Customer-Base Valuation in a Contractual Setting: The Perils of Ignoring Heterogeneity

Abstract

The past few years have seen increasing interest in taking the notion of customer lifetime value (CLV) and extending it to value a customer base (with subsequent links to corporate valuation). The application of standard textbook discussions of CLV leads to calculations based on a single retention rate. However, at the cohort level, retention rates typically increase over time. It has been suggested that these observed dynamics are due, in large part, to a sorting effect in a heterogeneous population. We show that failing to recognize these dynamics yields a downward-biased estimate of the residual value of the customer base (compared to an aggregate analysis that ignores these dynamics). We also explore the implications of failing to account for retention dynamics when computing retention elasticities and find that the frequently reported values underestimate the true effect of increases in underlying retention rates in a heterogeneous world.customer lifetime value, shifted-beta-geometric, retention elasticity

Deterministic and stochastic Customer Lifetime Value models. Evaluating the impact of ignored heterogeneity in non-contractual contexts

“…In their yet unpublished article entitled ' Customer-Base Valuation in a Contractual Setting:The Perils of Ignoring Heterogeneity ' , Fader and Hardie 33 show that models that assume constant retention at cohort or fi rm level are wrong, as typically retention rates that can be constant individually increase over time at aggregate cohort level. In an earlier version of the article, the authors warned managers and researchers not to use such models, and suggested that academics not teach formulae for computing CLV based on them.…”

“…A thorough investigation of the impact of heterogeneity on CLV in contractual settings can be found in the study by Fader and Hardie. 33 They use the two datasets from a previous version of their paper introducing the Shifted Beta Geometric distribution model (Fader and Hardie 34 ) in order to compare the latter with the fi xed retention rate model CLV calculation given in formula 2. In order to extend the investigation of the impact of heterogeneity to non-contractual situations, we use the formula we have derived in Table 4 for computing DERT for a yet-to-be-acquired customer in order to produce lifetime value calculations for a customer dynamic behaviour where buying and ' death ' probabilities are individually constant over time and ' wrongly ' considered homogenous within a cohort.…”

“…Further investigations of heterogeneity effects on long-term expected transactions and customer value can be made for each of the dynamic processes that are combined in the non-contractual settings: the buying process and the death process. A good illustration limited to only to the buying process is given in the study by Fader and Hardie (2006).…”

Modeling Customer Lifetimes with Multiple Causes of Churn

“…Much of the recent research on customer retention has linked retention rates and churn probabilities to forecasts of customer lifetime value (Fader and Hardie 2010), managing customer equity (Rust et al 2004), balancing the allocation of resources among retention and other marketing efforts (Reinartz and Kumar 2003;Reinartz et al 2005), and financial reporting and management (Gupta et al 2004). With an interest in managing retention, influencing it with marketing actions, and understanding the effect of retention on the value of the customer base, the focus has primarily been on when customers terminate a relationship.…”

“…From the perspective of a shareholder of the firm who is evaluating the financial health of the organization, the answer may be "no." The firm's aggregate churn (or retention) rate may be sufficient for assessing the value of the customer base in terms of the stream of discounted revenue that the firm can expect to accrue from the existing customer base (Gupta et al 2004;Fader and Hardie 2010).…”