Data science is transforming the world, and almost every industry is adopting it. From small startups to top-notch MNCs, almost every company is pouring in money to extract data and achieve desirable results. For any product to get a good response from the market, it is important to do a complete market survey to understand who your potential customer is. What if we tell you that you can do all this staying right where you are. For any project, you require a vast amount of data to start. This is where web scraping comes into the picture. So what exactly is web scraping? Let’s find out!
What is Web Scraping?
It is quite obvious that the first thing any business owner would do is look to generate potential clients. Have you ever thought of extracting data from a competitor’s website, and using it to produce desired results?
Most companies use this methodology to enhance their business. Some try to copy data from the website and paste it. This can be done when there is a very small amount of information that needs extraction. But most sites have vast amounts of data. You can’t copy and paste that much information. With the process of web scraping, you can extract almost any amount of data, and save it in the desired file format.
By definition, web scraping is nothing but the process of extracting data and saving it in the desired format, be it XLS. or CSV. format automatically. The time spent on gathering every information can get reduced to a considerable extent with the help of web scraping. It automates the whole process of copying and pasting.
Web Scraping in Retail and Manufacturing
Web scraping is a significant tool used in the retail and manufacturing industry. Manually keeping track of the prices of a product is never a feasible option, and it is quite time-consuming. Web scraping provides a better solution for this. You can extract competitors’ prices, and come up with a better pricing strategy to garner a considerable number of potential leads.
When it comes to purchasing materials from the retail market, you actually can’t visit every site and keep an eye on the retail market. This is where web scraping comes into the picture. Most companies spend enormous amounts of money to understand the retail market. However, with web scraping, you can reduce the cost spent on MAP compliance.
Using web scraping, you can analyze and track the customer sentiment. This enables you to come up with a product that meets the customer requirement and makes it more viable. Using web scraping, you can attain competitors product descriptions and understand the competitors marketing strategy.
Web Scraping in Financial and Equity Research
Major financial insights are available through newspapers and articles. It is not possible to go through every article, instead, you can opt for web scraping, through which you can extract all the data and keep track of all the information. There is a surplus amount of market data available on the internet, but it remains scattered across various websites, making it quite difficult to collect data from each site. Web scraping does that for you and helps you come up with the best investment strategies.
The insurance industry is another field that requires well defined and specified policies. You cannot copy it from any mediocre website. Using web scraping, you can extract suitable information from the most verified sites and come with a policy that meets all the standards laid by the Insurance Act of 1938.
Web Scraping in Sales and Marketing
Sales is one of the most pivotal departments in any industry. Most top-notch companies invest around 30–40% of the money on enhancing sales and creating a strong brand presence. With the surplus data that is available online, it has become difficult to extract suitable forms of information. This is where Web scraping comes into the picture.
It captures this data and provides a list of the kind of audience and their preferences. With this list, it is easy to target a specific group of people, and the chances of generating a potential customer increase to about 33%. With data scraping, you can collect information from social media platforms like Facebook, Twitter, Instagram and use this information to come up with posts that can garner greater attention and help build a brand presence.
Search engine optimization is a significant part of digital marketing. Without SEO content, it might be difficult for your site or content to feature at the top of the charts. With the help of web scraping, it is easier to extract the exact keywords to make your site reach high in the Google ranks.
There are several email marketing tools like Mail Chimp, Omnisend, and Hubspot that require client mail ideas to send a sales mail. Using web scraping, you can extract all the mail IDs and use these tools to send sales mail in one go. You can also create a chatbot and send customized messages to the potential customers generated using web scraping.
Best Programming languages for Web Scraping
It is quite obvious that the best programming language for web scraping in Python. There are many predefined libraries that you can use for web scraping.
Pandas: This library gets used for extracting data and manipulating it. It saves all the databases in a certain format.
Selenium: Selenium library extracts data from the web pages. It uses a web driver for Chrome for analyzing commands.
BeautifulSoup: This library is for extracting XML and HTML files. It employs data trees to extract data easily.
How Web Scraping is useful for a data scientist?
Web Scraping has multiple applications when it comes to data science. It gets used in real-time analytics, predictive analytics, natural language processing, and machine learning training models. With web scraping, it is easy to cluster, classify and contribute ideal sources of data.
Data science is more of statistics implemented with programming. Web Scraping extracts the desired data to enhance productivity and reduce the downtime of a workforce to a considerable extent. The roles and responsibilities of a data scientist are to garner an ideal amount of information, but with the help of web scraping, it is easier to extract this data and make this data usable for machine learning models.
From mediocre start-ups to top-notch MNCs, almost every enterprise uses data science and web scraping as a tool to produce potential leads. Companies like Facebook, Netflix, and Amazon have been roping in data scientists to extract the data and provide a better user experience. Recommendation engines are a product of data science and web scraping. The data about user preferences get recorded, and this information provides them with similar search results.
Closing Thoughts
Web scraping has become a significant tool used by most digital marketers and companies to achieve results. The implementation of web scraping in data science has reduced the work of data scientists to a considerable extent. Now all they have to do is use the ideal extracted data and conduct data analysis. The future of data science has become the next big thing, and the need for quality data scientists is on the rise. If you are looking to make a career out of data science, this is the best time to grab hold of the opportunity.
With the current COVID-19 pandemic, you can get yourself equipped with data science through free data science courses and there are also several Python tutorials for beginners. A premier tech-related educational institution like Great Learning can help you learn data science. The data science courses are excellent learning sources and favour e-learning as well. To know more details about the data science certification course or data science online course, get in touch with us today.
