Do you wish to make informed decisions to entice your existing customers and to pull in new prospects? Then, you have to adopt innovative technologies. In this article, we shall discuss more about the technology that is creating the buzz–web scraping–its different types, web scraping using Python and its applications.
What is Web Scraping?
As we all know, the Internet is a repository of information. Several businesses make the most of web scraping. Indeed, a business can gather and analyze the data of its competitor’s website. You can implement price monitoring and adjust your pricing methods as well.
Web scraping is the process of extracting data from the Internet, websites, social media, blogs and so on. With the help of software tools, web scraping can be implemented easily. For instance, web scraping using Python is the most popular.
How Does Web Scraping Work?
The very objective of a web scraper tool is to extract and store data for analysis. Usually, web scrapers are given URLs of websites from which you need to collect the data from.
Typically, a web scraper tool collects the data from the web pages. It is used for extracting the needed information. Then, the data is exported to an Excel spreadsheet or other formats for further analysis.
What is Web Scraping in Python?
Web scraping in Python automates the process of data collection from the Web. To start with, you need to gather the desired data. All you need is the URL of the target website from which you want to scrape the data. The data collected in the unstructured format needs to be transformed into structured ones to get useful insights. For this purpose, data is collected, stored and processed.
A Few Fundamental Steps in Web Scraping
If you want to extract data with web scraper using Python, follow the below fundamental steps:
- Select the URL from which you want to extract data
- Identify the data you want to collect
- Write the code
- Run and extract the data
- Store the fetched data
The Web Scraping Process
When you run the code for web scraping, a request is sent to the URL given. Responding to the request, the server sends the data and lets you access and read the HTML or XML page. The code parses the HTML or XML page and identifies and extracts the data.
What are the Different Types of Web Scrapers?
Now that we have discussed the web scraping process, we shall go through a few types of web scrapers. Based on their functions, web scrapers are classified as follows:
Browser Extension
You can add these extensions to browsers such as Chrome, Firefox and so on. Further, you can integrate it into almost all browsers directly.
It is ideal for those businesses which want to extract small amounts of data. However, there is a drawback. It does not support Internet Protocol (IP) address rotations and scrapes only one page at a time.
Cloud-based Scrapers
These web scrapers use an external server offered by a company that develops the web scraper tool. Therefore, it does not require installation on the system. All you need is to set up the data plan and your requirements.
The web scraper does the job! More importantly, it helps integrate advanced features. Therefore, cloud-based scrapers are useful for collecting large amounts of data.
Self-built Scrapers
It is possible to develop your web scraper tool. But at the same time, it requires the knowledge of programming language. The utilities and functionalities improve with the features added to your web scraper.
If you want more features, you may need more in-depth programming knowledge. This method is very easy to use and comes in handy. If you want to scrape similar pages, it becomes useful. Further, it is faster than manual implementation.
Installable Software
We all know that the demand for data is continuously increasing. More businesses have started developing installable web scraping software on their computers.
Most programs run on Windows and output the data in Excel spreadsheet, CSV or any other format. It is ideal for businesses that want to extract small and medium-sized data. Top of all, it can scrape several pages at a time.
Applications of Web Scraping
Several industries benefit from the top use cases of web scraping. Here are a few areas where web scrapers are used.
1. Market Research
Web Scraping is used for implementing market research by businesses. For marketing purposes, large chunks of data collected would help companies to analyze consumer trends. Additionally, it gives the company insights into taking the most appropriate action.
2. Product Price Monitoring
Businesses use web scrapers to scrap competitors’ data to check the impact of their pricing policies. Also, they use the data to make optimal pricing decisions.
3. Content and News Monitoring
Web scraping news sites bring exclusive reports on up-to-date news to your business. For example, if you are a company that makes news, using the web scraper tool for news data is a great way to collect and parse essential data within your industry.
4. Brand Monitoring
Are you selling products online? Are you concerned about how people respond to your brand? Do you want to know what your customers say about your product?
Brand monitoring is the answer! You can use the data collected from the web scraper tool to analyze brand acceptance — and frame customer service policies to enhance brand awareness.
5. Social Media Analysis
Just like brand monitoring, social media websites offer valuable data. For example, by analyzing the interactions you get from social media posts, you can effortlessly know how your customers perceive your business.
Social media scraping gathers social media data for sentiment analysis, improving audience engagement, marketing research and so on.
Frequently Asked Questions:
Which language is ideal for web scraping?
Python is considered the best language for developing a web scraper tool. It is simple and can handle data extraction effortlessly.
Is coding knowledge needed for web scraping?
Self-built web scrapers need advanced coding skills. You should be well-versed in coding if you wish to incorporate more features.
Why do you use web scraping tools?
Web scrapers enable businesses to collect the needed data and derive useful insights from them.
Artificial Intelligence in Web Scraping
Recently, integrating artificial intelligence (AI) into web scraping made it easy to scrape information more conclusively. AI-powered web scrapers are particularly useful when businesses need to scrape data from complex and dynamic websites. It is used when the scraped data has to be classified and analyzed.
Furthermore, AI-powered web scrapers extract data from websites that use an anti-bot system. Also, Natural Language Processing (NLP), an important component of machine learning, helps summarise content and performs sentiment analysis and entity recognition.
Final Words
Web scraping is a useful technique that has transformed how we gather data from the Internet. It does not matter which industry you belong to; web scraping is a great solution to fetch relevant data from the Internet.
Being a leading AI services provider, ThinkPalm possesses the capabilities to integrate AI into the data extraction process to fetch relevant information. Connect to us if you have requirements for data extraction support or any other related needs. Our AI-powered services can empower your business through enhanced services to customers.
Author Bio
Silpa Sasidharan is a content writer and social media copywriting expert working at ThinkPalm Technologies, who aspires to create marketing texts for topics spanning from technology, automation and digital business solutions.
