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Despite the demonstrated importance of customer sentiment in social media for outcomes such as purchase behavior and of firms' increasing use of customer engagement initiatives, surprisingly few studies have investigated firms' ability to influence the sentiment of customers' digital engagement. Many firms track buyers' offline interactions, design online content to coincide with customers' experiences, and face varied performance during events, enabling the modification of marketer-generated content to correspond to the event outcomes. This study examines the role of firms' social media engagement initiatives surrounding customers' experiential interaction events in influencing the sentiment of customers' digital engagement. Results indicate that marketers can influence the sentiment of customers' digital engagement beyond their performance during customers' interactions, and for unfavorable event outcomes, informational marketer-generated content, more so than emotional content, can enhance customer sentiment. This study also highlights sentiment's role as a leading indicator for customer lifetime value. [ABSTRACT FROM AUTHOR]

Practitioners increasingly employ relational price discounts by granting initial discounts to new customers with the goal of building sustainable relationships. However, extant research has provided mixed findings on the long-term effects of initial discounts on customer retention. The current research aims to reconcile this mixed evidence by exploring nonlinear effects of initial discounts on customer retention. Drawing on marketplace metacognition theory, the authors hypothesize that moderate initial discounts (5%–35%) have positive effects on customer retention, whereas low (<5%) and high (>35%) discounts have negative effects. Two large-scale field studies in an insurance company’s car insurance branch and property insurance branch provide empirical support for the hypothesized patterns. An additional laboratory experiment tests the psychological mechanism underlying the nonlinear effects. When compared with low and high discounts, moderate initial discounts lead customers to form higher expectations of future relational benefits provided by the firm, as well as to lower their expectations of future discounts. Finally, this research offers customer lifetime value implications based on the depicted findings. [ABSTRACT FROM AUTHOR]

Customer value refers to the economic value of the customer’s relationship with the firm. This study approaches the topic of customer value for measuring, managing, and maximizing customer contributions by proposing a customer valuation theory (CVT) based on economic principles that conceptualizes the generation of value from customers to firms. The author reviews the established economic theories for valuing investor assets (e.g., stocks) and draws a comparison to valuing customer contributions. Furthermore, the author recognizes the differences in the guiding principles between valuing stocks and valuing customers in proposing CVT. Using CVT, the author discusses the concept of customer lifetime value (CLV) as the metric that can provide a reliable, forward-looking estimate of direct customer value. In addition, economic models to estimate CLV, ways to manage CLV using portfolio management principles, and strategies to maximize CLV are discussed in detail. The author extends the customer value concept by discussing ways that a customer can add value to the firm indirectly through incentivized referrals, social media influence, and feedback. Finally, the benefits of CVT to multiple constituencies are offered. [ABSTRACT FROM AUTHOR]

The article discusses a framework created for valuing subscription-based firms using both the value of a firm's customers and the overall value of the firm, known as customer-based corporate valuation. Topics include the customer acquisition and retention models of firms, investors' use of customer data to estimate or predict customer behavior which determines a subscription-based business' cash flow, and the potential use of customer data and financial statements by marketing scholars to determine company value.

One of the most important tasks in marketing is to create and communicate value to customers to drive their satisfaction, loyalty, and profitability. In this study, the authors assume that customer value is a dual concept. First, in order to be successful, firms (and the marketing function) have to create perceived value for customers. Toward that end, marketers have to measure customer perceived value and have to provide customer perceptions of value through marketing-mix elements. Second, customers in return give value through multiple forms of engagement (customer lifetime value, in the widest sense) for the organization. Therefore, marketers need to measure and manage this value of the customer(s) to the firm and have to incorporate this aspect into real-time marketing decisions. The authors integrate and existing findings, show the best practices of implementation, and highlight future research avenues. [ABSTRACT FROM AUTHOR]

