CRM in Data-Rich Multichannel Retailing Environments: A Review and Future Research Directions

Many retailers have collected large amounts of customer data using, for example, loyalty programs. We provide an overview of the extant literature on customer relationship management (CRM), with a specific focus on retailing. We discuss how retailers can gather customer data and how they can analyze these data to gain useful customer insights. We provide an overview of the methods predicting customer responses and behavior over time. We also discuss the existing knowledge on the application of marketing actions in a CRM context, while providing an in-depth discussion on CRM and firm value. We outline future research directions based on the literature review and retail practice insights.     

Crafting Integrated Multichannel Retailing Strategies

Multichannel retailing is the set of activities involved in selling merchandise or services to consumers through more than one channel. Multichannel retailers dominate today's retail landscape. While there are many benefits of operating multiple channels, these retailers also face many challenges. In this article, we discuss the key issues concerning multichannel retailing, including the motivations and constraints of going multichannel, the challenges of crafting multichannel retailing strategies and opportunities for creating synergies across channels, key retail mix decisions facing multichannel retailers, and the dynamics of multichannel retailing. We synthesize current knowledge drawn from the academic literature and industry practice, and discuss potential directions for future research.     

Customer Experience Creation: Determinants, Dynamics and Management Strategies

Retailers, such as Starbucks and Victoria's Secret, aim to provide customers a great experience across channels. In this paper we provide an overview of the existing literature on customer experience and expand on it to examine the creation of a customer experience from a holistic perspective. We propose a conceptual model, in which we discuss the determinants of customer experience. We explicitly take a dynamic view, in which we argue that prior customer experiences will influence future customer experiences. We discuss the importance of the social environment, self-service technologies and the store brand. Customer experience management is also approached from a strategic perspective by focusing on issues such as how and to what extent an experience-based business can create growth. In each of these areas, we identify and discuss important issues worthy of further research.     

Customer perceived value,satisfaction, and loyalty: the role of willingness to share information

This study proposes and tests an integrative model to examine the relationships among customers’ willingness to share information, satisfaction, perceived value, and loyalty in a retailing context. This study extends research on customers’ willingness to share information from trust and privacy concerns toward key outcome measures such as perceived value, customer satisfaction, and loyalty, and is thus among the first to model customers’ willingness to share information with companies in robust theoretical retailing frameworks. The proposed relationships were tested using data from two retailing contexts – groceries (N = 429) and do-it-yourself (DIY) (N = 895). Findings from the two samples suggest that both perceived value and satisfaction are significant determinants of customers’ willingness to share information with a company. Although some differences emerge in the two studies, structural modeling largely supports the hypothesized framework and positions customers’ willingness to share information as an important antecedent of their loyalty intentions and behavior. This study provides practitioners with preliminary insight into the relationship between willingness to share information and perceived value, customer satisfaction, and customer loyalty. This study advances retailing research, as it is one of the few empirical studies investigating the role of customers’ willingness to share information in driving loyalty and its relationship with perceived value and satisfaction in a retailing context.     

Customer Lifetime Value as the Basis of Customer Segmentation

SUMMARY

In this article, we examine current trends in customer life-time value and customer segmentation models and identify key issues for future research. CLV-based segmentation is a segmentation approach that groups customers into meaningful segments based upon customer lifetime value and (potentially) other factors. In the article, we discuss the extent to which CLV-based segmentation meets the criteria for effective segmentation. We also identify six areas for future research: (1) models and management of “micro-segments,” (2) using CLV-based segmentation to improve the efficiency of marketing programs, (3) the need for more dynamic CLV-based segmentation models, (4) applying CLV-based customer segmentation to new products and new customers, (5) challenges associated with implementing CLV-based segmentation, and (6) the need for new models that enable firms to segment customers by response to marketing activities and CLV at different points in the customer decision process.     

Retailing research: Past,present, and future

The field of retailing has experienced significant changes in recent years. In this article, we review articles published in Journal of Retailing over the 2002–2007 time span, classified into ten broad topic categories: price, promotion, brand/product, service, loyalty, consumer behavior, channel, organizational, Internet, and other. Some areas have received a reasonable amount of attention; others would be worthy of additional work. We summarize a key insight from each article in the Appendix. Finally, we highlight some key insights for each area and some avenues for further research, in the hope that this review spurs additional research into these and other areas of importance to both academicians and retail practitioners.     

