數(shù)據(jù)挖掘技術(shù)在crm中應(yīng)用外文原文和譯文(編輯修改稿)
2025-08-09 23:28 本頁面
【文章內(nèi)容簡介】 cal CRM is the part of the CRM business strategy that drives increased customer intelligence and makes information actionable across all touchpoints. (Collins 2001) It enpasses a host of data mining applications (., marketing, forecasting and budgeting) that enable panies to develop greater customer intelligence and accordingly customerspecific strategies. Analytical CRM will be the main theme running throughout the research/project. The essence of CRM is understanding customer needs and leveraging that knowledge to improve a pany’s long term profitability. It requires the alignment of three building blocks: insight into customer decisionmaking, information about customers, and informationprocessing capability. (Stringfellow, et el. 2004) Recent developments in Information Technology (IT) have improved the informationprocessing capability dramatically. This along with the increasing availability of customer information, collected internally with continuous transaction records or bought from external sources, has created opportunities as well as challenges for panies to leverage the data and gain petitive advantage. Large amount of customer information is accessible in the databases, however, the knowledge hidden behind the data is not explicit and ready at hand. With respects to these conditions, the need to use data mining tools, which can help uncover the hidden insight of customer behaviours, has been raised.Data mining is the process of searching and analysing data in order to find implicit, but potentially useful, information. It involves selecting, exploring and modelling large amounts of data to uncover previously unknown patterns, and ultimately prehensive information from large databases (Shaw 2001). Data mining can be easily fitted into various business functions. Lets take my MSc summer project for example...... Based on the interplay between potential value and realised value, CRM/marketing managers can devise
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