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Abstract:
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Most marketers and analysts agree that data mining plays a critical role in assuring a successful campaign. At times, errors, in executing an analytics project can subtly creep in. While analytic and technical errors can certainly harm a data mining exercise, most of the problems that emerge in a predictive modeling project have little to do with technical issues. Rather, basic reasoning, and marketing related issues are at fault. While technical issues can also cause havoc in an analysis, most difficulties and problems emanate from the mundane issues. What is the correct marketing objective? Is the right analysis being applied? Are my files being prepared diligently? Is the sample valid? Are the tools appropriate? Does it make sense? Perhaps these standard issues are not as routine as we think?
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