Abstract

This paper will show, how the usage of an early-warning system, which has been developed and implemented for a big internet service provider, can detect customer equity potentials respectively risks and how to use this information to launch special customer treatment depending on strategic customer control dimensions in order to increase customer equity. The strategic customer control dimensions are: customer lifetime value, customer lifecycle and customer behaviour types. The development of the customer control dimensions depends on the availability of relevant customer data. Thus, from the huge amount of available customer data, relevant attributes have been selected. In order to reduce complexity and use standardised processes the raw-data is aggregated, for example into clusters. We will demonstrate by means of a real-life example the detection of spatial customer equity risks and the launch of customer equity increasing treatment using the early-warning system in interaction with the mentioned strategic customer control dimensions.KeywordsRegional LevelCustomer Relationship ManagementBusiness RuleCustomer Lifetime ValueCustomer DataThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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