Customer churn and segmentation

Customer churn and segmentation research examines why customers leave a business, which customers are most valuable over time, and how companies can act on that knowledge before revenue is lost. By combining data mining and machine learning with concepts like customer lifetime value and customer equity, researchers build predictive models that help firms allocate marketing resources more precisely — work that has been especially consequential in telecommunications, where switching costs are low and competition is intense. Central open questions include how to translate churn probability scores into marketing interventions that are both cost-effective and appropriately timed, and how segmentation schemes developed on historical data hold up as customer behavior shifts with new technologies and market conditions.

Works

30,915

Total citations

149,228

Keywords

Customer EquityChurn PredictionData MiningCustomer Lifetime ValueMarketing StrategySegmentation