Resumo

Customer lifetime value and Customer Equity appeared as a central metric for marketing in the last years, especially in a time where marketing accountability is challenged and instigates a more profound marketing-finance interface One latent issue was the possibility of biased estimates that could interfere in the managerial application of the CLV concept, since no study compared the existing models. This study tries to identify core differences on every approach and test them with real data.

This study tries to identify core differences on every approach and test them with real data, the first attempt to inspect for model dependency by a managerial perspective. Can managerial policy be dependent on the model chosen?

Customer lifetime value was defined by Kotler as ‘The present value of the future profit stream expected given a time horizon of transacting with the customer’ (KOTLER, 1974). Customer Equity (CE) was introduced by Blattberg and Deighton (1995) in their paper “Manage marketing by the customer equity test”. CE suffered an important change in its formal definition by the 2000s, when became the sum of all firm’s CLV. The underlying logic is to assume that the firm customer base represents an asset that yields revenues over time, in the same way financial assets do.

Literature review reveals that 56 models of CE or CLV were published between 1974 and 2018, at minimum, within journals indexed by Ebsco and Web of Science. After this first research, we designed criteria to classify the models developed on every study. Real customer data were used to compare models and see through a managerial perspective. Data contained information from a private stock brokerage firm from Brazil, which included historical monthly margins and net deposits from 10,232 customers in the period 2011-2013.

Figure shows that Pfeifer (2011) and Hobane et al. (2002) are the most impacted by margins, followed by Berger and Nasr (1998) and Gupta and Lehmann (2003)*, and finally Gupta and Lehmann (2003). All models showed that, in this case, the marginal impact of retention is higher than margins and discount rate, as expected. Until the rate of 50%, models with infinite projection are impacted by margins in a greater value than retention. The same is not true with finite models, where the retention rate always has more impact.

The research shows that deterministic models converge if retention rates are high, but until 50% decision making can differ depending on what model is used: margin impact will be greater than retention in models with infinite projection. On the other side, models with finite projection will always be more impacted by retention rates. So, the policy of retaining or acquiring new customers can have distinct priorities, which is an issue for managerial policy.

GUPTA, Sunil, LEHMANN, Donald R.; STUART, Jennifer Ames. Valuing Customers, Journal of Marketing Research, v. 4, n.1, 2004, p. 7–18. KUMAR, V. e SHAH, Denish. Expanding the role of Marketing: from Customer Equity to Market Capitalization. Journal of Marketing, v. 73, n. 6, November, 2009, p. 119-136. RUST, Roland T., LEMON, Katherine N.; ZEITHAML, Valarie A. Return on Marketing: Using Customer Equity to Focus Marketing Strategy. Journal of Marketing, v. 68, January, 2004, p. 109–127. KOTLER, Philip. Marketing during periods of shortage. Journal of Marketing, July, 1974.