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Abstract
Managers and investors need information about the performance and future prospects of a firm. If information is relevant in steering a business, it is also relevant for its investors' investment decisions. 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. Firms that aim to increase the value of their customer base should manage their business by future-oriented customer metrics. They should also report this information externally because it aligns customer management with corporate goals and investors' perspectives. The authors propose a means to report customer equity that enables monitoring firms' performance with respect to their customer assets. Furthermore, they develop a specific model for Netflix and apply it to quarterly reports that cover more than six years.

How can firms retain customers during recessions? To answer this question, we investigate the moderating role of consumer confidence (CC) on the effects of three types of crucial customer loyalty strategies. These strategies are value equity (VE), brand equity (BE), and relationship equity (RE), collectively called customer equity drivers (CEDs). We build on economics and marketing theories to develop our hypotheses on the concerned moderating role. A meta-analysis is used to synthesize the multilevel results of 13 service industries and to test the hypotheses. In addition, we use several robustness checks to validate the findings of the meta-analysis. The results consistently show that CC partly influences the effects of CEDs on customer loyalty and this influence varies across industries. These findings suggest that managers in service industries should consider CC as an important criterion for effectively adjusting customer loyalty strategies to their specific situation. Specifically, during recessions, when CC is relatively low, VE is effective for retaining customers, but this is more apparent for noncontractual settings than for contractual settings. Also, BE is more effective but only for noncontractual firms.

Customers can interact with and create value for firms in a variety of ways. This article proposes that assessing the value of customers based solely upon their transactions with a firm may not be sufficient, and valuing this engagement correctly is crucial in avoiding undervaluation and overvaluation of customers. We propose four components of a customer's engagement value (CEV) with a firm. The first component is customer lifetime value (the customer's purchase behavior), the second is customer referral value (as it relates to incentivized referral of new customers), the third is customer influencer value (which includes the customer's behavior to influence other customers, that is increasing acquisition, retention, and share of wallet through word of mouth of existing customers as well as prospects), and the fourth is customer knowledge value (the value added to the firm by feedback from the customer). CEV provides a comprehensive framework that can ultimately lead to more efficient marketing strategies that enable higher long-term contribution from the customer. Metrics to measure CEV, future research propositions regarding relationships between the four components of CEV are proposed and marketing strategies that can leverage these relationships suggested.

Recent years have seen the introduction of a "marketing dashboard" that brings the firm's key marketing metrics into a single display. Service firms across industries have created such dashboards either by themselves or together with a dashboard service provider. This article examines the reasons for this development and explains what dashboards are, how to develop them, what drives their adoption, and which academic research is needed to fully exploit their potential. Overcoming the challenges faced in dashboard development and operation provides many opportunities for marketing to exercise a stronger influence on top management decisions. The article outlines five stages of dashboard development and discusses the relationships among demand for dashboards, supply of dashboards, and the implementation process in driving adoption and use of dashboard systems. Key topics for future research include metrics selection, relationships among metrics, and the ultimate question of whether dashboards provide sufficient benefits to justify their adoption.