Knowledge that Transforms

Abstract Customer satisfaction (CSAT) is a central construct in theory and practice; yet its role as a strategic resource is often underappreciated. This article synthesizes the conceptual foundations, measurement approaches, empirical findings, and managerial applications of CSAT research. This article defines CSAT as a post-consumption evaluative judgment of whether customers receive the promised value, and distinguishes it from related constructs such as service quality, engagement, loyalty, experience, and value. Drawing on multiple scales and a comparative study across consumer demographics, we demonstrate that widely used CSAT measures exhibit strong convergent validity. A historical review of the evolution of CSAT research highlights the multi-level nature of the resulting frameworks, providing individual-, firm-, and industry-level insights. Furthermore, we use a large-scale dataset of more than 285 million ratings across 1,126 brands to replicate and extend prior meta-analytic evidence and show that CSAT is robustly associated with customer mindset metrics, accounting outcomes, and stock market performance. Finally, we develop micro-, meso- and macro-level conceptual frameworks and outline a forward-looking, multi-level research agenda to revitalize CSAT scholarship and practice.

Abstract Expectancy-disconfirmation has been the dominant paradigm to explain the formation of consumer satisfaction for over 40 years. Within this paradigm, it is possible for expectations to have opposing effects on consumer satisfaction depending on the underlying psychological processes presupposed. In general, assimilation processes predict positive effects, while contrast processes predict negative effects. A comprehensive assessment of the empirical evidence for these positions is missing. Hence, we provide a meta-analysis of expectancy-disconfirmation research, using 150 records ( N = 58,597), to test the direct effects of perceived performance and performance expectations on consumer satisfaction, while also including disconfirmation as a mediator in each path (using meta-analytical path analysis). We found evidence for an overall positive relationship between expectations and consumer satisfaction ( r = .29 [0.24, 0.34]) and no evidence supporting contrast effects. Moderator analyses revealed that the positive correlation between performance expectations and consumer satisfaction was significantly stronger for predictive (vs. normative) expectations, for services (vs. goods), and for cross-sectional (vs. longitudinal and experimental) studies. Furthermore, we found an unexpected downward publication bias, which suggests that the true correlation between disconfirmation and consumer satisfaction is higher than the (already high) estimate we found. We discuss how future research can empirically scrutinize popular practitioner views and promote the development of causal explanations, account for non-linear effects, and elucidate the anomalous publication bias found here.

Abstract The growing gender polarization in consumers’ pro-environmental engagement—with women more engaged than men—suggests that organizations should consider gender a key criterion when targeting their cause-related marketing and social advocacy campaigns for environmental causes. However, multilevel analyses of 11 behavioral interventions across 63 countries ( N = 56,582) reveal that relying on gender alone is insufficient and can even backfire, uncovering a surprising paradox: The gender gap in pro-environmental engagement widens among liberal consumers, in societies with higher gender equality, and cultures emphasizing care over competition. These gender paradoxes emerge when identities and societal contexts intersect, revealing why interventions ignoring such complexities can fail. Results show that a collective action framing is effective across several identity combinations, while a negative emotional appeal can backfire, particularly among conservative men in gender-equal countries. A web-based tool helps marketers and policymakers select effective environmental interventions across intersecting individual and country-level factors, enabling targeted advocacy and cause-related marketing.

Abstract The use of social media influencers as persuasive marketing agents has become ubiquitous. However, a comprehensive understanding of their effectiveness, mechanisms, and moderation is still lacking. To address this gap, we conducted a meta-analysis of 71 papers, yielding 135 experimental studies and 571 effect sizes related to the impact of social media influencers compared to other forms of brand endorsements. Our results reveal that social media influencers significantly impact both consumer engagement and purchase intention, and they are relatively more effective than brand posts, virtual influencers, and celebrities. A meta-analytic structural equation model analyzing the influencing mechanisms suggests that social media influencers enhance consumer responses indirectly through their credibility and attractiveness. A meta-regression analysis further shows that various factors—including characteristics of the influencers, message, products, social media platforms, and followers, as well as their interaction with influencer size—moderate the effectiveness of social media influencers. Notably, our results indicate that influencer size can address some inconsistencies in previous research. For instance, small and medium-sized influencers are more effective in driving engagement, while larger influencers have greater impact on purchase intention. Our research provides novel, rich, and nuanced insights that can help managers with decisions such as: (a) when to choose influencers over alternatives, and (b) how to optimize their use.

Abstract Brands communicate who they are through visual content (e.g., images, videos). How does the visual complexity of such content shape perceived brand status (prestige, luxury)? This research examines two key aspects of visual complexity: edge complexity (edge density and irregularity) and color complexity (hue quantity and dissimilarity). Drawing on computer-vision analyses of over 400,000 visuals and a controlled experiment, the findings show that: (1) edge complexity exerts a U-shaped effect on perceived brand status, such that status perceptions are lowest at moderate levels of edge complexity and higher at low or high levels; (2) color complexity consistently reduces perceived brand status; and (3) these effects operate sequentially through perceived visual curation (how intentionally and professionally crafted a visual appears) and perceived exclusivity (how limited in availability the offering appears). Theoretical, methodological, and managerial implications are discussed.

Abstract This research examines the dynamic effects of video advertising features on viewers’ attentional focus. We leverage state-of-the-art computer vision techniques to extract frame-level measures of visual complexity and scene cuts, and we combine these with eye-tracking data that capture attention via moment-to-moment attentional synchrony across viewers. Our findings indicate that short and visually simple scenes elicit higher levels of attentional synchrony. A time-series analysis of 2,520 individual viewing experiences across 42 public service announcements, reveals that visual complexity exerts a delayed, negative effect on attentional synchrony, whereas scene cuts (i.e., shorter scene durations) boost attention. Together, these results demonstrate that short and simple scenes help sustain attentional focus, which subsequently enhances narrative immersion, ad liking, and recognition. Our new analytical framework illustrates how computer vision, time-series modeling, and neuromarketing measures can be effectively integrated to advance video advertising research, while also offering actionable guidance for marketers to optimize viewer attention.

Abstract Access-based consumption, defined as transactions that may be market mediated in which no transfer of ownership takes place, is conceptualized by Bardhi and Eckhardt (2012). While it was introduced to explore consumer engagement in the sharing economy, conceptually it challenges the dominant assumption of ownership in marketing. This paper reflects on the impact of ABC and its boundary conditions. We critically interrogate and expand on five challenges of the original concept: the static dichotomy of access versus ownership; its transactional framing; its lack of identity value; its treatment of ideology; and its reliance on one context. We discuss the implications of ABC for marketing research related to: a prosumer role of the consumer; its ambivalent responsibility and governance; the bundled, or layered notions of access/ownership for digital ownership; as well as its implications for platformized consumption, which reinforces its instrumental sociality, and where value is extracted through data rather than ownership.

Abstract Generative AI (Gen AI) is shaping the future of marketing. In the next decade, Gen AI will influence how marketers interact and communicate with customers, help create and deliver marketing content (text, images, and video), and inform methods for researching and developing new products and services. In both service and sales settings, Gen AI will affect customers directly and significantly. Therefore, marketers, researchers, and public policy makers require a clear understanding of Gen AI and its potential, as well as its limitations. To assist marketers in thinking through the adoption and implementation of Gen AI, the current article presents a four-quadrant organizing framework that highlights trade-offs in both the nature of Gen AI inputs and the extent of human augmentation needed to deliver Gen AI–generated outputs. This framework provides guidance for the selection and implementation of Gen AI tools, as well as recommendations for further research.