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The ultimate goal of data mining is to find hidden predictive information from a large amount of data. The data mining process involves using existing information to gain new insights into business activities by applying predictive models, using analysis techniques such as regression, classification, clustering, and association. By extending MicroStrategy’s powerful analytical, query, and reporting capabilities, MicroStrategy Data Mining Services can help organizations use their data to forecast future outcomes. Data Mining Services can be widely used in different industries and business areas, ranging from forecasting future results and customer behavior to classifying customers and estimating risk. A good example is an important area in marketing called campaign management. The goal of campaign management is to reduce the costs of marketing campaigns while increasing the positive response.
First, you gather data about the customers targeted for past campaigns, including information such as their age, gender, income, education, household size, and whether they responded positively or negatively to the campaigns. Next, you develop a MicroStrategy report to generate a result set, which is then analyzed to determine if positive responders shared any factors. Once these predictive factors are identified and a predictive model is developed, a MicroStrategy metric is created that embodies this predictive model. This metric forecasts who is likely to respond positively to similar, future campaigns.
By using this metric in a report, you only need to contact those customers on the narrowed-down list. This lowers your company’s direct marketing costs and increases the effectiveness of the campaign. For details of this example, see Campaign management example (using logistic regression).
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