How to retain customers in omnichannel retailing: Considering the roles of brand experience and purchase behavior

The opportunities and challenges of omnichannel in retail industry have been widely discussed, yet despite these benefits, the key elements that constitute an effective omnichannel and how customers respond to omnichannel retailing strategies remain unclear. This research conducted online surveys to test the effects of omnichannel elements on various brand experiences and customer retention, considering the moderating role of purchase behavior. The results indicate that omnichannel elements (integration, individualization, and interaction) are generally helpful in retaining customers, through omnichannel elements influence brand experiences differently. In addition, these omnichannel elements have different influences on customer retention due to different purchase behaviors. The findings suggest that retailers can use different omnichannel strategies to attract customers’ purchases and provide insights for practitioners who want to use omnichannel strategies to deliver superior experiences for customers.     

Calculating,creating, and claiming value in business markets: Status and research agenda

A key challenge facing business marketers surrounds developing a deeper understanding of customer needs. We conceptualize that challenge as having three dimensions: calculating, creating, and claiming value. We discuss key problems, new developments and research challenges in each of these three domains and note the desirability for a deeper collaboration between academics and practitioners to address the research challenges.     

Choosing the Right Metrics to Maximize Profitability and Shareholder Value

There is an ever-present need for managers to justify marketing expenditures to the firm. This can only be done when we can establish a direct link between marketing metrics and future customer value and firm performance. In this article, we assess the marketing literature with regard to marketing metrics. Subsequently, we develop a framework that identifies key metrics that firms should focus on that can give a firm a better picture of how they got to where they are now and insights towards how they can continue to grow into the future. We then identify several organizational challenges that need to be addressed in order for firms to build the capabilities of collecting the right data, measuring the right metrics, and linking those metrics to customer value and firm performance. Finally, we offer guidelines for future research with regard to marketing metrics to help firms establish successful marketing strategies, measure marketing effectiveness, and justify marketing expenditures to top management.     

Service integration in omnichannel retailing and its impact on customer experience

Although omnichannel retailing has received considerable attention from scholars and practitioners in recent years, its impacts on customer experience and relationship outcomes remain unclear. Therefore, this study aims to examine the effects of two components of service integration in omnichannel retailing, namely service consistency and service transparency, on customer experience (i.e. flow and perceived privacy risk), and customer loyalty. Flow theory and hyperbolic discounting theory are employed to underpin these relationships. The data was collected using an online survey with 786 useable responses. Our findings indicate that service consistency has a direct and significant impact on flow and perceived risk while only the effect of service transparency on flow is significant. Moreover, both flow and perceived risk are related to customer loyalty to a retailer. Furthermore, it is found that showrooming behaviour and location-based service usage moderate the relationship between service consistency and privacy risk. The findings of the research provide important implications for a retailer regarding the development, implementation and management of omnichannel strategy.     

Machines augmenting entrepreneurs: Opportunities (and threats) at the Nexus of artificial intelligence and entrepreneurship

