Moving the customer experience field forward : introducing the Touchpoints, Context, Qualities (TCQ) nomenclature

In response to initial voices that put the customer experience (management) (CX(M)) movement into question, this article aims to introduce a formal nomenclature to push the CX(M) field toward a more mature state. First, drawing from an inductive analysis of 143 CX(M) papers, the authors identify 12 basic CX components that aggregate into three overarching building blocks-touchpoints (T, i.e., points of interaction between the customer and brand/firm), context (C, i.e., situationally available resources internal and/or external to the customer), and qualities (Q, i.e., attributes that reflect the nature of customer responses and reactions to interactions with the brand/firm). The TCQ nomenclature offers a language to make CX actionable, moving beyond the breadth of the current definition and frameworks by disentangling CX into small bite-sized chunks (i.e., the CX components) that any academic and practitioner, regardless of their discipline, may understand and use to discuss and manage CX. Second, using the TCQ nomenclature, the authors assess the current state of the CX(M) literature and identify mature (e.g., firm-controlled touchpoints and cognitive and emotional qualities associated with CX) and underdeveloped (e.g., nonfirm controlled touchpoints and the market and environmental context in which CX emerges) areas ripe for future research. In addition, they also provide a set of recommendations to strengthen the methodological rigor of the field. Third, the TCQ nomenclature may support managers in auditing their current CXM practices and/or serve as a basis for CX design and innovation

Customer Experience Driven Business Model Innovation

Business model innovation (BMI) is critical to a firm's ability to achieve growth and long-term viability. It helps improve the value of products or services and/or delivery of these offerings to customers. Much of the academic literature to date however lacks customer-driven business model innovation frameworks. As such, the aim of this investigation is to propose a customer experience driven (CX) business model innovation framework that aligns customer values and the firm's strategic needs. This paper contributes to the literature by (a) conceptualizing the way in which business model innovation and customer experience are related (b) providing managers with a concrete framework to guide business model innovation that supports customer experience-driven new services and (c) highlighting opportunities for future research to advance business model innovation research and practice

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

Does satisfaction matter more if a multichannel customer is also a multicompany customer?

Purpose - This research aims to investigate the moderating influence of both multichannel and multicompany usage on the impact that customer satisfaction has on share of wallet (SOW). Design/methodology/approach - The data used in the analyses were collected as part of both survey and transactional data of 802 households of a large financial services provider. Within class regression models were employed to test the moderating effects of different segments that were identified based on multichannel-multicompany customer differences. Findings - The findings confirm that using multiple channels has an overall positive moderating impact on the satisfaction-SOW link and that customer satisfaction matters more when the customer adopts multiple channels; online channel usage in addition to offline usage. Furthermore, this effect is even more pronounced for customers that transact with multiple providers. That is, the group of customers that use both the company's and competitors' offline and online channels reveal a higher satisfaction-SOW association than the group of customers that only adopted the offline channel with the company and competitor. Originality/value - This study broadens the understanding of multichannel behavior by comparing single (offline) and multiple channels (offline and online) for customers of multiple companies (two competitors)

Bridging the data divide between practitioners and academics: Approaches to collaborating better to leverage each other's resources

Purpose – Organizations (data gatherers in the context) drown in data while at the same time seeking managerially relevant insights. Academics (data hunters) have to deal with decreasing respondent participation and escalating costs of data collection while at the same time seeking to increase the managerial relevance of their research. The purpose of this paper is to provide a framework on how, managers and academics can collaborate better to leverage each other’s resources. Design/methodology/approach – This research synthesizes the academic and the managerial literature on the realities and priorities of practitioners and academics with regard to data. Based on the literature, reflections from the world’s leading service research centers, and the authors’ own experiences, the authors develop recommendations on how to collaborate in research. Findings – Four dimensions of different data realities and priorities were identified: research problem, research resources, research process and research outcome. In total, 26 recommendations are presented that aim to equip academics to leverage the potential of corporate data for research purposes and to help managers to leverage research results for their business. Research limitations/implications – This paper argues that both practitioners and academics have a lot to gain from collaborating by exchanging corporate data for scientific approaches and insights. However, the gap between different realities and priorities needs to be bridged when doing so. The paper first identifies data realities and priorities and then develops recommendations on how to best collaborate given these differences. Practical implications – This research has the potential to contribute to managerial practice by informing academics on how to better collaborate with the managerial world and thereby facilitate collaboration and the dissemination of academic research for the benefit of both parties. Originality/value – Whereas the previous literature has primarily examined practitioner–academic collaboration in general, this study is the first to focus specifically on the aspects related to sharing corporate data and to elaborate on academic and corporate objectives with regard to data and insights.This study was partially funded by a grant from the Ministry of Education, Singapore. Project: Service Productivity and Innovation Research, No. MOE2016-SSRTG-059

—Net Promoter, Recommendations, and Business Performance: A Clarification on Morgan and Rego

One of the most controversial findings in Morgan and Rego (2006) was that two widely advocated loyalty metrics, “Net Promoter” and “Number of Recommendations,” have little or no value in predicting the financial outcomes of firms. We argue that neither measure was actually examined and that conclusions about the predictive value of these measures cannot be drawn from their analysis. A primary problem is that the measures used in Morgan and Rego (2006) do not adequately adjust for the presence of neutral word-of-mouth activity. Nevertheless, Morgan and Rego (2006) provide important information regarding other common customer metrics and firm financial outcomes. We are unaware of another longitudinal study that examines the predictive value of satisfaction and loyalty metrics in such a comprehensive way.Net Promoter, word-of-mouth, recommendations, financial performance, intentions, customer satisfaction, customer loyalty