Segmentation

Segmentation is a key goal of many service providing companies and is a large component of both my research project and my work with Axtria. Segmentation is the process of dividing up clientele into subgroups based on available characteristics. It has uses that range from identifying prospective donors to targeting ads based on an individual's interests.

Groups can be segmented in a number of ways. Say for example you have a list of prospective donors and a list of past donors with a number of characteristics for each. You may know for both groups things like age, estimated income, connections with the organization, and many other variables. And you also have information on the donations of past donors such as amount given, frequency of gifts and things like this. Segmentation would work by trying to find a correlation between characteristics we care about (donation information) and other information about the donor base so we can know which potential donors would be more probable to donate so that more time can be focused on them.

Another example would be how Netflix uses segmentation. Netflix has an immense user base which they have a variety of information on from age, to categories of interest, to individual media that they found incredible or horrific. Thus, when new people sign up for Netflix and list their interests Netflix pattern matches them toward television shows and movies that they are most likely to enjoy. As customers watch and rate more Netflix has a larger data set and can make better and better suggestions.

Segmentation is but one small tool used in data analysis but it proves very useful when applied to the right circumstances.