Customer Segmentation 

Companies today realize that customers are not all the same and each of them may have very different needs and desires when it comes to the use of products and services.  

In customer-focused organizations, segmentation is always the starting point. Segmenting customers based on their likely behavior and potential profitability is the heart of Customer Relationship Management (CRM).

        In today’s competitive business environment, an understanding of customers is more important than ever. Customers are not all the same and have potentially different needs and desires when it comes to the use of products and services.  

         If customers cannot find satisfaction from your company, they will go to your competitor. Some people will buy a BMW for a status symbol, others for durability, and others for resale value. Knowing which customers are buying for which reasons can help in focusing your business and marketing strategy.  

      Once acquired, you need to ensure that you maximize the value of the customer over time. Marketing should be customized to specific segments.

 Data Mining is a high-end approach to customer segmentation. Large computers and advanced techniques are used in industries such as credit card management for complex analysis.    

           The purpose of data mining is to build a mathematical model that represents accurately the attributes of the customer base.  

          Building a data model involves a great deal of time and effort and requires a great deal of expertise. It is not uncommon to have a staff of statisticians spend months building a data model. The problem with data mining is that it is inaccessible to most people, and it can not be designed for time sensitive marketing applications.

 Smaller companies often begin with basic segments and then further refine them as they collect data. By focusing attention on specific sets of customers, needs, preferences, and opportunities can be uncovered.

    Demographic Segmentation

          Many companies use demographic segmentation – segments based on standard demographic measures : age, income, geography, gender, marital status – to divide up their customer base and create marketing programs. Demographic segments tend to be very large. A ten million customer base may have 10 segments. The size of the segments make them less useful because major differences in customer would be overlooked. Customers are interested in many things finding the smaller and finer grained segments is the new challenge.

         The standard response rate for most direct marketing programs is about 2 percent. That’s right 98% of the offers that are made by direct marketers are rejected. The opportunity for the elimination of such waste is vast and can be realized through more focused marketing campaigns dealing with finer segments. Higher response rates will surely follow.      

Getting the right offer to the right group is very important.

 Behavioral Segmentation

Customer segmentation in CRM must begin with an understanding of the following components:

            ·       Revenue generated by the customer

·       The cost of acquiring the customer

·       The cost of retaining the customer

·       The actual profitability from a customer

         Customer information can lead to the identification of high-value customers (those who contribute the majority of profits) and low-value customers (those who actually detract from profits because of extra services they require).

          The difference in the behavior between high-value customers and low-value customers create a useful benchmark for most profitable segment and least profitable segment. Most customers will fall in the middle and form the “normal customer” which is where up sell and cross sell opportunities can be found.  

           For customers who have a low current value and a low potential,  strategies can be put in place that revolve around reducing your costs or transferring service to lower cost channels.