Introduction
Web scraping is the technique of collecting data from the internet. Getting the required information from the web pages is defined as data extraction. It involves systematic access to the structured web data that works in an automated fashion. Today, people are constantly looking for information that is useful to them. The universe of the web is full of diverse data that is utilized by companies, organizations for their use. This systematic method of extracting information is called web scraping.
Why Web Scraping?
No doubt loads of information is available on the web. But web scraping with Python is useful when the information is not public to everyone and there is just limited access to the information. Also, when the websites do not have any API, data scraping or data extraction techniques are applied.
Scope of Web scraping
The web is scraped to extract data from the web in an automated fashion. There are many uses of data extraction, but the following are some of the cases where web scraping is mostly used.
1. Price monitoring
Price monitoring is the process of scraping the prices of your competitors or various other factors that control the price evaluation of an item. Web scraping price works in the following fashion. It monitors and analyses the prices of all the factors and competition to adjust the price tag of your item. Now if the competitor slashes the prices to $10 per item. You can automatically set the price on your website to 10 or less.
2. Price intelligence
Web data scraping tool involves evaluating the price of the competitors and making a pricing decision based on it. Price intelligence involves making competitor monitoring an easier task. It aids in dynamic pricing, revenue optimization, and product trend monitoring. Also, it is mostly used for brand and MAP ( Minimum advertised price) analysis.
3. News Monitoring
In today’s competitive world, time is money. We all need access to the latest updates and news happening worldwide. News scraping is an activity that involves taking action based on current happenings. It involves, making data-driven strategies in various spheres of business.
4. Lead generation
Lead is the first-ever step for any sale to happen. If you have enough leads you can ultimately convert a good percentage out of them into sales. Web scraping helps scrape leads online to the advantage of the business professional. The leads get populated in an automated fashion, and hence you can get access to the information available on the web.
5. Market research
Market research involves making informed decisions with diligence to come out with a strategy. Market research involves extracting information based on market research firms, directories, news sites, and industry blogs. It gives relatively studied access to information regarding opportunities and potential customer base.
Conclusion
Data extraction techniques are being utilized by people and business corporations to extract information and make wise decisions related to their work. Web scraping helps populate data in automated fashions thus making its evaluation an easier task. Many Python development companies provide world-class web scraping techniques to parse websites that have been structured to provide limited access to information.
Guest article written by: Jasmeet Sehgal is a content marketer and an MBA in Finance, currently working with Sifars. She writes for people to combat the content gremlins and succeed with technology doses. She helps them build measurable technological strategies that are time efficient, essential for business, deliver results, and provide valuable insights.