F. Javier Sese

How to Make Switching Costly The Role of Marketing and Relationship Characteristics

Customer switching costs have emerged as one of the fundamental drivers of customer retention. Although the consequences of these costs have been well documented in the literature, research on the determinants of switching costs remains limited. The present study seeks to address this issue by investigating the extent to which switching costs are influenced by marketing variables—price and advertising—and relationship characteristics. The authors develop a conceptual framework about the drivers of switching costs and test the framework empirically in the mobile phone industry using a hierarchical Bayes approach. The empirical results show that by using price and advertising—both service and brand advertising—firms are able to make switching costly for customers. Moreover, relationship characteristics significantly contribute to explaining consumers’ differences in the cost of switching. Finally, this study illustrates the key role played by competitors’ marketing actions in affecting the cost of switching for customers of the focal firm. Implications for decision makers are discussed.

Recasting the customer experience in today's omnichannel environment

Omni-channel marketing refers to the synergetic management of the available channels and customer touchpoints to enhance the customer experience and improve performance. It has become a cornerstone of marketing strategy but putting it into practice is still one of the major challenges that firms face today. In this study, we aim to understand how firms can manage all touchpoints across all channels in an integrated manner to provide a superior customer experience and gain competitive edge. To do so, we identify a number of key issues that firms must consider before they can embrace the changes that their organizations need to recast the customer experience and obtain superior performance. These include adopting a customer-centric approach, unifying all touchpoints across all channels, delivering personalized customer experiences, integrating the available channels, delight customers across channels, redefining the role of the physical store and embracing mobile marketing.

Strengthening Customer Relationships What Factors Influence Customers to Migrate to Contracts

Building long-term, profitable, customer relationships has become a strategic mandate for service firms. In this research, the authors present a modeling framework for understanding the decision of a noncontractual customer to strengthen the relationship with the firm by migrating to a contractual relationship. Drawing upon expected utility theory, the customer migration decision is modeled as a function of expected gains (actual expectations of service usage) and losses (price of the noncontractual service). In addition, the authors investigate the direct and indirect effects of the age of the noncontractual relationship and propose a model to understand the process of expectations formation. The framework is tested empirically in a business-to-consumer context in mobile communications services. The findings provide strong support for the proposed model and they reveal that actual expected service usage and noncontractual price increase the probability of the customer migrating to a contract, and that relationship age has both direct (positive) and indirect (through expected service usage) effects on the studied behavior. The present study also provides new theoretical and empirical insights into the formation of actual customer usage expectations. Finally, the study findings have several important implications for service managers to strengthen their relationships with their current noncontractual customers. For example, they need to proactively manage customers’ actual expectations about future service usage in order to increase a customer’s probability to migrate to a contract.

Does the Nature of the Interaction Matter? Understanding Customer Channel Choice for Purchases and Communications

Managing the increasing number and complexity of customer-initiated interactions across multiple channels consistently and effectively has become a key priority for marketing academics and practitioners. To achieve this, it is imperative that marketers understand how and why customers choose the available channels. In this study, we distinguish between two types of interactions, purchases and communications, and argue that the nature of these interactions influences the way customers behave in the presence of multiple channels. Drawing upon perceived risk research, this study develops an integrated conceptual framework that provides a theoretical understanding of customer channel choice for these interactions. The framework is tested empirically in financial services and the results reveal that channel choices significantly differ for purchases and communications. Channel choices for purchases are more inertial and more strongly affected by attitudes (i.e., relationship quality) than for communications. At the same time, preference for a personal touch in channel choice is more pronounced for purchases than for communications, and marketing activities are more effective at driving channel choice for communications. These results offer some recommendations for managing interactions across channels more effectively. For example, the use of personal channels is advised for managing high-risk interactions (i.e., purchases), while for low-risk interactions (i.e., communications), firms can use marketing activities to migrate customers to cheaper channels.