A debate about whether firms with superior customer satisfaction earn superior stock returns has been persistent in the literature. Using 15 years of audited returns, the authors find convincing empirical evidence that stock returns on customer satisfaction do beat the market. The recorded cumulative returns were 518% over the years studied (2000-2014), compared with a 31% increase for the S&P 500. Similar results using back-tested instead of real returns were found in the United Kingdom. The effect of customer satisfaction on stock price is, at least in part, channeled through earnings surprises. Consistent with theory, customer satisfaction has an effect on earnings themselves. In addition, the authors examine the effect of stock returns from earnings on stock returns from customer satisfaction. If earnings returns are included among the risk factors in the asset pricing model, the earnings variable partially mitigates the returns on customer satisfaction. Because of the long time series, it is also possible to examine time periods when customer satisfaction returns were below market. The reversal of the general trend largely resulted from short-term market idiosyncrasies with little or no support from fundamentals. Such irregularities have been infrequent and eventually self-correcting. The authors provide reasons why irregularities may occur from time to time. [ABSTRACT FROM AUTHOR]

Sorescu and Sorescu (2016) and Bharadwaj and Mitra (2016) have made a number of insightful observations and suggestions for future research regarding stock returns on customer satisfaction. They have also provided a series of assessments of a study by Fornell, Morgeson, and Hult (2016) that focus on abnormal returns on customer satisfaction. Building on the original study, as well as the two commentaries and previous research, the study's authors argue that the published empirical evidence is quite consistent in favor of abnormal returns on customer satisfaction. These findings are also supported by the new analysis of Sorescu and Sorescu, whomake several important contributions, not only regarding the persistence of abnormal returns over and beyond the technology sector but alsowith respect to the critical importance of industry classification in the context of customer satisfaction--something that definitely calls formore research attention. In fact, there aremany avenues for future research on the economic and financial impact of customer satisfaction, as laid out in the commentaries, the authors' original article, and this response. [ABSTRACT FROM AUTHOR]

Historically, when targeting potential adopters of a new product, firms have tended to focus first on people with disproportional effect on others, often labeled "opinion leaders." The authors highlight the benefit of targeting customers with high lifetime value (CLV), or "revenue leaders." The authors argue that targeting revenue leaders can create high value both by accelerating adoption among these customers and because of the higher-than- average value that revenue leaders generate by affecting other customers with similarly high CLV. The latter phenomenon is driven by network assortativity, whereby people's social networks tend to be composed of others who are similar to themselves. Analyzing an agent-based model of a seeding program for a new product, the authors contrast revenue leader seeding with opinion leader seeding and compare the factors that influence the effectiveness of each. They show that the distribution of CLV in the population and the seed size play a major role in determining which seeding approach is preferable, and they discuss the managerial implications of these findings. [ABSTRACT FROM AUTHOR]

It is common for business-to-business firms to use references from client firms when trying to influence prospects to become new customers. In this study, the authors define the concept of business reference value (BRV) as the ability of a client's reference to influence prospects to purchase and the degree to which it does so. They develop a three-step method to compute BRV for a given client using a retrospective reported measure of reference value. Next, they use data from a financial services and a telecommunications firm to identify and empirically test the drivers of BRV. These drivers fall into four categories: (1) length of client relationship, (2) client firm size, (3) reference media format, and (4) reference congruency. Next, the authors empirically show that clients that have the highest BRV are not the same as the clients that have the highest customer lifetime value. They also show that an average client that is high on BRV has significantly different characteristics from the average client that is low on BRV. Finally, they derive implications for managing BRV. [ABSTRACT FROM AUTHOR]

