative investments using scraped real estate data for specific areas or zip codes, like average property prices, historical property values, and neighborhood details. Insights into market trends and future property price projections can help investors manage risks and boost the likelihood of substantial investment returns.

2. Informed Home Purchasing:

Buyers can use real estate data to compare the prices of similar properties in their preferred areas, comprehend value trends, and evaluate the proximity of amenities such as schools, retail areas, and parks. This invaluable information can support home buyers in making informed decisions that align with their financial capacities and lifestyle requirements.

3. Empowering Real Estate Professionals:

Real estate agents and brokers can utilize real estate data to understand a specific market segment fully. This includes comprehending average property pricing, buyer preferences, historical data on property sales, and more for a chosen location. With this data, agents can effectively pair their properties with potential buyers and set competitive prices for the properties they handle.

4. Guiding Property Developers and Builders:

For those developing new properties, real estate data can provide insights into the types of properties in demand within a particular area or zip code. By recognizing trends in housing demand, developers can make strategic decisions about what properties to construct.

5. Informing Government Planning and Policy-Making:

Understanding housing market trends, including property pricing, demand, and availability in certain zip codes, can inform decisions about housing policies and zoning laws. For instance, if data reveals a shortage of affordable housing in a specific region, policymakers might act to encourage developers to create more budget-friendly housing options.

Marketing and Lead Generation

We all know that qualified leads are key to increasing sales. But nurturing your leads can be a tedious process.

Web scraping can benefit marketing in practices such as:

1. Competitor Analysis:

In competitive marketing, understanding what your rivals are doing is crucial. Web scraping allows marketers to extract data from competitor websites to gain insights into pricing strategies, promotional campaigns, and new product launches.

2. Sentiment Analysis:

With the vast data generated on social media platforms, marketers can use web scraping to gauge public sentiment about their products or brand. By scraping data from social media posts, reviews, and comments, marketers can identify patterns and trends in consumer attitudes, helping them adjust their strategies based on real-time feedback.

3. SEO Optimization:

Marketers can scrape data from search engine results pages (SERPs) to understand how search engines rank websites based on specific keywords. This can help businesses optimize their content and meta tags to improve their own rankings, driving more organic traffic to their website.

4. Content Marketing:

By scraping trending topics, popular keywords, and viral content from various digital platforms, marketers can gain insights into what type of content resonates with their target audience. This knowledge can be used to create compelling and engaging content that is more likely to attract and retain customers.

5. Lead Generation:

With web scraping, marketers can gather data from directories, social media platforms, and industry forums to identify potential leads. This data can include contact information, company details, and more, providing marketers with a rich source of potential customers to target with personalized marketing campaigns.

Talk about a boost in sales leads!

News Monitoring

Scraping the news allows businesses, researchers, and individuals to access and digest vast amounts of news data in a structured format, making information more manageable and meaningful.

Use cases of news scraping include:

1. Crisis Management

Businesses can scrape data from news sites to get alerts about negative press coverage immediately after publication. This early warning system allows businesses to respond swiftly, manage the narrative, and mitigate potential damage to their brand image.

2. Tracking Regulatory Changes

By setting up a web scraper to monitor government websites, legal news outlets, or regulatory bodies, businesses can get real-time updates on regulatory changes that could impact their operations. This enables them to adjust their strategies promptly and maintain compliance.

3. Verification of Information

Businesses can use web scraping to cross-check information across multiple sources, helping ensure the accuracy of the data they base their decisions on. For instance, a company can scrape data from trusted news outlets and fact-checking websites to verify the validity of a piece of news before acting on it.

4. Audience Perception Analysis

Understanding how your brand or products are being perceived by your audience is critical for any business. News scraping can provide valuable insights by tracking news articles, blog posts, and online reviews that mention your company or products. By analyzing the sentiment and topics of these mentions, businesses can better understand their audience’s perception, identify potential issues, and develop strategies to enhance their brand image.

5. Content Creation and Strategy

By scraping trending news topics, companies can identify what content is resonating with their audience. By tracking which articles receive the most shares or comments, businesses can gain insights into what type of content is most likely to go viral, helping them improve their content strategy.

As you can see, there are multiple use-cases for web scraping. The best part is you don’t have to worry about pulling data manually. Web scraping tools automate the process in real-time.
Now let’s talk about how to get started with web scraping.

How Does Web Scraping Work?

As mentioned, a web scraper extracts and converts data from a website into readable data.
This definition is simple, but there’s much more to it! If you want to know how web scraping works, keep reading for a step-by-step explanation.

Crawl

You can’t extract data without knowing what’s out there. So the first step is to crawl a website and learn what’s on each web page.
For example, if you were to crawl our website, it would start at our homepage, www.scrapehero.com. From there, the crawler would crawl the site by following each link from our homepage.
The goal of a web crawler is to learn what’s on a web page and retrieve the data you want.

We’ll discuss the difference between web crawling and data scraping later in this post.

Parse and Extract

Now that the web scraper has crawled your data, it can extract it.

Web scrapers will parse this crawled data with CSS selectors or Xpaths. Parsing means analyzing the raw data and choosing the essential information you need.

There are different types of parsing techniques. Some include:

• Regular expressions
• HTML parsing
• DOM parsing (using a headless browser)
• Automatic extraction using artificial intelligence

Clean and Format Data

Pulling data from websites is only helpful if you can read the data. So in this step, the web scraper will convert your data into a readable format.
Most datasets need some form of “cleaning” to become readable, so the scraper will use certain methods to clean up the data, like:

• Regular expressions
• String manipulation
• Search methods

Store the Data

Now that the data has been crawled, scraped, and formatted, you can finally store it.

