Using Customer Analytics to Build the Success of the Customer-Strategy Enterprise
Progress might have been all right once but it has gone on too long.
To the customer-centric enterprise, data about individual customers are like gold nuggets that, if collected and used effectively, can increase the value of the customer base significantly. Data mining is a frequently used term for the process of extracting useful nuggets of information from a vast database of customer information; but as the relationship revolution has taken hold, the data-mining process itself has also undergone an important transformation. In the pre-interactive age, data-mining techniques were used to uncover information about the types of customers to whom particular offers should be made, answering the question: Who is the next most likely customer to buy this product? Today, the question asked by companies engaged in managing ongoing, interactive relationships with individual customers is: What is the next most likely product that this particular customer will want to buy? As we saw in the last chapter, rather than optimizing around each product, the customer-strategy enterprise needs to optimize around the customer.
In truth, both product optimization and customer optimization have roles to play in any competitive enterprise’s efforts to get, keep, and grow customers. But in the interactive age, much more so than in the past, individual customer information drives the central engine ...