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Data Mining Data mining is the extraction of hidden predictive information from large databases. It is a powerful technology with great potential to help companies focus on the most important information in their data warehouses.

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Contents: 1. Introduction ---------------------------------------------------------------------- 2 2. Techniques used in Data Mining -------------------------------------------------- 3 3. Data mining and Customer Relationship Management ---------------------- 4 4. How Data Mining Helps Database Marketing --------------------------------- 4 5. Scoring ----------------------------------------------------------------------------------- 5 6. The Role of Campaign Management Software 5 ----------------------------- 5 7. Increasing Customer Lifetime Value ------------------------------------------- 5 8. Combining Data Mining and Campaign Management ----------------------- 6 9. Data Mining Challenges ---------------------------------------------------------- 6 10. Conclusion ---------------------------------------------------------------------------7 11. References -------------------------------------------------------------------------- 8 Introduction: Data mining is the extraction of hidden predictive information from large databases. It is a powerful technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools are used to predict future trends and behaviors, and allow businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that were traditionally too complex and time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Data mining also helps in linking in different types of data that experts may not think to relate to each other. For example, data mining can help make conclusions like: Men who buy diapers on Fridays also buy beer, so retailers can benefit by displaying beer and diapers close to each other. ...read more.


Businesses have to be very adaptive in their approach to customer relationships; they have to quickly respond to the needs and wants of their customers. Customer relationship management (CRM) is a process that manages the interactions between a company and its customers. The primary users of CRM software applications are database marketers who are looking to automate the process of interacting with customers. To be successful, database marketers must first identify market segments containing customers or prospects with high-profit potential. They then build and execute campaigns that favorably impact the behavior of these individuals. Identifying market segments requires significant data about prospective customers and their buying behaviors. Data mining applications automate the process of searching the humongous amount of data to find patterns/trends that are good predictors of purchasing behaviors. How Data Mining Helps Database Marketing Data mining helps marketing users to target marketing campaigns more accurately; and also to align campaigns more closely with the needs, wants, and attitudes of customers and prospects. If the necessary information exists in a database, the data mining process can model virtually any customer activity. The key is to find patterns relevant to current business problems. ...read more.


Marketers who build campaigns should be able to apply any model logged in the campaign management system to a defined target segment. Data Mining Challenges Limited or inaccurate data- Sufficient information regarding the area that is being analyzed is required to accurately find trends and to make conclusions. Companies who have not been collecting data over a period may face this issue. Changing database - the size of the database grows exponentially in most companies. An abundance of data is a benefit when trying to find trends over a few areas of interest, however, a huge amount of data can also make it more complicated to find trends. Conclusion Data warehousing and business intelligence provide a method for users to anticipate future trends from analyzing past patterns in organizational data. Data mining is more intuitive, allowing for increased insight beyond data warehousing. An implementation of data mining in an organization will serve as a guide to uncovering inherent trends and tendencies in historical information. It will also allow for statistical predictions, groupings and classifications of data. Data mining software allows users to analyze large databases to solve business decision-making problems. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. ...read more.

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