The authors investigate the relationships between brand equity and customer acquisition, retention, and profit margin, the key components of customer lifetime value (CLV). They examine a unique database from the U.S. automobile market that combines ten years of acquisition rate, retention rate, and customer profitability data with measures of brand equity from Young & Rubicam's Brand Asset Valuator (BAV) over the same period. They hypothesize and find that BAV brand equity is significantly associated with the components of CLV in expected and meaningful ways. For example, customer knowledge of a brand has an especially strong positive relationship with all three components of CLV. Notably, however, differentiation is a double-edged sword. While it is associated with higher customer profitability, it is also associated with lower acquisition and retention rates. The authors also find that marketing efforts exert indirect impacts on CLV through brand equity. Simulations show that changes in marketing, or exogenous changes in brand equity, can exert important effects on CLV. Overall, the findings suggest that the 'soft' and 'hard' sides of marketing need to be managed in a coordinated way. The authors conclude with a discussion of these and other implications for researchers and practitioners. [ABSTRACT FROM AUTHOR]

Conventional wisdom, marketing literature, and cross-selling practices to date are based on the notion that customer cross-buying is positively associated with customer profitability. However, this study finds that when certain customers with persistent adverse behavioral traits (e.g., limited spending, excessive revenue reversals, excessive service requests, promotion purchase behavior) engage in cross-buying, they exhibit a downward spiral of unprofitable relationship, with the losses increasing with higher levels of cross-buy. The authors analyze the customer databases of five firms and find that 10%-35% of the firms' customers who cross-buy are unprofitable and account for a significant proportion (39%-88%) of the firms' total loss from its customers. Consequently, the authors present a two-stage framework to enable managers to discern customers who are likely to engage in profitable versus unprofitable cross-buying. Overall, the findings refine the basic understanding of the cross-buy phenomenon and motivate managers to rethink their marketing practices and policies, which are typically designed to maximize cross-buy opportunities for every customer. [ABSTRACT FROM AUTHOR]

Customers are the most important assets of most companies, such that customer equity has been used as a proxy for shareholder value. However, linking customer metrics to shareholder value without considering debt and non-operating assets ignores their effects on relative changes in customer equity and leads to biased estimates. In developing a new theoretical framework for customer-based valuation, grounded in valuation theory, this article links the value of all customers to shareholder value and introduces a new leverage effect that can translate percentage changes in customer equity into shareholder value. The average leverage effect in more than 2000 companies across ten years is 1.55, which indicates that a 10%% increase in customer equity is amplified to a 15.5%% increase in shareholder value. This research also compares the influence of customer and financial metrics on shareholder value. The findings challenge previous notions about the dominant effect of the retention rate and underline the importance of predicting the number of future acquired customers for a company. [ABSTRACT FROM AUTHOR]

Referral programs have become a popular way to acquire customers. Yet there is no evidence to date that customers acquired through such programs are more valuable than other customers. The authors address this gap and investigate the extent to which referred customers are more profitable and more loyal. Tracking approximately 10,000 customers of a leading German bank for almost three years, the authors find that referred customers (1) have a higher contribution margin, though this difference erodes over time; (2) have a higher retention rate, and this difference persists over time; and (3) are more valuable in both the short and the long run. The average value of a referred customer is at least 16% higher than that of a nonreferred customer with similar demographics and time of acquisition. However, the size of the value differential varies across customer segments; therefore, firms should use a selective approach for their referral programs. [ABSTRACT FROM AUTHOR]

Many firms are now using referral marketing campaigns to harness the power of word of mouth and to increase referrals to acquire new customers. Prior research has identified a method of computing the value of referrals using only a customer's actual past referral behavior to compute customer referral value (CRV). In this article, the authors develop and test a new four-step approach to compute CRV. In addition, they determine the behavioral drivers of CRV and then identify the most effective methods of targeting the most promising customers on the basis of their customer lifetime value (CLV) and CRV scores. The authors illustrate and test this approach through four separate field experiments with firms from two industries: financial services and retailing. They find that to maximize profitability, it is critical to manage customers in terms of both their CLV and CRV scores and that understanding the behavioral drivers of CRV can help managers better target the most profitable customers with their referral marketing campaigns. [ABSTRACT FROM AUTHOR]

