Non-contractual churn prediction using Hierarchical Temporal Memory

2018

Master's thesis Information- and communication technology IKT590 - University of Agder 2018 As markets become more saturated and industry leaders compete over the existing customer base, competitors look for ways to improve customer retention with their customers. It is considered much more expensive to gain a new customer than retaining one, so the industry leaders look for ways in which churn in a customer can be predicted and potentially be avoided by incentivizing the customer to stay. Several of the previously proposed approaches struggle with combining the linearity with the non-linearity that exist within churn analysis and prediction. This emphasizes the need for research into state…