Estimating defection in subscription-type markets with down-sampled representation: Analysis from the scholarly publishing industry

Roberts, Michael; Deza, Ignacio; Ihshaish, Hisham; Zhu, Yanhui

Abstract

We explore the subscription-type market within the context of customer churn, and provide analysis on the business model of such markets, and how these characterise the academic publishing business. The proposed method attempts to provide inference of customer’s likelihood of defection on the basis of a resampled use of provider resources.
We show that this approach can be both accurate as well as uniquely useful in the business-to-business context. The main findings suggest that whilst all predictive models examined, especially ensemble methods, achieve substantially accurate prediction of churn, as far as a year ahead, this can be achieved even when specific behavioural attributes that can be associated to each customer probability to churn are overlooked. We show that modelling churn on the basis of resampling customers’ use of resources over subscription time is a straightforward and valid alternative to handling the complex granularity often associated with timeseries consumption behaviour data.

• Deposit Date: Sep 25, 2023
• Publisher: Elsevier
• Public URL: https://uwe-repository.worktribe.com/output/11138317