International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 12, No. 4, 8 Aug. 2020
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Designing a Real-Time Data-Driven Customer Churn Risk Indicator for Subscription Commerce
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Author(s)
Index Terms
Churn prediction, Customer relationship management, Prototype algorithm, Purchase transaction data, Conversion rate.
Abstract
One of the main goals of customer relationship management is to reduce or eliminate “customer churn”, i.e. loss of existing customers. This paper introduces a prototype algorithm to estimate a continuously updated indicator of the probability of an existing customer to cease purchasing from a subscription commerce business. The investigation is focused on the case of repeat consumers of subscription commerce products which require regular replacement or replenishment. The motivation is to help marketers to make targeted proactive retention actions by categorizing regular customers into groups of similar estimated churn risk. The proposed algorithm re-computes the probability of churn for each customer at regular intervals using past purchase transaction data and incorporating subscription-based business logic. We describe the detailed process from data collection and feature engineering to the algorithm’s design. We also present evaluation results of the algorithm’s performance based on a pilot test that took place on a consumables e-commerce business. The results suggest a significant capability of the proposed algorithm in capturing the purchasing intentions of repeat customers, regardless of the risk group they belong to.
Cite This Paper
Alexandros Deligiannis, Charalampos Argyriou, "Designing a Real-Time Data-Driven Customer Churn Risk Indicator for Subscription Commerce", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.12, No.4, pp. 1-14, 2020. DOI:10.5815/ijieeb.2020.04.01
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