Business Intelligence is a process of transforming the data into information and turning information into actionable insights. However, a successful business intelligence strategy is only on the premise that we have enough valuable data in a structured format for us to generate in-depth analysis. But how? As of today, the amount of data scattering across the internet is far beyond our capacity to consume, let alone digging out valuable information. But don’t worry! If there’s a problem, there is a solution.
Web data extraction refers to an automated process to collect data that replaces the traditional way of manual work of copy and pastes. There are many ways to achieve automation, either writing code by yourself or hiring a freelancer to do the job for you. However, the most cost-effective method would be a SaaS to manage the process with a reasonable time.
I list four real-world examples of how web data extraction plays into the system of business intelligence.
Social media data comes with many forms. They can be blogs, reviews, posts, images, comments, social engagements and more. Social media data extraction can explore business opportunities, track competitors, monitor consumer sentiment by extracting this information on a regular basis.
E-commerce practitioners often need to look out for prices from single or multiple websites. They also need to compare competitors’ with what they offer daily to optimize their marketing efforts accordingly. Web data extraction makes it possible to track prices every few minutes and update the information to your database. This allows you to monitor the price volatility and make a dynamic price strategy.
Business needs to track and improve their presence and visibility across social media. Data extraction can collect positive, negative mentions and the people who mention the product on time. As such, you can react to grievances in time. Even better, build a relationship with those who speak highly about your brand, and turn them to your brand evangelists.
If you need to track how your competitors are handling their products, you can leverage web data extraction to collect the product information across multiple websites including Amazon, eBay, Walmart, etc. As a result, you can take a better assortment decision.
These are just a few examples of data extraction applications in business intelligence. But please be aware that the business intelligence environment is way more complex. It involves methodology, applications, and technologies to enable entire information processing. And a sufficient volume of quality data enables us to draw a conclusion from data analysis, discover patterns and forecast future events, eliminate risk. In this case, data extraction has a great impact on business operations.
Choosing the right method to extract data is crucial. Traditionally, people would write code to extract web data. The most common programming languages would be python or R. These coding-approaches can get you a sheer volume of data at a certain time. Yet, as soon as the structure of the webpages changed, they have to rewrite the code or even have to change the entire approach.
Web pages are constantly changing. They are dynamic, and it challenges us to get data from the internet. In this sense, the data extraction tool would be the most cost-effective method. An intelligent web data extraction tool like Octoparse can achieve real-sense automation. Its advanced features ensure that you can extract data from dynamic websites while also being intuitive and user-friendly without coding.
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