Data mining is an aide to strategic, tactical and operational decision-making in situations where numerous variables, affecting costs or benefits, impinge on the eventual outcome of the course of action that a company might decide to take. The modeling that accompanies data mining assimilates the information on costs and benefits of alternative courses of action as visualized in the form of familiar decision trees. Companies use such information to find new opportunities for growth, choose more effective means to achieve their business goals and streamline business processes to lower their costs.

Customer churn is one of the several examples of complex business problems that data mining addresses. A great deal of marketing activity involves customer acquisition, retention and extension and companies invest considerable resources to achieve this. When all the competing companies in an industry exert themselves to woo customers, churn rates increase and higher costs have to be incurred to attract customers and to keep them. The benefits of attracting customers in the telecommunications industry, for example, depend on the length of time they stay with a company, the number and the duration of their calls. The costs, on the other hand, depend on network costs which are higher if interconnection charges are incurred or more outbound calls take place, time of day for calls, i.e., costs are higher at peak time, customer service support and the duration of calls (shorter calls mean higher costs). None of these variables can be readily estimated at the outset.

Data mining uses statistical techniques, such as survival analysis, to determine the length of time for which a customer can be expected to stay with a company. Based on the profile of groups of customers, as indicated by demographics, psychographics, price sensitivity and knowledge of alternative vendors, the length of their expected stay with a company can be estimated. Similarly, the calling behavior of customers and attendant costs of servicing can be estimated from their profession, personality (introverted or extroverted), social networking behavior. Based on such data, companies can decide on the amount of money they can afford to spend to satisfy customers in order to acquire and retain their customers.

Profiling or segmentation of the customer base is the linchpin of much of the benefits that flow from data mining. The task of profiling consists of identifying homogenous groups of customers who exhibit similar patterns of behavior. Armed with this information, companies learn to target specific customers rather than randomly promote products to all of them. Customers are happier because junk mail otherwise inundates them and is aggravating. Companies don't have to drain their resources by sending mailers to customers who are often so indifferent that they toss an offer into a waste paper basket.

Customer segmentation is also a source of innovation such as in the design of insurance plans in the health industry. In the past, customers had access to only two broad types of insurance plans; the HMO and the PPO. The prices paid by customers have been uniform regardless of their actual use of health services. Consequently, customers are less responsible about their lifestyles choices such as smoking, weight, diet and exercise. Worse, responsible customers, who invest in preventive care, by spending on yoga, alternative care, are not rewarded. As a result, health care costs have been rising rapidly without a commensurate improvement in quality. In recent years, however, companies such as WellPoint Health Networks Inc., PacifiCare Health Systems Inc. and Blue Shield of California consumer driven health plans have started to offer health insurance plans tailored to the risk profile of customers. Consumers are allowed to choose their price points and the benefits they receive and are provided information on the web to make a choice of their doctors. This is expected to lower waste in the health industry and encourage preventive care and patients would have a choice to spend on alternative care.

In general, profiling and segmentation of customers helps companies to efficiently align resources with the specific needs of customers. They can set prices, choose channels and design communication strategies based on the character of specific segments of customers.

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