Data Mining Techniques in CRM


The Mining Data Mart


The success of a data mining project strongly depends on the breadth and quality of the available data. That is why the data preparation phase is typically the most time-consuming phase of the project. In the following sections we will deal with the issues of selecting, preparing, and organizing data for data mining purposes.

Data mining applications should not be considered as one-off projects but rather as continuous processes, integrated into the organization’s marketing strategy. Data mining has to be “operationalized.” Derived results should be made available to marketers to guide them in their everyday marketing activities. The results should also be loaded into the organization’s front-line systems in order to enable “personalized” customer handling. This approach requires the setting up of well-organized data mining procedures, designed to serve specific business goals, instead of occasional attempts which just aim to cover sporadic needs.

In order to achieve this and become a “predictive enterprise” an organization should focus on the data to be mined. Since the goal is to turn data into actionable knowledge, a vital step in this “mining quest” is to build the appropriate data infrastructure. Ad hoc data extraction and queries which just provide answers to a particular business problem may soon end up as a huge mess of unstructured information. The proposed approach is ...

Get Data Mining Techniques in CRM now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.