In today’s competitive world everybody is looking for ways to innovate and make use of new technologies. Web scraping (also called web data extraction or data scraping) is an automated process that extracts data from a website and exports it in a structured format.
Web scraping is useful if the public website you want to get data from doesn’t have an API, or only provides limited access to web data.
In this article, we are going to shed some light on web scraping, here’s what you will learn:
Web scraping is the process of collecting structured web data in an automated fashion. It’s also known as web data extraction.
In general, web data extraction is used by people and businesses who want to make use of publicly available web data to make smarter decisions.
If you’ve ever copied and pasted information from a website, you’ve performed the same function as any web scraper, only you manually went through the data scraping process. Unlike the tedious process of extracting data by yourself, web scraping uses intelligent automation to retrieve hundreds, millions, or even billions of data points from the internet’s seemingly endless frontier.
Whether you’re using a web scraper to get web data or outsourcing the web scraping project to a web data extraction specialist, you’ll need to know a bit more about the differences between web crawling and web scraping.
Just as importantly, you’ll need to understand the possible pitfalls of extraction and how to avoid them.
Web scraping provides something really valuable that nothing else can: it gives you structured web data from any public website.
More than a modern convenience, the true power of data web scraping lies in its ability to build and power some of the world’s most revolutionary business applications.
‘Transformative’ doesn’t even begin to describe the way some companies use web scraped data to enhance their operations, informing executive decisions all the way down to individual customer service experiences.
Web data extraction – also widely known as web data scraping – has a huge range of applications.
A web scraper automates the process of extracting information from other websites, quickly and accurately. The data extracted is delivered in a structured format, making it easier to analyze and use in your projects.
The use of web data extraction tools to scrape public websites can benefit different industries.
In the world of e-commerce, a website scraper is commonly used to get data for competitor price monitoring. Data scraping is the only practical way for brands to check the pricing of their competitors’ products and services. This allows them to fine-tune their own price strategies and stay ahead of the competition. It’s also used as a tool for manufacturers to ensure retailers are compliant with pricing guidelines for their products.
Market research organizations and analysts depend on using a website scraper for data extraction to gauge consumer sentiment by keeping track of online product reviews, news articles, and feedback.
A web scraper also has a vast array of applications in the financial world. Tools that scrape web data are used to extract insight from news stories, using this information to guide investment strategies.
Similarly, researchers and analysts depend on data extraction to assess the financial health of companies. Insurance and financial services companies can mine a rich seam of alternative data scraped from the web to design new products and policies for their customers.
The endless methods and applications for web data extraction don’t end there.
Web data scraping is widely used for:
It’s extremely simple, and works by way of two parts: a web crawler and a web scraper.
The web crawler is the horse, and the scraper is the chariot.
The crawler leads the scraper, as if by hand, through the internet, where it extracts the data requested.
Learn the difference between web crawling & web scraping and how they work.
A web crawler, which we generally call a “spider,” is an artificial intelligence that browses the internet to index and search for content by following links and exploring. Just like a person with too much time on their hands.
In many projects, you first “crawl” the web or one specific website to discover URLs which then you pass on to your scraper.
A web scraper is a specialized tool designed to accurately and quickly extract data from a web page. Web data scraping tools vary widely in design and complexity, depending on the project.
An important part of every web scraper is the data locators (or selectors) that are used to find the data that you want to extract from the HTML file - usually, XPath, CSS selectors, regex, or a combination of them is applied.
Understanding the difference between a web crawler and scraper, lets you move forward with your web data extraction projects.
A web scraping tool is a software program designed to extract (or ‘web scrape’) relevant data from websites. You’ll almost certainly be using some kind of web scraper to extract specific datasets when collecting data from websites.
A scraping tool, or website scraper, is used as part of the web scraping process to make HTTP requests on a target website and extract web data from a page. It parses content that is publicly accessible and visible to users and rendered by the server as HTML.
Sometimes it also makes requests to internal application programming interfaces (APIs) for associated data – like product prices or contact details – that are stored in a database and delivered to a browser via HTTP requests.
There are various kinds of web scrapers and data extraction tools, with capabilities that can be customized to suit different data extraction projects.
You might need a web scraping tool to recognize unique HTML site structures, or extract, reformat and store data from APIs.
Web scraping tools can be large frameworks designed for all kinds of typical scraping tasks, but you can also use general-purpose programming libraries and combine them to create a scraper.
For example, you might use an HTTP requests library - such as the Python-Requests library - and combine it with the Python BeautifulSoup library to scrape data from your page. Or you may use a dedicated framework that combines an HTTP client with an HTML parsing library.
One popular example is Scrapy, an open-source library created for advanced scraping needs.
Are you wondering how to scrape a website or how web data extraction process works?
This is what a general DIY web scraping process looks like:
Simple enough, right? It is!
That is, if you just have a small project.
But unfortunately, there are quite a few challenges you need to tackle if you need data at scale.
There are multiple open-source web data scraping tools that you can use but they all have their limitations.