Artificial intelligence (AI) refers to machines that are trained to perform tasks associated with human intelligence, interpret external data, learn from that external data, and use that learning to flexibly adapt to tasks to achieve specific outcomes. This paper briefly explains AI and looks into the future to highlight some of AI's broader and longer-term societal implications. We propose that AI can be combined with entrepreneurship to represent a super tool. Scholars can research the nexus of AI and entrepreneurship to explore the possibilities of this potential AI-entrepreneurship super tool and hopefully direct its use to productive processes and outcomes. We focus on specific entrepreneurship topics that benefit from AI's augmentation potential and acknowledge implications for entrepreneurship's dark side. We hope this paper stimulates future research at the AI-entrepreneurship nexus.Executive summaryArtificial intelligence (AI) refers to machines that are trained to perform tasks associated with human intelligence, interpret external data, learn from that external data, and use that learning to flexibly adapt to tasks to achieve specific outcomes. Machine learning is the most common form of AI and largely relies on supervised learning—when the machine (i.e., AI) is trained with labels applied by humans. Deep learning and adversarial learning involve training on unlabeled data, or when the machine (via its algorithms) clusters data to reveal underlying patterns.AI is simply a tool. Entrepreneurship is also simply a tool. How they are combined and used will determine their impact on humanity. While researchers have independently developed a greater understanding of entrepreneurship and AI, these two streams of research have primarily run in parallel. To indicate the scope of current and future AI, we provide examples of AI (at different levels of development) for four sectors—customer service, financial, healthcare, and tertiary education. Indeed, experts from industry research and consulting firms suggest many AI-related business opportunities for entrepreneurs to pursue.Further, we elaborate on several of these opportunities, including opportunities to (1) capitalize on the “feeling economy,” (2) redistribute occupational skills in the economy, (3) develop and use new governance mechanisms, (4) keep humans in the loop (i.e., humans as part of the decision making process), (5) expand the role of humans in developing AI systems, and (6) expand the purposes of AI as a tool. After discussing the range of business opportunities that experts suggest will prevail in the economy with AI, we discuss how entrepreneurs can use AI as a tool to help them increase their chances of entrepreneurial success. We focus on four up-and-coming areas for entrepreneurship research: a more interaction-based perspective of (potential) entrepreneurial opportunities, a more activities-based micro-foundation approach to entrepreneurial action, a more cognitively hot perspective of entrepreneurial decision making and action, and a more compassionate and prosocial role of entrepreneurial action. As we discuss each topic, we also suggest opportunities to design an AI system (i.e., entrepreneurs as potential AI designers) to help entrepreneurs (i.e., entrepreneurs as AI users).AI is an exciting development in the technology world. How it transforms markets and societies depends in large part on entrepreneurs. Entrepreneurs can use AI to augment their decisions and actions in pursuing potential opportunities for productive gains. Thus, we discuss entrepreneurs' most critical tasks in developing and managing AI and explore some of the dark-side aspects of AI. Scholars also have a role to play in how entrepreneurs use AI, but this role requires the hard work of theory building, theory elaboration, theory testing, and empirical theorizing. We offer some AI topics that we hope future entrepreneurship research will explore. We hope this paper encourages scholars to consider research at the nexus of AI and entrepreneurship.     

From Multi-Channel Retailing to Omni-Channel Retailing: Introduction to the Special Issue on Multi-Channel Retailing

The world of retailing has changed dramatically in the past decade. The advent of the online channel and new additional digital channels such as mobile channels and social media have changed retail business models, the execution of the retail mix, and shopper behavior. Whereas multi-channel was in vogue in the last decade in retailing, we now observe a move to so-called omni-channel retailing. Omni-channel retailing is taking a broader perspective on channels and how shoppers are influenced and move through channels in their search and buying process. We discuss this development conceptually and subsequently discuss existing research in this multi-channel retailing. We also introduce the articles in this special issue on multi-channel retailing and position these articles in the new omni-channel movement. We end with putting forward a research agenda to further guide future research in this area.     

How do customers meet their needs in in-store and online fashion shopping? A comparative study based on the jobs-to-be-done theory

Understanding customer needs is key for fashion retailers to stay competitive and innovative. Surprisingly, however, extant literature mainly explores customer needs in terms of a garment and its attributes rather than viewing shopping as a problem-solving process to meet customer needs. Moreover, these studies fail to address how customers meet their needs in-store (ISFR) and online fashion retailing (OFR). To fill this research gap, we empirically investigate customers' personal and social needs and how they can be met through the jobs-to-be-done theory. Findings reveal that, beyond the purchase of a garment, customer needs can be fulfilled through different ways, such as smart technology or a person's high interaction with social others in ISFR and the online shop experience or a social linkage without social interaction in OFR. Additionally, our findings offer potential service innovations for fashion retailing managers.     

How Technology is Changing Retail

Retailing is undergoing a remarkable transformation brought by recent advances in technology. In this paper, we provide a deep discussion of and look ahead on how technology is changing retail, starting with a classification of technologies that impact retailing, in particular, in the COVID-19 and beyond world. We discuss different theoretical frameworks or lenses to better understand the role of technology in retailing. We identify and elaborate on the drivers and outcomes of technology adoption by shoppers, retailers, employees, and suppliers. We speculate on future retail scenarios and outline future research avenues on technology and retailing. We close by concluding that technology is not only reshaping retailing, but also allowing retailing to pivot in the face of new and unforeseen circumstances.     

