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. [...]
[...] Data warehousing and data mining can help this process, but it is by no means a solution to all of the problems associated with customer acquisition. Deciding what is an interesting offer is where the art of marketing comes in INTRODUCTION A data warehouse is a repository of an organization's electronically stored data. Data warehouses are designed to facilitate reporting and analysis. If operational data is kept in the databases it can create a lot of problems. As time passes the amount of data will increase and this will affect the performance of the system. [...]
[...] Typical patterns that data mining uncovers include which customers are most likely to drop a service, which are likely to purchase merchandise or services, and which are most likely to respond to a particular offer. The data mining process results in the creation of a model. A model embodies the discovered patterns and can be used to make predictions for Frequently, the data to be mined is first extracted from an enterprise data warehouse into a data mining database or data mart (Fig. [...]
[...] Existing channels such as the Internet or outbound telemarketing also allow you to be more specific in the ways you target the exact wants and needs of your prospective customers. A significant drawback of the modeling of individual response behaviors is that the analytical processing power required can grow dramatically because the data mining process needs to be carried out multiple times, once for each response behavior that you are interested in. V. Once the data has been prepared, the actual data mining can be performed. [...]
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