Organizations generate a plethora of data on a daily basis. For any organization to have a successful business model, collecting insightful information is imperative. This information can be retrieved from the existing data that the organizations have. Often, it is observed that while segregating data, instead of retrieving the insightful information, organizations retrieve reliable information, which gives them the idea of what they are looking for, but doesn't help them to understand the importance of the retained information. But, for any organizations to grow and evolve, it becomes imperative that information which gets retrieved is insightful. That's where the process of Web Data mining comes into the picture.

Just like the manual process of mining which is conducted for extracting minerals, web data mining is the process of extracting information, that determines the patterns, trends, and ideas for accelerating business intelligence, observing business growth, and promulgating strategies that can be deployed for business excellence. Business intelligence is also governed by analysing the inputs installed by the competitors' company, observing its market share,  and deriving patterns that can accelerate, and enhance business. Hence, integrating business models with web data mining would be crucial for the success of the organizations.

Understanding Web Data Mining

The Web data mining is the process of automatically identifying and extracting information from the available documents and services available online, in order to identify patterns and behaviour of customers towards a product, observe the pattern in the sale of that particular product and for improving the capability of the Search Engine Optimization for identifying useful web pages.

A Successful business model does not only involve scanning through the data available on the web, but also picking out information that is of paramount importance. According to experts, successful web data mining would involve the following applications:

• Scanning through the news articles of the rival companies, for identify the strategic plan of that company.
• Looking through the 10-k filing, so that insights about the product development, sales, and purchases can be derived, and comparing it with the company's sales, purchase and product models, so that difference can be observed.
• Automatically finding and analyzing the government rules and regulations
• Identifying and tracking conferences with locations and organizations.

Web Data Mining using Web Content

Web content mining, extracts information from the web documents, by analyzing the text, videos and images, using machine learning and natural language processing. Web content mining would help in identifying that information that is driving the content of the rival company to be successful. By analyzing the blogs put out by the rival company, or accessing the videos and images, the organizations will have an idea about the quality and speciality of the products offered by the competitor. This will drive them to chalk out strategic processes that will upscale their products.

Web Structure Mining

Web structure mining extracts the information from the structure of the data available online. By analyzing the data available online, organizations will be able to track down the nodes, hyperlinks, and web graphs, which will be helpful in determining the link between different commercial products. By analyzing the hyperlinks in the content of the rival company, necessary information like the market performance can also be retained.

Web Usage Mining

With the help of the machine learning model, web usage mining extracts information from the large sets of data, to understand customer behaviour.

Hence for any successful business model, it becomes paramount that insightful information is readily available, so that data-driven decisions can be made.