Customer Segmentation - Data Mining Techniques in CRM: Inside Customer Segmentation - page 218

Table 5.5 Profitability factors in banking.

Factor Description MARPU contribution

Margin The difference between the interest

gained and the interest expense

+

Funding credit The amount earned by banks on the

deposits employed

+

Cost of funds Amount of interest expense paid for

the funds used by banks

−

Loan loss provision The amount reserved by banks to

cover expected loan losses

−

Capital charge The capital allocated multiplied by

rate of return

−

Overhead The fixed and variable expenses

associated with the product
(e.g., transactional)

−

The tasks of this phase also include selection of the segmentation population
and level as well as selection of the value cut-points that will be used to divide
customers, for example, top 1%, high 19%, medium 40%, low 40%.

Data Understanding and Preparation - Calculation of the Value Measure

Data understanding includes a thorough investigation of the availability of the
required data components and the detection of possible problems that may
be encountered due to missing information. After that, all relevant customer
information should be consolidated, evaluated in terms of quality, cleaned, and
prepared for calculating a credible value measure. This phase ends with the
development of an accurate and valid formula for quantifying the customers'
value. The calculation should use input data that cover a sufficient period of
time, at least six months, so that it accurately summarizes the value of each
customer.

Grouping Customers According to Their Value

There is no modeling phase in value-based segmentation. Instead of modeling, this
segmentation type requires simple computations for the calculation of a credible
value measure and the use of this measure to divide customers accordingly.
Customers are sorted according to the calculated value measure and binned
in groups of equal size, named quantiles, such as tiles of 1% (percentiles) or tiles of
10% (deciles). For instance, the partitioning in deciles would result in 10 groups of