Data Mining in CRM - Data Mining Techniques in CRM: Inside Customer Segmentation - page 12

limitations. The business objective should be translated into a data mining
goal. Success criteria should be defined and a project plan should be developed.
2. Data understanding: This phase involves considering the data requirements
for properly addressing the defined goal and an investigation of the availability
of the required data. This phase also includes initial data collection and
exploration with summary statistics and visualization tools to understand the
data and identify potential problems in availability and quality.
3. Data preparation: The data to be used should be identified, selected, and
prepared for inclusion in the data mining model. This phase involves the
acquisition, integration, and formatting of the data according to the needs
of the project. The consolidated data should then be ''cleaned'' and properly
transformed according to the requirements of the algorithm to be applied. New
fields such as sums, averages, ratios, flags, and so on should be derived from
the raw fields to enrich customer information, to better summarize customer
characteristics, and therefore to enhance the performance of the models.
4. Modeling: The processed data are then used for model training. Analysts
should select the appropriate modeling technique for the particular business
objective. Before the training of the models and especially in the case of
predictive modeling, the modeling dataset should be partitioned so that the
model's performance is evaluated on a separate dataset. This phase involves
the examination of alternative modeling algorithms and parameter settings and
a comparison of their fit and performance in order to find the one that yields
the best results. Based on an initial evaluation of the model results, the model
settings can be revised and fine tuned.
5. Evaluation: The generated models are then formally evaluated not only in
terms of technical measures but also, more importantly, in the context of
the business success criteria set out in the business understanding phase.
The project team should decide whether the results of a given model properly
address the initial business objectives. If so, this model is approved and prepared
for deployment.
6. Deployment: The project's findings and conclusions are summarized in a
report, but this is hardly the end of the project. Even the best model will
turn out to be a business failure if its results are not deployed and integrated
into the organization's everyday marketing operations. A procedure should be
designed and developed to enable the scoring of customers and the updating
of the results. The deployment procedure should also enable the distribution
of the model results throughout the enterprise and their incorporation in the
organization's databases and operational CRM system. Finally, a maintenance
plan should be designed and the whole process should be reviewed. Lessons
learned should be taken into account and the next steps should be planned.