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The building of a model identifies key characteristics of the target group. The model is created by analysing data where responses are known and creating a formula or set of rules. This model is applied to data containing the same predictor variables but where the response is unknown to produce a set of propensity scores. These cyprus mobile phone numbers scores can be used to select other customers who look most like the responders in the original target group.
The main steps in modelling are outlined below.
Identify the business question
The first step in customer modelling is to specify the business question that we are aiming to model (also called the response variable, independent variable or target variable). This could be as simple as identifying the records that are flagged as your customers or might be far more complex e.g. based on product upgrades or lifetime value criteria.
This article will consider modelling customers/non-customers and refer to “prospects” as those customers identified by the model as having characteristics similar to existing/good customers. Remember, however, that this is just an example of a larger class of analyses. Similarly references to consumers could be extended to businesses when modelling in a Business-to-Business (B2B) environment.