|Rosella Predictive Knowledge & Data Mining|
Why customer segmentation? People with similar attributes tend to display similar patterns in various ways. This fact is particularly important in customer relationship management, marketing, and risk management. For example, people with certain life-styles tend to buy certain-types of products. Promoting products particularly targeted towards the demographic group can lead to successful marketing. In credit and insurance industry, good customer segmentation can lead to minimum exposure to risk involved in credits and insurances. Similarly, in catalog sales, customers can be selectively targeted to reduce marketing cost. Customer segmentation can be used in various ways. Note that customer segmentation is a very important tool for customer lifecycle management - CLM.
Technically speaking, customer segmentation is a process that divides customers into smaller groups called segments. Segments are to be homogeneous within and desirably heterogeneous in between. In another words, customers of the same segments possess the same or similar set of attributes. But customers of different segments have differing sets of attributes. Segmentation process can be very complicated. Therefore, it's best to use advanced analytic tools.
What is your motivation for Customer Segmentation?
This is very important since there are many ways you can segment customers. Without clearly defined motivation, no clear segmentation objectives. Segmentation is meaningless. You need to have clearly defined motivation and objectives to achieve. For example, to optimize profits for campaign marketing, or to monitor customer or market trends, or to manage customer loyalty programs, or to use for customer lifecycle management, and so on. Depending on your motivation, different segmentation techniques are employed. Note that CMSR Data Mining Software provides several segmentation and segment monitoring tools such as decision tree, neural clustering, etc.
Customer Segmentation for Trend Analysis and Forecasting
Timely identification of newly emerging trends is very important to businesses. For example, sales patterns of various customer segments indicate market trends. Upward and downward trends in sales signify new market trends. The same can be applied to loans, mortgages, credits, and so on. Trend analysis and forecasting over well-designed customer segmentation is a powerful tool for monitoring and detecting newly emerging trends. For more, please read Trend Analysis and Forecasting.
Customer Segmentation using Neu