The role of customer gratitude in making relationship marketing investments successful

This paper recognises that customer loyalty is important for many competitive organisations, and that retail firms make investments to build and maintain loyal relationships with their existing and potential customers (e.g. loyalty programs). However, there has been little focus on the mechanisms by which these relationship investments operate to achieve customer loyalty. This paper examines one mechanism, namely customer gratitude, which works to make a firm’s relationship marketing investment a success or a failure. Using data from 1600 undergraduate students, this study empirically confirms the mediating role of customer gratitude between the customers’ perceptions a firm’s relationship marketing investments and customers’ perceptions of the value of the relationship with the firm. Further, a significant moderating effect of perceived benevolence on the relationship between customers’ perceptions a firm’s relationship marketing investments and customer gratitude was identified. For theorists, this customer gratitude model offers a better psychological explanation of how relationship marketing investments operate to improve the value that customers place on their relationships with retailers. Our research suggests that managers should invest resources to stimulate customer gratitude in order to build strong customer–seller relationships.     

Siri,Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications

ABSTRACT

Digital assistants (e.g., Apple’s Siri, Amazon’s Alexa, Google’s Google Assistant) are highly complex and advanced artificial intelligence (AI) based technologies. Individuals can use digital assistants to perform basic personal tasks as well as for more advanced capabilities. Yet, the functional and topical use of a digital assistant tends to vary by individual. This study reflects the contextual experiences of the respondents. At present, there is little empirical evidence of customer satisfaction with digital assistants. PLS-SEM was used to analyse 244 survey responses to examine this research gap. The results confirmed that expectations and confirmation of expectations have a positive and significant relationship on customer satisfaction with digital assistants. This study provides evidence that customer expectations are being satisfied through the digital assistant interaction experience. As firms integrate digital assistants into their operations, they must help customers properly define what to expect from the firm’s interactive experience.     

Comparing email and SNS users: Investigating e-servicescape,customer reviews,trust, loyalty and E-WOM

For better or worse, satisfied or dissatisfied customers function as trusted branding faces for organizations as they transmit potentially viral messages through E-WOM. These E-WOM messages can prove marketers' best friends or worst enemies, depending on their tenor. With data from actual customers of an e-tailer, this research enriches our understanding of how e-servicescape is linked to E-WOM. E-servicescape captures the online environmental factors of marketers’ websites. Two forms of E-WOM are examined; i.e., emails and social network postings. Customer reviews were investigated as a prospective sub-dimension of e-servicescape. Findings suggest that customer reviews play an integral role in the e-servicescape construct, that e-servicescape positively impacts trust and that trust positively influences E-WOM and customer loyalty. Two groups of customers were compared, and results indicated differences between email and SNS users. Theoretical and managerial insights related to E-WOM and electronic commerce shopping behavior were generated.     

Market orientation, competitive advantage, and performance: A demand-based perspective

This study assesses how customer value affects a firm's market orientation and consequently, competitive advantage and organizational performance in a service industry — the global hotel industry. The findings show that if a firm perceives its customers as valuing service, the firm is more likely to adopt both a customer and a competitor orientation; if the firm thinks its customers are price sensitive, the firm tends to develop a competitor orientation. Moreover, the greater a firm's customer orientation, the more the firm is able to develop a competitive advantage based on innovation and market differentiation. In contrast, a competitor orientation has a negative effect on a firm's market differentiation advantage. Finally, innovation and market differentiation advantages lead to greater market performance (e.g., perceived quality, customer satisfaction) and in turn, higher financial performance (e.g., profit, market share).     

The friend or foe fallacy: Why your best customers may not need your friendship

Organizational transactions are handled along a continuum of the firm’s customer relationships, ranging from relational and friendly to more adversarial and us-versus-them in demeanor. For top customers, the approach is almost always close and relational. In this article, we question this view and suggest that it is beneficial to condition the firm’s relationship development efforts on an understanding of the true value to be gained from partnering and increased closeness. We provide a framework with which managers can diagnose their current portfolio of relationships with key customers or suppliers and offer suggestions for action. We provide an empirical illustration of the typical distribution of responses among five regions of the framework and discuss its implications.     

