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Intelligent Data Mining

Intelligent data mining depends on knowing the behavior of the variables that make up each record in the database. A Univariate, Bivariate, and Multivari are techniques both Tabular and Graphical. Once the data is well understood, modeling will begin. If there is a stable and robust response variable present, then a Logistic Regression or other kind of model is a logical next step, depending on the modeling objective and the available response variable(s). Modeling efforts may result in:

  • Response Models and Revenue/Profit Models
  • Retention/Loyalty/Persistency Models
  • Lifetime Value Models

In the event where marketing history is not available for a given Product or Product Class, latent variable Analysis,(an extension of exploratory analysis) can also be used to generate a propensity model.