Reduce Customer Churn Research Articles

Validating Antecedents of Customer Loyalty for Indian Cell Phone Users

The Indian telecom industry is one of the fastest growing in the world and second largest mobile market globally. The Indian cell phone market is characterized by a large subscriber base (545 million connections as on May, 2010, expected to reach 876.6 million in 2013), low average revenue per user (INR 209 as on March 2009) and high churn rates (53.2% in 2009, and is expected to increase to 59.6% in 2013). The Indian consumers are enjoying a wide range of services along with the world�s lowest local call rates. The mobile phone operators in India are faced with the challenge of reducing customer churn in the ever-increasing prepaid subscriber market. Under such circumstances, the success of mobile phone service providers in India mainly depends on developing innovative schemes to increase customer loyalty. In service organizations, customer loyalty is considered as prime determinant of long-term financial performance of firms. One of the crucial issues of today is to understand how or why a sense of loyalty develops in customers. Loyalty definitions and metrics are mostly in behavioural and attitudinal terms. Consensus is absent in the marketing literature on how loyalty should be conceptualized and measured in the service industry. The present study addresses both the conceptual and measurement issues related to customer loyalty amongst the cell phone users. Building on existing literature, the antecedents of customer loyalty are reassessed in a service setting namely, customer satisfaction, trust, commitment, corporate image, and switching costs. This paper reports the development and validation of scales for measuring customer loyalty and its antecedents. The scale development and validation process was divided into three phases. Phase 1 consisted of the item generation process, assessment of content validity, and initial purification of measures. Item analysis and exploratory factor analysis were used on data collected from 250 postgraduate business students of a major university in India for initial purification of the instrument. In Phase 2, additional data were collected from 855 cell phone users in northern India to assess the latent factor structure through confirmatory factor analysis. In Phase 3, the discriminant validity and convergent validity of the measures were established. The managerial implications of the major findings of this study are as follows: It contributes to the existing literature by developing a theory-based framework for understanding the direct effects of satisfaction, trust and commitment, switching costs and corporate image on behavioural and attitudinal loyalty. By measuring loyalty as composite measure consisting of both behavioural loyalty and attitudinal loyalty, it provides evidence of the multidimensional nature of loyalty construct. Using data collected from mobile phone users, the reliability and validity of the scale are established. The newly refined and validated measures can be used by future researchers to study customer loyalty and its antecedent factors. The loyalty measures developed in this study provides managers with an easy tool to identify attitudinal and behavioural differences among customers. Marketing managers can draw meaningful distinctions between customers who buy out of habit and those who buy because of emotional attachment to the company.

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.

Customer asset management at DHL in Asia

Subject area Marketing; customer segmentation; operations and logistics. Study level/applicability Undergraduate business and management students, MBA/MA level application for international marketing modules incorporating customer segmentation and customer asset management. Case overview DHL, the international air express and logistics company, serves a wide range of customers, from global enterprises with sophisticated and high volume supply-chain solutions shipping anything from spare parts to documents, to the occasional customer who ships the odd one or two documents a year. To be able to effectively manage such a diverse customer base, DHL implemented a sophisticated customer segmentation cum loyalty management system. The focus of this system is to assess the profitability from its customers, reduce customer churn, and increase DHL's share of shipments. Expected learning outcomes Case teaching objectives: to demonstrate the concept of customer segmentation with loyalty management as a total system in a logistics company setting, and to evaluate appropriateness of the classification; to utilize the concept of service tier model within the company's current operations, and to evaluate the effectiveness of the model; to analyze the implementation of the customer segmentation cum loyalty management system and development of the necessary rules required to classify the various accounts into categories; to highlight the possible challenges arising from the implementation of customer segmentation cum loyalty management system, and to discuss possible methods of resolution. Supplementary materials Teaching note.

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 article, 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 tradeoffs), but others are uncontrollable (e.g., customer relocation and death). Using data from a provider of land-based telecommunication services, we examine how the relative likelihood to end service due to different reasons shifts during the course of the customer-firm relationship. We then show how the effect of a firm’s efforts to reduce customer churn for controllable reasons are mitigated by presence of uncontrollable ones. The result is a measure of the incremental customer value that a firm can expect to accrue by delaying churn for different reasons. This “upper bound” on the return of retention marketing is always less than what one would estimate from a model with a single cause of churn and depends on a customer’s tenure to date with the firm. We discuss how our framework can be employed to tailor the firm’s retention strategy to individual customers, both in terms of which customers to target and when to focus efforts on reducing which causes of churn.

Customer perceptions and sustained usage of recommender systems

Service firms (e.g., Amazon, Netflix) testify that recommender systems earn repeat purchases, reduce customer churn, and sharpen competitive edges. However, little is known about why customers will keep using a company's recommender system. We conceptualise that customer perceptions of accuracy, benevolence and process value may affect sustained usage. We also explored the roles of preference stability and privacy concerns. We surveyed customers who had used recommender systems. Surprisingly, perceptions of benevolence and process value, rather than accuracy, drive sustained usage behaviour. Results fail to support the effects of preference stability or privacy concerns. Implications for research and businesses are discussed.