Web Scraping as a Research Tool - Guide from ESK-Solutions
Internet, which has more than 2 billion websites, is the largest database the planet Earth has ever seen. With virtually unlimited data at your fingertips, the question is no longer "does this information exist?" but rather "how can I get it?".
Defining the data you need is very important, but it is only half the battle. Collecting information can be complex, expensive, and time-consuming, which is why professional software for web scraping comes to the rescue.
Data parsing, also known as data collection, is a technique designed to automate the extraction of information from the Internet. Professional website scraping software is used to find and collect target data (in the form of text, images, or downloaded files) and convert it into a convenient format. Data parsing simplifies the process of obtaining information at scale and allows you to take only what you need without spending hours manually browsing sites, searching for data fields, or manually copying information.
Why ready-made software for website parsing?
There are three common approaches to extracting data using professional scraping software:
- Manually collect data from the target site(s).
- Hire developers to write custom scripts.
- Use ready-made scraping software.
Manual data collection is only effective for very small projects; it is labor-intensive and tedious work; because it depends on human input, this method can also lead to costly input errors. Hiring an engineer to write custom scripts can provide good data, but this approach is expensive, slow, and requires constant rewriting of scripts for new projects.
For many organizations, using ready-made scraping software is the most practical solution. It is a fast and cost-effective solution that stands out in several key areas:
Good data parsing software allows users to find, extract, and export data with minimal technical knowledge. The user interface enables non-developers to manage the data collection process from start to finish and adapt their data collection project without needing to write code.
Built-in features: Website scraping software comes with tools to help you overcome the challenges of the ever-changing Internet. Features such as geolocation and cookie storage make it easier to collect data from complex sites.
Data integration: Data cannot achieve much in isolation. Some scraping software allows you to connect collected web data directly to other digital tools—from CRM to data processing and visualization packages.
Value: Web scraping is an inexpensive way to accumulate data for organizations of all shapes and sizes. It minimizes the time and training required to implement effective data collection projects.
How can this information be useful for each industry?
There are almost as many scraping tasks as there are pages on the Internet, but some use cases are more common than others. Here are four typical applications of scraping:
#1: Retail
In the competitive world of retail, it is no surprise that every business needs to stay on top of competitors' prices and products 24 hours a day, 7 days a week. Being aware of new discounts or products allows retailers to stay ahead of the competition and make quick strategic decisions.
#2: Travel
With the rise of cheap flights and new destinations emerging every day, travel companies need to monitor their competitors. Travel companies also use site scraping to track traveler reviews and feedback, enabling them to respond quickly to issues and adapt to customer needs.
#3: Real Estate
Real estate markets are very dynamic, which can make it difficult for agents and organizations. Leaders in real estate use site scraping to track changes in price indices, competitor listings, and market statistics. Web scraping is ideal for extracting multiple data fields (e.g., time on market, price changes, square footage, etc.) from property listing sites such as Avito.
#4: Journalism and Academic Research
In an age of misinformation, it is more important than ever for journalists and researchers to have access to accurate data. Scraping reduces the time needed to compile statistics, catalog secondary sources, and extract large datasets for further analysis, so writers and researchers can spend more time verifying sources and creating compelling content.
All these cases have in common that they require large volumes of important data obtained from limited sources to analyze the relevant industry and draw necessary conclusions. Regardless of where you work or what your project entails, the ability to use web data can increase efficiency, drive growth, and provide the "secret sauce" needed to stay ahead of competitors.