IBM intelligent miner for data and it's application

Abstract

In today's dynamic business environment, successful eiiyanwations must be able to react rapidly to the cfumgats market demands. To do this requires an understanding of all of the factors that have an influence on business, and this in turn requires an ability M monitor these factors and provide the relevant and timely wfonwawn to the appropriate decision makers. As the market is getting more and more competitive m the telecoms industry today, companies realisy thai customers are major assets and their/ecus should be on how to keep and expand their existing customer base. Identifying the characteristics a/customers is the core analysts activity to give a view of customers that can be directly mapped info clear business strategies/or Customer Relationship Management (CRM). By using data mining, it is possible to get the customer segmentation model to identify the groups of customers with the similar characteristics which will help to understand customers. Eventually it will be used as the fundamental of customer analysis and marketing strategy development. Article represents Data mining tools and techniques, which help discover new contexts and hence new things about customers. This example considers the auestion of how to characterize customers using data that are routinely collected about them. It illustrates how to discover customer segments from data rather than having to use subjective business rules w identify the deferent types of customers. To generate the segments was used the daia mining technique of clustering and showed how it is possible to use this technique to map out -where deferent customers are in relation to each other. In this specific example also is shown: how to develop class^ication models that can be deployed around business to classify customers, how classification and prediction can be used to provide the vital information required for targeted marketing campaigns.