Advancements in technology have made relationship marketing a reality in
recent years. Technologies such as data warehousing, data mining, and
campaign management software have made customer relationship management a
new area where firms can gain a competitive advantage. Particularly
through data mining-the extraction of hidden predictive information from
large databases-organizations can identify valuable customers, predict
future behaviors, and enable firms to make proactive, knowledge-driven
decisions. The automated, future-oriented analyses made possible by data
mining move beyond the analyses of past events typically provided by
history-oriented tools such as decision support systems. Data mining
tools answer business questions that in the past were too time-consuming
to pursue. Yet, it is the answers to these questions make customer
relationship management possible. Various techniques exist among data
mining software, each with their own advantages and challenges for
different types of applications. A particular dichotomy exists between
neural networks and chi-square automated interaction detection (CHAID).
While differing approaches abound in the realm of data mining, the use
of some type of data mining is necessary to accomplish the goals of
today's customer relationship management philosophy.
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