Modeling Customer Lifetimes with Multiple Causes of Churn

Customer retention and customer churn are key metrics of interest to marketers, but little attention has been placed on linking the different reasons for which customers churn to their value to a contractual service provider. In this paper, we put forth a hierarchical competing-risk model to jointly model when customers choose to terminate their service and why. Some of these reasons for churn can be influenced by the firm (e.g., service problems or price–value trade-offs), but others are uncontrollable (e.g., customer relocation and death). Using this framework, we demonstrate that the impact of a firm's efforts to reduce customer churn for controllable reasons is mitigated by the prevalence of uncontrollable ones, resulting in a “damper effect” on the return from a firm's retention marketing efforts. We use data from a provider of land-based telecommunication services to demonstrate how the competing-risk model can be used to derive a measure of the incremental customer value that a firm can expect to accrue through its efforts to delay churn, taking this damper effect into account. In addition to varying across customers based on geodemographic information, the magnitude of the damper effect depends on a customer's tenure to date. We discuss how our framework can be used to tailor the firm's retention strategy to individual customers, both in terms of which customers to target and when retention efforts should be deployed

The interplay of customer experience and commitment

Purpose This research aims to better understand customer experience, as it relates to customer commitment and provides a framework for future research into the intersection of these emerging streams of research. Design/methodology/approach This research contributes to theoretical and practical perspectives on customer experience and its measurement by integrating extant literature with customer commitment and customer satisfaction literature. Findings The breadth of the domains that encompass customer experience – cognitive, emotional, physical, sensorial and social – makes simplistic metrics impossible for gauging the entirety of customers’ experiences. These findings provide strong support of the need for new research into customer experience and customer commitment. Practical implications Given the complexity of customer experience, managers are unlikely to track and manage all relevant elements of the concept. This research provides a framework identifying empirically the most salient attributes of customer experience with particular emphasis on those elements that enhance commitment. This offers insight into service design to correspond with specific commitment and experience dimensions. Originality/value This research is the first to examine the customer experience as it relates to customer commitment – a key factor in customer loyalty, positive word of mouth and other desired outcomes for managers and marketers. This paper provides a framework for future research into these emerging topics. </jats:sec

Linking Brand Equity to Customer Equity

equity and brand equity are two of the most important topics to academic researchers and practition-ers. As part of the 2005 Thought Leaders Conference held at the University of Connecticut, the authors were asked to review what was known and not known about the relationship between brand equity and customer equity. During their discussions, it became clear that whereas two distinct research streams have emerged and there are distinct differences, the concepts are also highly related. It also became clear that whereas the focus of both brand equity and customer equity research has been on the end consumer, there is a need for research to understand the intermediary’s perspective (e.g., the value of the brand to the retailer and the value of a customer to a retailer) and the consumer’s perspective (e.g., the value of the brand versus the value of the retailer). This article represents general conclusions from the authors ’ discussion and suggests a modeling approach that could be used to investigate linkages between brand equity and customer equity as well as a modeling approach to determine the value of the manufacturer to a retailer

The effects of customer equity drivers on loyalty across services industries and firms

Customer equity drivers (CEDs)—value equity, brand equity, and relationship equity—positively affect loyalty intentions, but this effect varies across industries and firms. We empirically examine potential industry and firm characteristics that explain why the CEDs–loyalty link varies across services industries and firms in the Netherlands. The results show that (1) some previously assumed industry and firm characteristics have moderating effects while others do not and (2) firm-level advertising expenditures constitute the most crucial moderator because they influence all three loyalty strategies (significant for value equity and brand equity; marginally significant for relationship equity), while three industry contexts (i.e., innovative markets, visibility to others, and complexity of purchase decisions) each influence two of the three loyalty strategies. Our results clearly show that specific industry and firm characteristics affect the effectiveness of specific loyalty strategies

A Longitudinal Analysis of Customer Satisfaction, Relationship Commitment Dimensions, and Triggers on Share of Wallet

The overwhelming majority of research in marketing has treated commitment as a one or two dimensional construct and largely disregarded temporal effects when investigating the relationship between satisfaction, commitment and customer loyalty. This under-specification of the commitment construct and cross-sectional nature of studies has the potential to misrepresent these relationships. This research uses a three-component model of commitment (affective, calculative, normative) and situational triggers to examine their impact on customers’ share of wallet (SOW). The data consists of 269 households whose banking relationships were tracked for two years. The results showed that changes in affective, calculative and normative commitment each have a significant positive association with change in share of wallet when one adjusts for the effects of customer characteristics such as age and tenure with company. The baseline level of calculative commitment, and changes in affective commitment provide the best explanations for changes in SOW, and when this information on commitment is used, contemporaneous changes in satisfaction has no significant incremental value as a predictor for changes in SOW. Finally the analysis reveals a two-segment customer model which demonstrates how managers can be misled if they assume that everyone will react to satisfaction and commitment improvement efforts similarly.Customer Satisfaction, Affective Commitment, Calculative Commitment, Normative Commitment, Share-of-Wallet