Exploring value creation through web mining: a case study on the online weather forecast business

The rapid progress of internet business makes organizations and companies to accumulate vast amounts of web data. It is a tremendous challenge to extract valuable information from vast amounts of these data. Generally, traditional data analysis tools and techniques are unable to process of such a large amount of web data effectively and accurately. In addition, given the complexity of web data even using traditional methods to process the relatively small data sets, it is difficult to obtain a noticeable effect. In this context, data and mining are emerging technologies to support the extraction of valuable data from vast amounts of web data. This thesis investigates the benefits of data and web mining for the internet-based weather service companies by finding gaps in the customer’s journey to improve the user experience, and outlining the potential of new business opportunities. A literature review and industry analysis was undertaken to understand the current state of online weather industry and identify the main touch points that impact the user. A case study was conducted to demonstrate research results applying into practice. The final outcomes are possible solutions to improve user experience and a new business model based on data mining to exploit new profit for online weather service companies.