Attitudinal perspectives for predicting churn

Steffen Frank Zorn · Wade Jarvis · Steven Bellman

19 citations0/0 files storedJournal of Research in Interactive Marketing

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Customer churn and segmentation Customer Service Quality and Loyalty Consumer Market Behavior and Pricing

Abstract

Purpose As acquiring new customers is costly, putting effort into satisfying and keeping customers over the long term can improve profitability. Firms usually do not know how each individual customer is feeling at any time (their attitude to the firm), so typically a customer's likelihood of leaving (“churning”) is predicted from behavioural data. The purpose of this paper is to investigate how a firm can add attitudinal variables to these churning models by deriving proxy indicators of satisfaction and commitment from behavioural data. The paper tests whether adding these proxies improved predictions of churning compared to a typical model based on purchasing behaviour (PB). Design/methodology/approach Analysing data from 6,000 regular customers from an Australian digital versatile disc rental company, logistic regression predicted membership termination (i.e. churning=1) versus continuation (=0). A baseline model used three traditional behavioural variables directly linked to members' PB. A second model including proxies for satisfaction and commitment from the customer database was compared against the baseline model to investigate improvement in churn prediction. Findings The most significant predictor of churn is an indicator of commitment: the uncertainty of a customer's commitment, indicated by number of times they changed their subscription plan. Practical implications The more customers change their plan, the more likely they are to quit the relationship with the firm, most likely because they are uncertain about how they can benefit from a long‐term commitment to the firm. Monitoring uncertainty indicators, such as plan changing, allows firms to intervene with special offers for uncertain customers, and, therefore, increase the likelihood of them staying with the firm. Originality/value The paper discusses the use of customer behaviour recorded in databases to identify proxy indicators of attitude before this attitude translates into churning behaviour.

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References

1996The Behavioral Consequences of Service Quality 1999Whence Consumer Loyalty?1999The Different Roles of Satisfaction, Trust, and Commitment in Customer Relationships 1995Why Satisfied Customers Defect 1998A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction 1997Customer delight: Foundations, findings, and managerial insight 2000On the Profitability of Long-Life Customers in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing 2000Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers

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