Data Mining in CRM - Data Mining Techniques in CRM: Inside Customer Segmentation - page 13

The phases above present strong dependencies and the outcomes of a phase
may lead to revisiting and reviewing the results of preceding phases. The nature
of the process is cyclical since the data mining itself is a never-ending journey and
quest, demanding continuous reassessment and updating of completed tasks in the
context of a rapidly changing business environment.
DATA MINING AND BUSINESS DOMAIN EXPERTISE
The role of data mining models inmarketing is quite new. Although rapidly expand-
ing, data mining is still ''foreign territory'' for many marketers who trust only their
''intuition'' and domain experience. Their segmentation schemes and marketing
campaign lists are created by business rules based on their business knowledge.
Data mining models are not ''threatening'': they cannot substitute or replace
the significant role of domain experts and their business knowledge. These models,
however powerful, cannot effectively work without the active support of business
experts. On the contrary, only when data mining capabilities are complemented
with business expertise can they achieve truly meaningful results. For instance, the
predictive ability of a data mining model can be substantially increased by including
informative inputs with predictive power suggested by persons with experience
in the field. Additionally, the information of existing business rules/scores can
be integrated into a data mining model and contribute to the building of a more
robust and successful result.Moreover, before the actual deployment, model results
should always be evaluated by business experts with respect to their meaning, in
order to minimize the risk of coming up with trivial or unclear findings. Thus,
business domain knowledge can truly help and enrich the data mining results.
On the other hand, data mining models can identify patterns that even the
most experienced business people may have missed. They can help in fine tuning
the existing business rules, and enrich, automate, and standardize judgmental ways
of working which are based on personal perceptions and views. They comprise an
objective, data-driven approach, minimizing subjective decisions and simplifying
time-consuming processes.
In conclusion, the combination of business domain expertise with the power
of data mining models can help organizations gain a competitive advantage in their
efforts to optimize customer management.
SUMMARY
In this chapter we introduced data mining. We presented the main types of data
mining models and a process model, a methodological framework for designing