Can a marketer drive the stock price of the firm? Yes, it should be possible. Toward this endeavor, the authors develop a framework to link customer equity (CE) (as determined by the customer lifetime value metric) to market capitalization (MC) (as determined by the stock price of the firm). The authors test the framework in an empirical field experiment with two Fortune 1000 firms in the business-to-business and business-to-consumer contexts, respectively. The findings show that (1) a CE-based framework can reliably predict the MC of the firm and (2) marketing strategies directed at increasing the CE not only increase the stock price of the firm but also beat market expectations. Furthermore, the results indicate that the relationship between CE and MC is moderated by risk factors in the form of volatility and vulnerability of cash flows from customers. By accounting for these factors, the authors improve the association between CE and MC. The findings broaden the scope and role of marketing while reinforcing the importance of the marketer to any organization. [ABSTRACT FROM AUTHOR]

Although highly relevant for marketing practice, few studies provide conceptual and empirical insights into customer portfolio management. Furthermore, most approaches to analyzing customer portfolios are static. This article discusses three neglected key issues relevant for a dynamic customer portfolio analysis: (1) Does a static versus a dynamic valuation lead to a different prioritization of customer segments in a portfolio? (2) How does offensive or defensive management of segment dynamics affect portfolio value? and (3) Do reliable predictors for dynamics of a customer's position in the portfolio exist? As a tool for customer portfolio analysis, the authors develop a segment-based customer-lifetime-value model. They capture customer dynamics by analyzing how customers switch between segments of different values across time. The authors apply their tool with longitudinal data from four firms with up to 300,000 customers. The results from the empirical analysis and a simulation study provide answers to the three key issues raised. First, compared with a dynamic analysis, a static approach overestimates the value of some customer segments but underestimates others. Second, a defensive versus offensive management of value dynamics is relatively more appropriate for middle-tier segments, whereas the opposite holds true for bottom-tier segments. Third, general customer characteristics and aggregated transaction characteristics indicate future segment dynamics, whereas specific product usage data differentiate customers according to current value. [ABSTRACT FROM AUTHOR]

Recent initiatives demand information that supplements and complements a firm's financial statements to bridge the gap between financial statement capabilities and financial reporting objectives. Such information assists investors' decision making by explaining the main trends and factors that underlie the development, performance, and position of the firm's business. Firms that aim to increase the value of their customer base should report forward-looking customer metrics because such reports align customer management with corporate goals and investors' perspectives. The authors propose a means to report customer equity that enables investorsthe consumers of financial reportsto monitor firms' performance with respect to their customer assets. Furthermore, they develop a specific model for Netflix and apply it to quarterly data from September 2001 to September 2006. [ABSTRACT FROM AUTHOR]

In recent years, several authors have developed models that focus on the allocation of scarce marketing resources based on customer lifetime value (CLV). These approaches use CLV to develop a rank order of customers and recommend devoting more resources to customers with higher ranks. However, it has been discussed in the literature that a simple net present value analysis may not reflect the value of the flexibility to make such decisions. Therefore, some authors recommend the use of a real-options analysis in certain situations. Building on this stream of research and using the case of the option to abandon unprofitable customers, this article proposes an approach that combines real-options analysis and CLV; this approach explicitly values the seller's flexibility to abandon unprofitable customers. Using a combination of examples, empirical analysis, and Monte Carlo simulations, the authors provide evidence that the divergence between CLV that includes and CLV that excludes option value can be substantial and may not be the same for all customers. Therefore, the authors conclude that a distribution of customers based on CLV can change when option value is included. Thus, using CLV as a basis for marketing decisions but not including the value of the option to make such decisions a priori when calculating CLV can lead to an overall biased result. [ABSTRACT FROM AUTHOR]

The drivers of customer loyalty intentions are dynamic. What remains unclear is how these intentions evolve through the introduction and growth phases of a life cycle. Using a longitudinal study of cellular phone customers, the authors demonstrate that loyalty intentions are a function of perceived value early in the life cycle. Over time, more affective attitudes toward the brand and the relationship with the company come to mediate the effects of value on intentions. The results suggest that from the introduction to the growth stage of a life cycle, managers must adapt from improving value per se to measuring and managing relationships and brands directly. [ABSTRACT FROM AUTHOR]