You’ll have to export your data into a CSV, JSON, XML, or spreadsheet. You may store it in the cloud using services like Dropbox or Google Drive. You could even put large data in databases.

And that’s how web scraping works! If you’re thinking, “Okay, that sounds complicated,” then don’t worry. You can always use a web scraping service to automate this process.

Speaking of services, let’s go over three ways to collect data with a web scraper.

Methods of Gathering Data Using Web Scraping

Now you know what web scraping is, why it’s useful, and how it works. Now let’s go over three ways to collect data.

Custom Web Scraping Services

The first way to extract data is with a custom web scraping service. Outsourcing this task avoids the time and costs associated with working in-house.

Plus, most services can extract millions of pages without your assistance. So you can focus on your projects without worrying about tedious tasks like bypassing CAPTCHAs, rotating proxies, and other methods websites use to block web scraping.

You’ll want to use custom web scraping service providers, like ScrapeHero, to extract thousands of web pages. Our software has the technology to scale to your business needs.

Web Scraping Tools and Software

A web scraping tool differs from a custom service because of its visual interface. An interface lets you decide what data you need. Once you decide what type of information you want, the software will use your instructions to build a web scraper.

Using software is a great choice as long as you have a small data set. Our cloud software, ScrapeHero Cloud, avoids downloading software to your computer.

Using our cloud software, you can access the scraper and data from all IP addresses and deliver findings to DropBox. This means your desktop won’t run out of storage from scraping.

Scraping Data Yourself

You can always collect web data yourself using almost any programming language, like:

• Python
• JavaScript (Node.js)

As a developer, open-source web scraping tools will help you with projects.
A few examples include BeautifulSoup and Scrapy, but you can check out our web scraping tutorial and guides to get started.
A time-saving approach to scraping data yourself is to prompt large language models such as ChatGPT to generate scraping scripts for you. If you’re interested in learning more about this method, read Web Scraping using ChatGPT: A Comprehensive Tutorial

Before you start data scraping, consider the size of your company. Writing code from scratch with smaller data scraping needs is one thing. But you’ll need a web scraping service to scale up if you want to extract different web pages and thousands of data fields.

If you don't like or want to code, ScrapeHero Cloud is just right for you!

Skip the hassle of installing software, programming and maintaining the code. Download this data using ScrapeHero cloud within seconds.

Get Started for Free

Web Scraping FAQs

You might have a few more questions about scraping data, like whether it’s legal or how much it costs. See below for a few of the most commonly asked questions.

1. What is the difference between web scraping and web crawling?

People often use the terms web scraping and web crawling interchangeably. Although they both collect data from the web, they have different purposes.

Web Crawling downloads and stores website data by following links in web pages. Crawlers can navigate through pages independently because they are a standalone bot—they’re the backbone of search engines like Google, Bing, and Yahoo.

On the other hand, a web scraper handles the structure of a specific website. It uses this site-specific structure to pull individual data elements from the website. Unlike a web crawler, a web scraper collects particular information, such as pricing data, stock market data, and business leads.

If you have a hard time differentiating web crawling and web scraping, remember this: Web crawlers scan and index web pages, while web scrapers extract data from web pages.

2. Is Web Scraping Legal?

Web scraping is controversial and raises legal questions about copyright and terms of service. With that said, it’s difficult to prove copyright over specific data, as only a selection of data is legally protected. So most scrapers can pull web data without any copyright infringement.

3. How Much Does Web Scraping Cost?

Hiring a web scraping service to scrape data from a simple website can cost anywhere from $250 to $500 monthly. But it varies on the service and whether they charge by the hour or with a fixed price.

So what if you’re interested in building an in-house team of scrapers?

Hiring in-house might sound like a good idea, but consider how much more you’d pay each employee. Most large-scale scraping projects need a team of at least five people, so you’d be paying five full-time salaries for a service you can outsource.

You might wonder, “I’m not a company, but an individual. How much would it cost for me to do it myself?”

If you’re a developer working on a side project, taking on the job yourself makes sense. But if you’re running low on time, you might want to outsource the job or use a quick and easy-to-use tool like ScrapeHero Cloud.

4. How long does Web Scraping take?

If you run a company, it can take months to gather the tools and employees to start web scraping, especially if it’s an ongoing project.

As for developers, it depends on your expertise and data size. It can take you anywhere from hours to months.

Most web scraping services, like ScrapeHero, can set up your website and start sending data in a week or less. We’re a team dedicated to scraping data, so the turnaround time is much quicker.

5. How Do I Practice ‘Ethical Web Scraping’?

If you request data too frequently, the website you’re collecting from will block you. And because the website owner has a property interest, you may be liable for damages.

That doesn’t sound too fun, does it?

Luckily, you can avoid this entirely with “ethical web scraping.” An ethical scraping tool will request data a reasonable amount of times. They avoid getting blocked because they aren’t bugging the website in the first place.

This is a big reason why most companies outsource web scraping. Most web scraping services, like ScrapeHero, know how to “politely” request and extract data.

You can learn how to prevent getting blocked here.

What’s Next?

Throughout this article, we have answered the question- of what web scraping is, discussed its use cases, broken down the process, and illustrated multiple methods to do it. We have shown how this efficient technique enables us to collect, structure, and utilize vast amounts of data from the web, a crucial skill in areas like data analytics, machine learning, and artificial intelligence.

With a clear understanding of web scraping, you can now tap into online data in a precise and automated way.

This knowledge is a valuable asset, especially in an age where the ability to gather and interpret large volumes of information quickly is increasingly important.

Web scraping is not just a technique; it’s a critical skill for anyone looking to use digital resources effectively.

As you continue to explore and apply web scraping, you’ll further realize its potential in unlocking valuable insights from the expansive digital universe.