Network Effects in the Mobile Communications Industry: An Overview

Information technology (IT) markets, in general, and mobile telecommunications, in particular, represent a large and growing portion of today’s economy. They are one of the main sources of economic growth in modern economies (Greenspan 2000) and provide the basis for the development of a knowledge-centric world. The rapid development of these markets and the central role that they play in the economy have attracted the attention of a large number of researchers who have shifted their emphasis from traditional markets to the so-called New Economy. When dealing with these markets, however, it is important to understand that they are governed by a unique set of characteristics that may render wellestablished principles and managerial practices invalid (Shapiro and Varian 1998). One of the most significant distinctive features of these markets is the central role played by the network of users. In IT markets, customers derive utility not only from the product/service itself, but also from the networks surrounding these products (Frels, Shervani, and Srivastava 2003). This is because the installed base of users offers benefits to existing and potential customers in the form of reduced uncertainty, compatibility, the transfer of technical and non-technical information between members of the network and the increased availability and quality of complements, among others (Farrell and Klemperer 2007). This feature explains why IT markets are frequently referred to as network markets (Shankar and Bayus, 2003; Tanriverdi and Lee, 2008). Mobile communications, video games and software are just three examples of businesses where network effects drive market competition and consumer behavior. The network of users becomes a central strategic asset for assessing the firm’s current and future competitive position (Shankar and Bayus 2003; McIntyre and Subramaniam 2009) and, as a result, the understanding of network effects has become a top priority for researchers and practitioners alike. The previous discussion can help explain why network effects have emerged as a trendy topic in recent years in economics and management literatures. This research stream focuses on understanding how network effects alter the way in which firms compete. This increasing interest is due to the evidence that network industries seem to challenge much of

Customer‐Base Management in Network Industries: The Moderating Role of Network Size and Market Growth

The study of network industries has emerged as an important research theme. In these markets, the customer base is a critical strategic asset for assessing the firms current and future competitive position. To manage the customer base optimally in these industries, it is crucial to understand the key drivers of customer acquisition and retention. In this study, we integrate strategic and customer management research and provide a framework to understand the direct role of price and the moderating influences of two central characteristics of network markets, namely, network size and market growth, on a firms ability to acquire and retain customers. The proposed framework is empirically tested in the European mobile communications industry using a longitudinal panel that contains information (quarterly data during 1998 to 2008) for 65 companies in 19 European markets. Our findings offer mixed support for the proposed framework as they reveal that, while network size and market growth do moderate the effect of price on customer acquisition, they only exert a direct influence on customer retention.

Multi-tier Loyalty Programs to Stimulate Customer Engagement

Customers differ in their purchase behavior, profitability, attitude toward the firm, and so on. These differences between customers have led to numerous firms introducing multi-tier loyalty programs. A multi-tier loyalty program explicitly distinguishes between customers by means of hierarchical tiers (e.g. Silver, Gold, Platinum) and assigns customers to different tiers based on their past purchase behavior. Next, customers in different tiers are provided varying levels of tangible rewards and intangible benefits, which are potentially powerful instruments to stimulate customer engagement. In this chapter, we focus on the design and effectiveness of such multi-tier loyalty programs. Building on loyalty program and customer prioritization research, we discuss whether, why, and how multi-tier loyalty programs are effective (or not) in influencing customer behavior, thereby enhancing customer engagement and financial performance.

Customer value co-creation over the relationship life cycle

Purpose Drawing from the theory of relationship dynamics, the purpose of this paper is to investigate how the relationship life cycle moderates the link between relationship quality and customer value co-creation. As customer-firm relationships pass through different stages (exploration, buildup, maturity, and decline) characterized by distinct customer behaviors, this study proposes a dynamic conceptual framework. Design/methodology/approach A questionnaire was administered in financial services firms. The final valid sample comprised 2,000 individuals. Subjective customer information from the questionnaire was combined with objective data that the financial entity provided. Findings The results demonstrate that the relationship life cycle plays a key moderating role, revealing that, in the buildup and maturity stages, the influence of relationship quality on customer value co-creation is stronger than in the decline stage. However, for customers in the exploration stage, relationship quality does not lead to customer value co-creation behaviors. Practical implications As customer relationship stages are constantly evolving, this study provides companies with additional interesting tools to personalize business strategies and to adapt marketing investments to the specific situation of customers. Originality/value To the authors’ knowledge, this is the first study to consider how the relationship life cycle influences the strength with which relationship quality promotes customer value co-creation.

Online customer-initiated contacts and the development of profitable relationships

Abstract Recent advances in technology have profoundly impacted the way firms interact and transact with current and prospective customers. The emergence of online channels has been of particular relevance, as it promotes consumers’ active participation in the value-creation process. In this study, we draw from the Stimulus-Organism-Response model to provide a theoretical understanding of the role played by two critical factors driving online customer-initiated contacts (OnCICs): social effects and perceived risk. Additionally, we establish a direct link between these interactions and customer profitability. We merge longitudinal objective data with subjective data for a sample of 1990 customers in financial services and apply partial least squares, revealing that social effects influence perceived risk. Perceived risk consequently promotes the development of OnCICs, while social effects reduce the need for such interactions. Finally, OnCICs help to promote high-quality relationships and leads to higher performance. Implications for theory and management are discussed.