In this article, the authors strengthen the chain of effects that link customer satisfaction to shareholder value by establishing the link between satisfaction and two characteristics of future cash flows that determine the value of the firm to shareholders: growth and stability. Using longitudinal American Customer Satisfaction Index and COMPUSTAT data and hierarchical Bayesian estimation, the authors find that satisfaction creates shareholder value by increasing future cash flow growth and reducing its variability. They test the stability of findings across several firm and industry characteristics, and they assess the robustness of the results using multimeasure and multimethod estimation.

Managers commonly use customer feedback data to set goals and monitor performance on metrics such as “Top 2 Box” customer satisfaction scores and “intention-to-repurchase” loyalty scores. However, analysts have advocated a number of different customer feedback metrics including average customer satisfaction scores and the number of “net promoters” among a firm's customers. We empirically examine which commonly used and widely advocated customer feedback metrics are most valuable in predicting future business performance. Using American Customer Satisfaction Index data, we assess the linkages between six different satisfaction and loyalty metrics and COMPUSTAT and CRSP data-based measures of different dimensions of firms' business performance over the period 1994–2000. Our results indicate that average satisfaction scores have the greatest value in predicting future business performance and that Top 2 Box satisfaction scores also have good predictive value. We also find that while repurchase likelihood and proportion of customers complaining have some predictive value depending on the specific dimension of business performance, metrics based on recommendation intentions (net promoters) and behavior (average number of recommendations) have little or no predictive value. Our results clearly indicate that recent prescriptions to focus customer feedback systems and metrics solely on customers' recommendation intentions and behaviors are misguided.customer satisfaction, marketing metrics, marketing strategy

Most large firms operating in consumer markets own and market more than one brand (i.e., they have a brand portfolio). Although firms make corporate-level strategic decisions regarding their brand portfolio, little is known about whether and how a firm's brand portfolio strategy is linked to its business performance. Using data from the American Customer Satisfaction Index and other secondary sources, the authors examine the impact of the scope, competition, and positioning characteristics of brand portfolios on the marketing and financial performance of 72 large publicly traded firms operating in consumer markets over ten years (from 1994 to 2003). Controlling for several industry and firm characteristics, the authors analyze the relationship between five specific brand portfolio characteristics (number of brands owned, number of segments in which they are marketed, degree to which the brands in the firm's portfolio compete with one another, and consumer perceptions of the quality and price of the brands in the firm's portfolio) and firms' marketing effectiveness (consumer loyalty and market share), marketing efficiency (ratio of advertising spending to sales and ratio of selling, general, and administrative expenses to sales), and financial performance (Tobin's q, cash flow, and cash flow variability). They find that each of these five brand portfolio characteristics explains significant variance in five or more of the seven aspects of firms' marketing and financial performance examined.

Investors and managers evaluate potential investments in terms of risk and return. Research has focused on linking marketing activities and resource deployments with returns but has largely neglected marketing's role in determining risk. Yet the theoretical literature asserts that investments in market-based assets, such as brands, should lead to reductions in firm risk. Adopting risk measures that are well established in the finance literature, the authors use credit ratings to capture debt-holder risk and the standard deviation of stock returns to measure equityholder risk, which they then decompose into systematic and unsystematic equity risk. The authors examine the impact of consumer-based brand equity (CBBE) on firm risk using data covering 252 firms from EquiTrend, COMPUSTAT, and the Center for Research in Security Prices over the 2000-2006 period. They find that a firm's CBBE is associated with firm risk and explains variance in the risk measures beyond that explained by existing finance models (i.e., it has "risk relevance"). They also find that CBBE has a stronger role in predicting firm-specific unsystematic risk than systematic risk but that it also has a particularly strong role in protecting equity holders from downside systematic risk. The results have clear economic significance and suggest that managers should make brand management part of the firm's risk management strategy and protect or even increase CBBE investments during periods of economic uncertainty.

This study empirically investigates marketing department power within U.S. firms over the 1993-2008 period and assesses its impact on firm performance. Using a new objective measure of marketing department power and a cross-industry sample of 612 public firms in the U.S., results reveal that marketing department power generally increased over this time period. Further, our analyses show that a powerful marketing department enhances firms' longer-term future Total Shareholder Returns (TSR) above and beyond its positive effect on firms' short-term Return on Assets (ROA). The findings also reveal that a firm's long run market-based asset building and short run market-based asset leveraging capabilities partially mediate the effect of a firm's marketing department power on its longer-term shareholder value performance, and fully mediate the effect on its short-term ROA performance. This research provides new insights for marketing scholars and managers concerning marketing's influence within the firm and how investments in building a powerful marketing department impact firm performance.While there is a perception of a decline in marketing department power within firms over time in the literature (e.g., Verhoef and Leeflang 2009; Webster, Malter, and Ganesan 2005), little clear empirical evidence exists for such a belief (Homburg, Workman, and Krohmer 1999; Merlo and Auh 2010). For example, in a recent study Homburg et al. (2015) find a decline in marketing departments' decision influence between two points in time (1996 and 2013) in two samples of similar German firms. Yet, other recent studies report evidence of increasing marketing department power (e.g., Lamberti and Noci 2009; Merlo, Lukas, and Whitwell 2012). Further, irrespective of whether it is rising or declining, we have no clear understanding of whether marketing department power really matters because the few empirical studies examining its relationship with firm performance have also reported conflicting results. For example, Moorman and Rust (1999) and Homburg et al. (2015) report a positive relationship between marketing department power and firm performance. In contrast, Götz, Hoelter, and Krafft (2013) find a negative relationship, and Verhoef and Leeflang (2009) and Merlo and Auh (2009) report no relationship.A key problem with existing knowledge is that the few empirical studies of marketing department power use cross-sectional survey data from relatively small samples of firms.While surveys are an appropriate way to measure departmental power within firms (e.g., Finkelstein 1992; Pfeffer 1981), their use in this context creates two particular problems.First, the difficulty of collecting repeated survey data over long periods of time from the same firms means that there have been no large sample longitudinal survey studies of marketing department power. This has limited researchers' ability to examine changes in marketing department power over multiple points in time in generalizable samples. Second, while crosssectional survey data allow correlat...