Customer base analysis with recurrent neural networks

One of the primary goals that researchers look to achieve through customer base analysis is to leverage historical records of individual customer transactions and related context factors to forecast future behavior, and to link these forecasts with actionable characteristics of individuals, managerially significant customer sub-groups, and entire cohorts. This paper presents a new approach that helps firms leverage the automatic feature extraction capabilities of a specific type of deep learning models when applied to customer transaction histories in non-contractual business settings (i.e., when the time at which a customer becomes inactive is unobserved by the firm). We show how the proposed deep learning model improves on established models both in terms of individual-level accuracy and overall cohort-level bias. It also helps managers in capturing seasonal trends and other forms of purchase dynamics that are important to detect in a timely manner for the purpose of proactive customer-base management. We demonstrate the model performance in eight empirical real-life settings which vary broadly in transaction frequency, purchase (ir)regularity, customer attrition, availability of contextual information, seasonal variance, and cohort size. We showcase the flexibility of the approach and how the model further benefits from taking into account static (e.g., socio-economic variables, demographics) and dynamic context factors (e.g., weather, holiday seasons, marketing appeals). We make an open-source reference implementation of the newly developed method available at https://github.com/valendin/rfm2lstm.     

Customers who misbehave: Identifying restaurant guests “acting out” via asymmetric case models

This study uncovers the impact of combined dark triad personality traits, firm's power, and customer demographic characteristics. It uses a sample of 263 restaurant customers. The findings include customer configurations indicating misbehavior and non-misbehavior cases. From a theoretical perspective, the study questions the philosophy of customer sovereignty and applies asymmetric case-based modeling to identify configurations indicating misbehavior customers and non-misbehavior customers. Strategy implications: from a managerial perspective and to tackle misbehavior, firms should use coercive power (e.g., suing customers who misbehave), reward power (e.g., recognition and flattery when customers behave properly), and referent power (e.g., enforcing customers' affective attachment).     

Moving from customer lifetime value to customer equity

We study the consequence of moving from Customer Lifetime Value maximization to Customer Equity maximization. Customer equity has traditionally been seen as the discounted sum of the lifetime earnings from all current and future customers and thus it has been largely assumed that maximizing customer lifetime value would lead to maximum customer equity. We show that the transition from CLV to CE is not that straightforward. Although the CLV model is appropriate for managing a single non-replaceable customer, the application of a CLV model to the acquisition and valuation of customers as an ongoing concern for the firm leads to sub-optimal customer relationship management and acquisition strategies. This leads the firm following a CLV maximization approach to have a smaller and less profitable customer base than one that follows a CE maximization strategy.

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Linking customer resources to firm success: The role of marketing program implementation

Drawing from both resource-based view and dynamic capabilities theory, this research investigates how customer resources (i.e., knowledge and network size) influence firm performance through marketing program implementation. The current research shows that customer resources are critical to the development and execution of marketing programs, which can then lead to firm success. Through surveying 269 retailers, this study finds that while customer knowledge directly affects marketing program implementation, it does not directly influence firm performance. In contrast, customer network size not only directly contributes to marketing program implementation and firm performance, but also serves as a significant moderator.     

Effect of social support on customer satisfaction and citizenship behavior in online brand communities: The moderating role of support source

Customers often join online brand communities to seek support from others when they encounter product problems. Some customers who receive good social support exhibit customer citizenship behavior. This study develops a theoretical model to investigate how social support influences customer citizenship behavior through customer satisfaction with firms in online brand communities. Moreover, the moderating role of support source (i.e., firms vs. other customers) is measured. The research model is tested by using the Partial Least Squares technique. The results show that informational and emotional support significantly affects the customer citizenship behavior of providing feedback to the firm, recommendations, and helping other customers through customer satisfaction in online brand communities. Moreover, informational and emotional support from firms and other customers exert different effects on customer satisfaction.     

