Enterprise

Customer Segmentation
While overall customer satisfaction measurements prove an effective method of gaining valuable consumer insight, often times they are also very limited. Satisfaction metrics most often provide evaluations of customers that are either deemed satisfied or unsatisfied, failing to incorporate all of the varying levels in between the two spectrums. Customer segmentation however, goes the step further by breaking down the varying levels beyond the simplistic satisfied vs. unsatisfied measurements and thus provides opportunity to retain a broader range of a company’s customer base.

What is it exactly?
Customer segmentation places customers that have something in common into smaller subsets. Segmentation can provide a broad look by grouping customers according to one or two similar characteristics, (say region or age) or can provide a more detailed look at specific segments by categorizing customers based on numerous factors (such as region, age, lifestyle, values, brand loyalty, etc). Whatever the case, by grouping customers in such a way, the outcome is being able to provide products / services that will respectively tailor to each segment – a broader range of customers - which is not often the case when a company groups customers based solely on satisfaction or dissatisfaction.

So how are customers grouped?
It is important to group customers in such a way that the segment is still large enough to be profitable. While segments typically share several factors in common, if each segment is too small it becomes difficult to provide any sort of actionable findings.

Segmentation is typically successful when habits or characteristics are consistently shared among customers in their respective segmentation, are easily measurable or identifiable, are distinctly separate from other segments, and are stable over time. Such characteristics can include:

Region of the world or country
Country / City Size
Climate
Age / Gender
Family Size
Education
Income
Occupation
Socioeconomic status
Personality / life style
Values / attitude
Product / service usage
Benefit sought
Brand loyalty

Typically customers are grouped in like segments by utilizing research analysis tools such as cluster analysis, algorithms, or discriminate analysis.

For more information about Customer Segmentation, go to
http://www.quirks.com/articles/a2003/20031109.aspx?searchID=17651416&sort=7&pg=1 http://www.quirks.com/articles/a2003/20031006.aspx?searchID=17651416&sort=7&pg=2