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Data warehousing and data mining: Bringing pinpoint accuracy to sales

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  1. Introduction
  2. Data mining and data warehousing
  3. Relevance to a business process
  4. Conclusion
  5. References

For most businesses, the primary means of growth involves the acquisition of new customers. This could involve finding customers who previously were not aware of your product, were not candidates for purchasing your product, or customers who in the past have bought from your competitors. Some of these customers might have been your customers previously, which could be an advantage or a disadvantage as they might have switched as a result of poor service. The traditional approach to customer acquisition involved a marketing manager developing a combination of mass marketing (magazine advertisements, etc.) and direct marketing (telemarketing, etc.) campaigns based on their knowledge. In the case of traditional direct marketing, customer acquisition is relatively similar to mass marketing. A marketing manager selects the demographics that they are interested in, and then works with a data vendor (service bureau) to obtain lists of customers who meet those characteristics.

[...] If a model does not use some of the overlay variables, you might want to save some money and leave out these unused variables the next time you purchase a prospect list CONCLUSION Data Warehousing and data mining are increasingly popular because of the substantial contribution they can make. They can be used to control costs as well as contribute to revenue increases. Many organizations are using data warehousing and data mining to help manage all phases of the customer life cycle, including acquiring new customers, increasing revenue from existing customers, and retaining good customers. [...]


[...] The operational business software can then feed the results of the decision to the appropriate touch point systems (call centers, direct mail, web servers, email systems, etc.) so that the right customers receive the right offers DATA MINING WAREHOUSING AND DATA Furthermore, you will have already addressed many of the problems of data consolidation and put in place maintenance procedures. The data mining database may be a logical rather than a physical subset of your data warehouse, provided that the data warehouse DBMS can support the additional resource demands of data mining. [...]

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