A multi-category customer base analysis

Customer base analysis is an essential tool to measure and develop relationships with customers. While various models have been proposed in a noncontractual setting, they focus primarily on analyzing transactional patterns associated with a single product category or a firm-level activity, such as the times at which purchases are made at a particular retailer. This research proposes a modeling framework for customer base analysis in a multi-category context. Specifically, we model the time between a customer's purchases at the firm and the product categories that comprise her shopping basket arising from multi-category choice decisions. The proposed model uses a latent space approach that parsimoniously captures the dynamics of multi-category shopping behavior due to the interplay between purchase timing and shopping basket composition. We also account for interdependence among multiple categories, temporal dependence across category choices, and latent customer attrition. Using category-level transaction data, we show that the proposed model offers excellent fit and performance in predicting customer purchase patterns across multiple categories. The forecasts and inferences afforded by our model can assist managers in tailoring marketing efforts across categories.     

A guide to pay-what-you-wish pricing from the consumer’s viewpoint

As customer participation in business transactions increases, it is important to investigate how consumers approach financial transactions with firms in terms of selfishness and fairness. Pay-what-you-wish pricing models continue to attract managerial and academic interest as allowing customers to set prices provides an unorthodox setting in which to examine forces that drive buyer-seller interactions. This Executive Digest provides an overview of the current state of pay-what-you-wish (PWYW) pricing and the benefits it can provide to a firm.     

Matching the Personal Initiative Capabilities of FLEs to Their Self-Regulatory Processes and the Firm's Initiative Climate

Frontline employees (FLEs) — the people behind the counter, on the phone, or walking the shop floor — can profoundly affect the customer experience. Harnessing the capability of FLEs to positively shape customer experiences is critical for service firms.However, placing the right employee in the right frontline role is not an easy task. To deliver positive service experiences, FLEs must be customer-oriented, placing customers’ interests first. In addition, FLEs need to demonstrate personal initiative by going beyond prescribed job roles to find solutions to customer problems. We propose that personal initiative is an important mediating variable in the relationship between customer orientation and FLE performance. Further, we examine whether this relationship is strengthened or weakened when a firm’s climate encourages initiative-taking behavior and FLEs have a prove or avoid orientation, or engage in deep or surface acting. We test the model across two studies using a multi-respondent data collection procedure within the retail banking sector. Our findings demonstrate that personal initiative mediates the relationship between customer orientation and FLE performance. Notably, this effect is stronger when a firm’s climate encourages initiative-taking and when FLEs have a prove orientation or engage in deep acting, and that the effect is weaker when FLEs have an avoid orientation or engage in surface acting. Our findings underscore that it is only when the fit between FLEs, their roles, and the work climate is right that firms will get the best out of their employees (c.f., Arthur et al. 2006; Kristof-Brown et al., 2005).     

Timing customer reactivation initiatives

Firms operating in non-contractual settings apply customer reactivation initiatives such as email messages to stimulate customers who have become inactive temporarily or permanently to resume their transaction activities. Thus, firms need to know which customers are inactive, and when a customer becomes inactive. Existing approaches struggle to distinguish active from inactive customers and do not provide time-scale estimates of when to send reactivation mails. To address these shortcomings, we develop an approach to target and time the sending of reactivation mails. Building on control chart methods, we introduce a gamma–gamma control chart, modelling the average customer interpurchase time and the variation therein to determine activity boundaries. Crossing these boundaries signals a potential change in a customer’s purchasing activity, providing a signal to initiate customer reactivation. A field experiment in the greetings and gifts industry, supported by several additional analyses, illustrates the improved performance of our approach when it comes to signaling customer activity against a wide range of competing models. The improved performance of our method occurs particularly in settings where customers vary strongly in purchase and inactivity patterns.     

Quantifying the influence of customer experience on consumer share-of-category

Customer experience is an all-encompassing construct, and most companies go to considerable lengths to create memorable, extraordinary experiences. Nevertheless, customers experience offerings, companies, and their brands very differently. Using one qualitative and three quantitative studies we explore customers’ experiences from a financial perspective by measuring and quantifying the linkages between these and customers’ share-of-category. When measured by means of customers’ share-of-category, customers demonstrate significantly different purchasing intentions and behavior. In addition, customer retail service experiences that influence the share-of-category differ significantly between customers with a low and a high share-of-category. We expand our knowledge of customer experience by highlighting that different customer groups may perceive a similar retail experience differently, leading to a different purchasing behavior and influencing their respective share-of-category. This study expands existing research by providing empirical evidence of the link between the customer experience and customers’ purchasing behavior.     

