In the Discover phase, customer profiling and segmentation are conducted using a clustering technique. The clustering technique follows Exploratory Data Analysis, applying a group of multivariate techniques to group objects based on the characteristics that they possess. The objects are grouped in such a way that the degree of association between two objects is maximal if they belong to the same group and minimal otherwise.
Generational and Age Cohorts
While both age and generational cohorts can be powerful, generational cohorts have proven to be more powerful than straight age selects, particularly when combined with a strong, generationally-specific creative message. An age cohort is limited to a specific age range, and people would move in and out of the cohort. A generational cohort is a set group of people defined by year of birth. You remain in the same generational cohort throughout your life. The age bands are defined by looking at universal defining events, social norms, and values of the general population during the formative years of pre-adolescence and adolescence.
Predictive vs Descriptive
Segmentation can also be thought of as descriptive or predictive. For example, generational cohorts would be descriptive while High, Medium and Low Value customers would be more predictive. Both are valuable – predictive can drive your target selection while descriptive can drive your creative message. Often the best results come from combining both to create a segmentation matrix – think of a 2 or 3 dimensional Rubik’s cube of combinations of segmentation schemas – for example, a cell might be High Value X Baby Boomers (2 dimensional) or High Value X Baby Boomer X Lapsed Customer (3 dimensional).
Remember, the success of analytics is predicated on data accuracy, competence in relevant methodology and adherence to proven process and approach. Measuring, analyzing and reporting on all relevant program results contribute to the refinement of subsequent marketing initiatives.