It is sometimes hard to understand what the results of data mining and modeling analyses are really saying. Marketing managers who don't fully understand sometimes react with skepticism - which is not good, because it can prevent valuable results from being used. But the opposite reaction can be just as harmful. Marketing managers who don't understand the limitations of data mining and modeling can place so much confidence in the results that they select a marketing strategy that is too narrow. Prematurely limiting your marketing options in this way can result in the best strategies being discarded.
Take the case of a motivational segmentation analysis. Understanding what motivates your customers and prospects is key to making each marketing touch a "call to action." Because motivations cannot simply be observed, an effective way to study motivations is with survey-based market research. Using such a survey, a financial services provider might determine that investors can be segmented into several different motivational segments such as thrill seekers, college financiers and retirement savers. Clearly, knowing the correct segment of a prospect could drive whether the appropriate messaging strategy is offers of stock options, mutual funds or annuities.
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