How personal costs influence customer citizenship behaviors

Many customers engage in customer citizenship behaviors, such as restocking unwanted items, helping other customers, or putting shopping carts back. Although previous research has investigated a variety of antecedents of customer citizenship behaviors, it has not yet considered the personal costs that might inhibit the decision to engage in those behaviors. Using social exchange theory and tested with three experimental studies, this research demonstrates that customers consider their personal cost/benefit trade-off prior to engaging in customer citizenship behaviors. Specifically, perceived self-sacrifice reduces intention to engage in customer citizenship behaviors while awareness of public self-image increases intention. Furthermore, this cost/benefit trade-off between self-sacrifice and public self-image is influenced by peer norms and perceived consequence to the firm.     

The benefits and implementation of performance transparency: The why and how of letting your customers ‘see through’ your business

While some organizations swear by the benefits of transparency and are eager to learn and implement transparency practices, many managers are still reluctant or even afraid to use them. Our research reveals that only a few innovative companies have taken steps to leverage a potentially useful form of transparency: the provision of accessible and objective information to customers (e.g., sharing unbiased benchmark data, publishing unfiltered customer comments, or providing candid product reviews that may praise but also criticize the company’s products). Our study also shows that many companies remain wary and view greater calls for transparency as a challenge to be managed rather than an opportunity to be traded upon. This is partly due to limited research into the performance benefits of giving customers access to objective information, and lack of practical guidelines on how to actually implement it. This article addresses these shortcomings. First, we investigate whether performance transparency leads to customer outcomes that can be profitable for an organization and, second, we analyze the characteristics of successful transparency initiatives in a wide range of industries. Our research shows that customers exhibit more trust and are willing to pay a premium to deal with transparent businesses. Also, it uncovers seven effective strategies to leverage transparency. This article provides convincing empirical evidence for the benefits of performance transparency and the ways in which management may implement it successfully.     

Managing Complaints to Improve Customer Profitability

In this study, the authors aim to understand whether, to what extent, and under what circumstances, organizational responses to customer complaints improve customer profitability. To do so, they build upon the congruence approach and propose a contingency framework in which the effectiveness of three organizational responses to customer complaints (timeliness, compensation and communications) in improving customer profitability is contingent upon the strength of the relationship and the type of failure. The framework is tested empirically in the financial services industry applying latent class techniques to longitudinal data for a sample of complaining customers. The results reveal that: (1) different complaint-handling initiatives affect customer profitability differently for each of the four segments of complaining customers that are obtained; (2) these heterogeneous responses to complaint handling are explained by differences in the orientation of the relationship and in the failure context; and (3) complaint-handling initiatives are more (less) effective at improving customer profitability when the benefits they offer strongly (poorly) match the benefits sought by customers in each segment to recover from the failure. These results contribute to a better theoretical understanding of customers’ heterogeneous responses to complaint handling and offer managerial recommendations to allocate marketing resources across alternative complaint-handling strategies to improve profitability.     

A sequence analysis approach to segmenting credit card customers

This research examines the longitudinal relationships between patterns of customer loyalty behavior and firm financial outcomes in the context of credit card use. By examining credit card users' transactions with a focal bank and its competitors, this study creates a typology of loyalty behavior and employs a sequence analysis to segment customers on the basis of their behavioral patterns exhibited over time. The analysis results in six distinct customer segments: Loyalist, Switching Loyalist, Switching Defector, Defector, Dormant Loyalist, and Dormant Defector. We subsequently estimate the revenue, servicing costs, and profitability associated with each segment, and assess differences across segments. We discuss the implications for managing distinct credit card customer segments and optimizing the bank's marketing resource allocation.     

Customer Selection and Prioritization

Abstract

That a firm benefits most when customers stick around for the long haul is a central premise of relationship marketing. This conviction has manifested itself over the past decade in the form of numerous formal loyalty programs that aim to seek and foster customer relationships. Scant evidence for the success of such programs has accrued since. This has lead firms to re-evaluate their investments in customer relationship management. Optimal resource allocation models address issues of relative investments in customer acquisition versus retention, and on managing relationships with profitable customers so that the value of a firm's customer base is maximized.