This article presents a marketing communications process that uses customer relationship management ideas for multichannel retailers. The authors describe and then demonstrate the process with enterprise-level data from a major U.S. retailer with multiple channels. On the basis of the results, the authors develop an initial marketing communications strategy for the retailer. [ABSTRACT FROM AUTHOR]

Drawing on the relationship marketing and market information processing literature streams, the authors conceptualize and measure relational information processes, or organizational routines that are critical for customer relationship management (CRM). The authors examine the key drivers and outcome of relational information processes and the role of technology in implementing CRM using data collected from a diverse sample of firms. The results show that relational information processes play a vital role in enhancing an organization's customer relationship performance. By moderating the influence of relational information processes on customer relationship performance, technology used for CRM performs an important and supportive role. The study provides insights into why the use of CRM technology might not always deliver the expected customer relationship performance outcome. [ABSTRACT FROM AUTHOR]

The calculation of customer value without regard to marketing policy is problematic because the value of managerial flexibility and the impact of consumer learning are neglected. This article develops a structural dynamic programming model of consumer demand that includes marketing variables and consumer expectations of promotions. The author uses the estimated parameters to conduct policy experiments that yield more accurate forecasts of customer value and to study the impact of alternative marketing policies. [ABSTRACT FROM AUTHOR]

Customer relationship management (CRM) is perceived to be failing, and there is an urgent need for some practical ways to address this issue. The research presented in this article demonstrates that the implementation of CRM activities delivers greater profits. Using calculations of the lifetime value of customers in two longitudinal case studies, the research finds that customer management strategies change as more is discovered about the value of the customer. These changes lead to better firm performance. The contribution of this article is to show that CRM works and that a relatively straightforward analysis of the value of the customer can make a real difference. [ABSTRACT FROM AUTHOR]

In this research, the authors present a modeling framework for balancing resources between customer acquisition efforts and customer retention efforts. The key question that the framework addresses is, "What is the customer profitability maximizing balance?" In addition, they answer questions about how much marketing spending to allocate to customer acquisition and retention and how to distribute those allocations across communication channels. [ABSTRACT FROM AUTHOR]

The authors evaluate the usefulness of customer lifetime value (CLV) as a metric for customer selection and marketing resource allocation by developing a dynamic framework that enables managers to maintain or improve customer relationships proactively through marketing contacts across various channels and to maximize CLV simultaneously. The authors show that marketing contacts across various channels influence CLV nonlinearly. Customers who are selected on the basis of their lifetime value provide higher profits in future periods than do customers selected on the basis of several other customer-based metrics. The analyses suggest that there is potential for improved profits when managers design resource allocation rules that maximize CLV. Managers can use the authors' framework to allocate marketing resources efficiently across customers and channels of communication. [ABSTRACT FROM AUTHOR]

Management of an entire portfolio of customers who are at different relationship stages requires a dynamic theory of exchange relationships that captures the trade-offs between scale economies and lifetime customer value. This article contributes to the understanding of relationship management by developing a typology of exchange relationship mechanisms and a model of relationship dynamics and by simulating the model to provide guidelines for customer portfolio management. An important insight from the research is that a key to the creation of value through closer relationships lies in bringing weaker relationships into a portfolio in the first place. Another insight is that firms that position themselves toward offerings with low economies of scale, such as personal services, must build closer relationships to create value. [ABSTRACT FROM AUTHOR]

