 Tracking and MeasuringRichard Boire Chapter Chapter 16 in Data Mining for Managers, 2014, pp 133-140 from Palgrave Macmillan Abstract: Abstract Data mining is much more than just technology. It is a step- by-step process resulting in the development and application of a solution. Yet, at the same time, this process should always yield new insights and learning that can be utilized for future campaigns. Besides the development and application of solutions, the data mining process should encompass an ongoing learning environment that provides the means for continuous business improvement. It is this stage of tracking and measurement of results that provides learning and insights for future business initiatives. In fact, leading-edge organizations devote much of their resources and time to this area. Why? Being able to measure and evaluate results as part of an ongoing process provides the insights required for continuous business improvement. However, it is equally important that these results are effectively communicated so that the information and insights are disseminated to a wide audience. The empowerment of more people through increased access to these results simply means that more minds can be focused on building solutions rather than having to rely on only a select few. Keywords: Lorenz Curve; Marketing Campaign; Offer Type; Data Mining Process; Business Initiative (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-1-137-40619-4_16 Ordering information: This item can be ordered from Access Statistics for this chapter More chapters in Palgrave Macmillan Books from Palgrave Macmillan |
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