Customer Segmentation - Data Mining Techniques in CRM: Inside Customer Segmentation - page 195

• Classic users: Average voice and SMS usage.
• Youth - SMS users: Heavy SMS users - they prefer using SMS to voice.
• Oldies - basic users: Voice usage only - very low incoming community.
• Inactive: No outgoing usage for a significant time period.
A detailed methodological approach for behavioral segmentation is presented
in ''A Guide for Behavioral Segmentation''.
PROPENSITY-BASED SEGMENTATION
Propensity-based segmentation utilizes the results of classification models such as
churn or cross- and up-selling models. This type of segmentation involves simple
computations and the binning of customers in groups according to their propensity
scores. For instance, customers can be divided into groups of low, medium, and
high churn likelihood as a result of a churn model. Churn models estimate and
assign churn propensity scores to all customers. These scores denote the likelihood
of defection and enable marketers to rank customers according to their churn
risk. When the churn prediction model has been developed, customers are sorted
according to their churn scores. Appropriate threshold values are determined and
customers are assigned to low-, medium-, or high-risk groups according to their
estimated churn likelihood.
Analysts can combine multiple propensity models and scores to create com-
pound segmentation schemes. This procedure typically requires the application
of a clustering model. Once the propensity scores are estimated by the relevant
models, they can be used as inputs fields in the clustering model. As an example let
us consider the case of multiple propensity models that estimate the likely uptake
of the following banking products:
• Savings products
• Investment products
• Credit cards
• Consumer loan
• Mortgage loan.
Cluster analysis can be applied to the respective propensity scores in order
to reveal the segments of customers with similar future needs for specific product
bundles. This approach may provide valuable support in the development of an
optimized product bundling and cross-selling strategy.
Propensity scores and respective segmentations can also be combined with
other standard segmentation schemes such as value-based segments. For instance,