The authors present a unified strategic framework that enables competing marketing strategy options to be traded off on the basis of projected financial return, which is operationalized as the change in a firm's customer equity relative to the incremental expenditure necessary to produce the change. The change in the firm's customer equity is the change in its current and future customers' lifetime values, summed across all customers in the industry. Each customer's lifetime value results from the frequency of category purchases, average quantity of purchase, and brand-switching patterns combined with the firm's contribution margin. The brand-switching matrix can be estimated from either longitudinal panel data or cross-sectional survey data, using a logit choice model. Firms can analyze drivers that have the greatest impact, compare the drivers' performance with that of competitors' drivers, and project return on investment from improvements in the drivers. To demonstrate how the approach can be implemented in a specific corporate setting and to show the methods used to test and validate the model, the authors illustrate a detailed application of the approach by using data from the airline industry. Their framework enables what-if evaluation of marketing return on investment, which can include such criteria as return on quality, return on advertising, return on loyalty programs, and even return on corporate citizenship, given a particular shift in customer perceptions. This enables the firm to focus marketing efforts on strategic initiatives that generate the greatest return. [ABSTRACT FROM AUTHOR]

The authors develop a framework that incorporates projected profitability of customers in the computation of lifetime duration. Furthermore, the authors identify factors under a manager's control that explain the variation in the profitable lifetime duration. They also compare other frameworks with the traditional methods such as the recency, frequency, and monetary value framework and past customer value and illustrate the superiority of the proposed framework. Finally, the authors develop several key implications that can be of value to decision makers in managing customer relationships. [ABSTRACT FROM AUTHOR]

Relationship marketing emphasizes the need for maintaining long-term customer relationships. It is beneficial, in general, to serve customers over a longer time, especially in a contractual relationship. However, it is not clear whether some of the findings observed in a contractual setting hold good in noncontractual scenarios: relationships between a seller and a buyer that are not governed by a contract or membership. The authors offer four different propositions in this study and subsequently test each one in a noncontractual context. The four propositions relate to whether (1) there exists a strong positive customer lifetime-profitability relationship, (2) profits increase over time, (3) the costs of serving long-life customers are less, and (4) long-life customers pay higher prices. The authors develop arguments both for and against each of the propositions. The data for this study, obtained from a large catalog retailer, cover a three-year window and are recorded on a daily basis. The empirical findings observed in this study challenge all the expectations derived from the literature. Long-life customers are not necessarily profitable customers. The authors develop plausible explanations for findings that go against the available evidence in the literature and identify three indicators through discriminant analysis that can help managers focus their efforts on more profitable customers. The authors draw several marketing implications and acknowledge the limitations of the study. [ABSTRACT FROM AUTHOR]

Several theories of relationship marketing propose that customers vary in their relationships with a firm on a continuum from transactional to highly relational bonds. Few empirical studies have segmented the customer base of an organization into low and high relational groups to assess how evaluations vary for these groups. Using structural equation analysis, the authors analyze the relationships of satisfaction, trust, and commitment to component satisfaction attitudes and future intentions for the customers of a New York off-Broadway repertory theater company. For the low relational customers (individual ticket buyers and occasional subscribers), overall satisfaction is the primary mediating construct between the component attitudes and future intentions. For the high relational customers (consistent subscribers), trust and commitment, rather than satisfaction, are the mediators between component attitudes and future intentions. [ABSTRACT FROM AUTHOR]

For consumers, evaluation of a service firm often depends on evaluation of the "service encounter" or the period of time when the customer interacts directly with the firm. Knowledge of the factors that influence customer evaluations in service encounters is therefore critical, particularly at a time when general perceptions of service quality are declining. The author presents a model for understanding service encounter evaluation that synthesizes consumer satisfaction, services marketing, and attribution theories. A portion of the model is tested experimentally to assess the effects of physical surroundings and employee responses (explanations and offers to compensate) on attributions and satisfaction in a service failure context. [ABSTRACT FROM AUTHOR]

This article proposes that the dyadic interaction between a service provider and a customer is an important determinant of the customer's global satisfaction with the service. Based on role theory, a theoretical framework is presented which abstracts some of the critical components of service encounters across industries. [ABSTRACT FROM AUTHOR]