Business-Driven Data Mining: New Algorithms and Applications
PhD thesis by: Alex Seret (2015), KU LEUVEN
The explosive growth of the amount of available data and the reliance on data mining techniques have led to the creation of a myriad of new business models and opportunities. The field of direct marketing is not an exception and explores ways of getting competitive advantages by supporting research on the development of innovative and value- adding techniques.
Although data mining techniques have been successfully applied in different companies (often big companies), it is still difficult for smaller organizations to monetize or at least explore the data they collected. From this perspective, a need for comprehensible stepwise business-oriented exploration techniques can be identified. In the re- mainder of this document, different approaches applied on cases with such smaller companies or departments are presented and discussed. The focus of this thesis is on providing the business with business- oriented, comprehensible, step-wise and visual exploration techniques and methodologies. Since the step-wise aspect of the approaches pre- sented in this work is of a crucial importance for business acceptance reasons, some of the techniques are reused and re-discussed in different chapters.