al effort on our part. Figure 11-2: Mutually Exclusive Segmentation When it comes to segmentation by more intangible groupings such as attitude, behavior, likes and dislikes, we run into a problem. Many times, some of our customers do not fit very well into any one category. Other times, we end up with segmentation schemes that leave large groups of customers unaligned with any segment. When this happens, we need to be in a position to understand what the real purpose of the segmentation is and be sure that the scheme was appropriately established. Multidimensional Segmentation As long as we are able to limit our segmentation to only one dimension at a time (for example, segmenting customers only by age, or by sex, or by geographic location), the problems of mutual exclusivity and all inclusiveness will not appear. It is easy to accomplish these conditions with only one characteristic to keep track of. eXcellence in Telecommunications The Telco Churn Handbook Unfortunately, simple, one-dimensional segmentation is not all that useful in the real world. Most organizations find that they need segments based on many characteristics and many dimensions. For example, it is not uncommon to find a segmentation scheme that includes age, sex, geography, income, social status, and credit rating in its definition. Once we start adding and combining characteristics, we create segmentation models that usually do not meet these criteria. Problems with Mutual Exclusivity The situation becomes more difficult for the developer of segmentation schemes when we try to integrate less tangible and more descriptive criteria into the formula. As long as our segmentation is based on hard, tangible facts such as age and sex, we have little problem with mutual exclusivity. That is no longer the case when we build segmentation based on concepts such as "young urban professional," "single parent working from home," or "people who like new technologies." With these types of criteria, we tend to create the situations where one person fits easil