That’s part of the reason many businesses choose to outsource their web data projects.
1. Our team gathers your requirements regarding your project.
2. Our veteran team of web data scraping experts writes the scraper(s) and sets up the infrastructure to collect your data and structure it based on your requirements.
3. Finally, we deliver the data in your desired format and desired frequency.
Ultimately, the flexibility and scalability of web scraping ensure your project parameters, no matter how specific, can be met with ease.
Fashion retailers inform their designers with upcoming trends based on web scraped insights, investors time their stock positions, and marketing teams overwhelm the competition with deep insights, all thanks to the burgeoning adoption of web scraping as an intrinsic part of everyday business.
For all but the smallest projects, you’ll need some kind of automated web scraping tool or data extraction software to obtain information from websites.
In theory, you could manually cut and paste information from individual web pages into a spreadsheet or another document. But you’ll find this to be laborious, time-consuming, and error-prone if you’re trying to extract information from hundreds or thousands of pages.
Web scraping applications and website scrapers, automate the process, extracting the web data you need and formatting it in a structured format for storage and further processing.
Another route for data scraping, is actually buying the web data you need from a data services provider who will extract it on your behalf. This would be useful for big projects involving tens of thousands of web pages.
In our experience, price intelligence is the biggest use case for web scraping.
Extracting product and pricing information from e-commerce websites, then turning it into intelligence is an important part of modern e-commerce companies that want to make better pricing/marketing decisions based on data.
Web pricing data and price intelligence benefits:
Market research is critical – and should be driven by the most accurate information available. With data scraping, you get high quality, high volume, and highly insightful web scraped data of every shape and size is fueling market analysis and business intelligence across the globe.
Unearth alpha and radically create value with web data tailored specifically for investors.
The decision-making process has never been as informed, nor data as insightful – and the world’s leading firms are increasingly consuming web scraped data, given its incredible strategic value.
The digital transformation of real estate in the past twenty years threatens to disrupt traditional firms and create powerful new players in the industry.
By incorporating web scraped product data into everyday business, agents and brokerages can protect against top-down online competition and make informed decisions within the market.
Modern media can create outstanding value or an existential threat to your business - in a single news cycle.
If you’re a company that depends on timely news analyses, or a company that frequently appears in the news, web scraping news data is the ultimate solution for monitoring, aggregating, and parsing the most critical stories from your industry.
Lead generation is a crucial marketing/sales activity for all businesses.
In the 2020 Hubspot report, 61% of inbound marketers said generating traffic and leads was their number 1 challenge. Fortunately, web data extraction can be used to get access to structured lead lists from the web.
In today’s highly competitive market, it's a top priority to protect your online reputation.
Whether you sell your products online and have a strict pricing policy that you need to enforce or just want to know how people perceive your products online, brand monitoring with web scraping can give you this kind of information.
In some situations, it can be cumbersome to get access to your data. Maybe you need to extract data from a website that is your own or your partner’s in a structured way.
But there’s no easy internal way to do it and it makes sense to create a scraper and simply grab that data. As opposed to trying to work your way through complicated internal systems.
Minimum advertised price (MAP) monitoring is the standard practice to make sure a brand’s online prices are aligned with their pricing policy.
With tons of resellers and distributors, it’s impossible to monitor the prices manually.
That’s why web scraping comes in handy because you can keep an eye on your products’ prices without lifting a finger.
There are various free web data scraping solutions available to automate the process of scraping content and extracting data from the web. These range from simple point-and-click scraping solutions aimed at non-specialists to more powerful developer-focused applications with extensive configuration and management options.
If you’re viewing a website – just as you’re doing now – you could simply cut and paste the information you’re reading on screen into another document like a spreadsheet. It’s certainly one way of extracting web data for free. But collecting data and gathering information manually this way is slow, inefficient, and error-prone.
In practice you’ll be looking at ways to automate this process, allowing you to extract web data from multiple web pages – maybe thousands or millions of them per day – and organize the results in an structured format.
To achieve this you’ll need some kind of web data extraction tool, often known as a web scraper.
There are plenty of free web scraping solutions out there to extract data from the web. Some of these are dedicated applications aimed firmly at programmers, requiring a level of coding proficiency to configure and manage.
With that said, are free web scraping tools and web scrapers efficient?
They are ideal for non-specialists with moderate extraction needs.
There are also some easy-to-use scrapers that run as a browser extension or plug-in with a simple point-and-click interface. Less sophisticated than their developer-focused counterparts, they’re typically more limited in the variety and volume of data they let you scrape.
Here at Zyte (formerly Scrapinghub), we have been in the web scraping industry for 12 years. We make automated web scraping easy.
With our data extraction services and automatic web scraper, Zyte Automatic Extraction, we have helped web scrape data for more than 1,000 clients ranging from Government agencies and Fortune 100 companies to early-stage startups and individuals.
During this time we gained a tremendous amount of experience in web scraping and web data extraction.
Here are some of our best resources on how to scrape the web, and tools and services used for web scraping if you want to deepen your knowledge as a web scraper: