5 Ways Big Data And Web Scraping Through API Is Revolutionizing Business Intelligence

Every decision-making process in a business is founded on the basis of accurate, relevant information collection and getting the most out of it in an effective manner. But, with over 2 billion webpages overflowing the internet, the manual collection of such big data is impossible. So, what is the solution? A Web Scraping API!

While web scraping is an ultra-modern, innovative data extraction technique that enables to fetch the HTML of a webpage, the API allows in data collection automation on a large-scale basis.

Here are 5 ways how big data and web scraping can be leveraged to improve business analytics and intelligence.

  • Content aggregation

When it comes to the majority of media websites, gaining access to information that is trending on the web in a continuous and consistent fashion and reporting the most recent news quickly are important facets that need to be taken into account.

With the help of web scraping, it is conceivable to keep track of popular social media platforms or news portals to get hold of up-to-the-minute information. This is achieved by resorting to trending keywords and topics. Also, when you use web scraping, updates can happen very fast.

One more application of content aggregation enables various business development groups to identify the companies that have plans of expansion or relocation. This is achieved by scanning through news articles. Thus, it is always possible to obtain precise updated information by virtue of web scraping techniques.

  • Competitor monitoring

In general, all e-commerce businesses need to keep an eye on their competitors to acquire real-time information of their business strategies and make small adjustments to their own to derive competitive advantage.

To gain a competitive advantage in your niche market you need to be collecting data about your competitors. You can not do it manually and hence price scraping becomes a must-to-do task for you using a tool or API.

Web scraping through API facilitates business owners to keep competitor activities under close surveillance regardless of their promotional activities or update on product information. 

A business can gain more popularity when product deals and details offered by the competitors are pulled out and reviewed amid the cutthroat online space. Web scraping also allows incorporating the extracted information into the system. Following this, it determines the ideal price for each product after a comprehensive analysis of the collected information.

  • Sentiment analysis

Any project revolving around sentiment analysis is based on user-generated content (UGC). By and large, this type of data includes:

  • Books
  • Complaints with regard to products and services
  • Consumer-centric services or events
  • Events
  • Movies
  • Music
  • Opinions
  • Product reviews

This information can be effortlessly derived through the deployment or one or more web crawlers designed to gather data from multiple sources.

  • Market research

Market research is an indispensable activity which nearly all companies are bound to carry out. The various online platforms such as social media or several other review forums provide anchorage to various kinds of data. These include:

  • Product information
  • Tags
  • Reviews

Market research conducted via traditional methods of data collection is time-intensive and expensive affair. Through the extraction of relevant, voluminous data by means of the web scraping APIs, it is feasible to easily adopt a simple approach to execute market research and secure gainful results.

  • Machine learning

Similar to sentiment analysis, the availability of a massive quantity of appropriate data through web scraping paves the way to obtain good educational stuff related to machine learning technology. By undertaking entity extraction belonging to metadata values and fields or procuring tagged extracted content it is possible to learn natural language processing.

At the same time, information gathered from tags and categories can be used to execute statistical tagging or bring about the formation of clustering systems. Thus, the web scraping technique aids in picking up extracted data more accurately and efficiently.

Conclusion

So, web data scraping is a process that has a resemblance to automatic copy-paste activity. It is a developing field of expertise that can come up with compelling insights to offer support to business analytics and intelligence.

To scrape websites, the need to have programming skills is optional. There are wide-ranging scraping tools and service providers. Not only do they provide readily available web scraping templates to help develop a scraper, but extend services of customized data extraction as well.