These programs have been successful in increasing retention rates and have had a significant bottom line impact. While these programs recognize the importance of maintaining customers and creating loyalty, they generally lack a targeting approach. A program that broadly treats the entire customer base is by definition, wasting time and resources against saving unprofitable customers. The key is finding out which individual customers are going to defect, months in advance of their ultimate defection so that effective intervention techniques can be deployed to save these customers. This process can be accomplished through the use of some very sophisticated database mining tools and algorithms.
Database mining is the process of finding the hidden gems locked in an organization's database.
A true data mining expedition is one that is not limited to data queries that are based on a priori suppositions. It is instead a process whereby data are freely exposed to analytical tools that are in capable hands of experienced analysts. Essentially, a profile is developed for each customer's behavior that is premised upon transactional data gathered during accounting, service, marketing, or any other type of interaction. Neural network protocols can then be used to search through customers' transactional data and update their likelihood of defection on the basis of patterns and trends in their transactions. Since all customers are not alike, in order to produce highly accurate predictions of defection, a thorough data-mining endeavor should capitalize on consumer differences and isolate segment specific models.