Exploring phygital omnichannel luxury retailing for immersive customer experience: The role of rapport and social engagement

Omnichannel retailing has revolutionized the way retailers create strategies for engaging customers in making purchase decisions. Phygital is a new-age transformative form of omnichannel retailing that emphasizes combining the physical and digital elements, with a particular focus on the human touch to satisfy social and symbolic consumer needs. Extant research has not fully addressed the role of phygital in luxury fashion retail. We explore the research question regarding how human interactions with experienced salespeople add value to the phygital experience. In doing so, we contribute to the luxury marketing literature by addressing the research gap by elucidating the role of phygital functionality in enhancing rapport building, social engagement, and developing trust and commitment, which results in a seamless customer experience, along with enhanced loyalty and patronage. Through 18 in-depth qualitative research interviews conducted with luxury retail managers and senior retail leaders, we provide guidelines to managers and practitioners at retail firms, to create actionable growth-oriented strategies focused on leveraging phygital capabilities.     

Examining consumer food waste through grocery retailers' customer data: Segments and practical implications

Grocery retailers have a large amount of societally relevant data on food purchases in their databases, which they have traditionally used merely for marketing purposes. However, despite the potential, the data have so far been rarely used in sustainability-related research. This study addresses a key sustainability challenge—the reduction of food waste—by using retailers' customer data and a questionnaire. This paper's purpose is to identify and analyse household food waste segments and discuss their actual purchasing behaviour patterns. By doing so, we also illustrate and exemplify the potential use of customer loyalty card data to address global challenges related to food at the consumer level. The study utilizes an extensive data set of food purchases together with a survey of self-reported reasons for food waste in households. Utilizing cluster analysis, Phase 1 identifies six household segments: no food waste; trust in date labels; safety first; occasional wasters; overpurchasers and overpreparers; and family first. These segments differ in their sociodemographic and purchase profiles. In Phase 2, these segments' purchasing behaviour is examined further by applying tree-based methods. This study contributes to food waste research and studies on sustainable retailing. It also has practical implications for how retailers can facilitate household food waste reduction.     

Omni-channel retailing: propositions,examples and solutions

Customers are not passive agents, but intrinsic to the value creation process. Because retailers are the customer’s link to the marketplace they are uniquely placed to develop value co-creation opportunities that give themselves a strategic advantage. Omni-channel retailing is a means to create an advantage by forging deeper customer relationships and potentially developing new markets. Omni-channel retailing can appeal to the heterogeneity in customers’ shopping orientations with the aim of providing a seamless cross-channel experience. However, without a clear strategic purpose, omni-channel initiatives can easily result in unbeneficial – or worse, counterproductive – investments. To address this, the purpose of this paper is to formulate guiding principles to facilitate decision-making with respect to developing an omni-channel marketing strategy. Consequently, two complementary research streams are presented. The first pertains to strategic considerations regarding omni-channel retailing; the second pertains to value co-creation as seen through a service-dominant logic lens. These research streams are then linked to derive five propositions– along with examples and solutions – to assist retailing decision-makers when developing an omni-channel marketing strategy. These propositions underline the importance of viewing channels as value-facilitating resources that should be aligned with the customer’s decision journey.     

Creating customer repurchase intention in Internet retailing: The effects of multiple service events and product type

Internet retailing literature shows that customers׳ experience with a retailer׳s website and order fulfillment separately influence repurchase intention. This study examines these two experiences׳ interactive effects on repurchase intention. Our research model includes a product type as a moderator, because the type of product can likewise affect a customer׳s experience with the retailer׳s website and order fulfillment. Results of multiple-group structural equation modeling (SEM) from customer reviews of 306 Internet retailers demonstrate that the interactive effects of a web site experience and order fulfillment are significant. In the interactive mechanism, order fulfillment experience is proven to serve as a proximal cause of repurchase intention. The moderating role of product type is significant as well. This finding suggests that practitioners should have unmatched measures for retailing different types of goods.     

An Exploratory Framework for Analysing International Retail Learning

It is argued that international retail research has overlooked an essential component of the retail internationalization process, notably learning. This paper proposes an exploratory framework that enables the application of learning theory to the study of international retailing. The paper provides a meaningful starting point for developing an overarching framework which would represent one sort of re-conceptualization of the retail internationalization process, and arguably a new perspective for reinterpreting, re-evaluating and refining the existing literature on international retailing. Alongside this exploratory framework, we present a series of research propositions that might serve as an agenda for research into international retail learning. The paper concludes with a summary of the key themes and ways in which the area of international retail learning may be investigated.