International Journal of Research in Marketing最新文献

Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Apple’s introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.

Advances in technology change the way consumers search and shop for products. Emerging is the trend of home-shopping devices such as Amazon’s Alexa and Google Home, which allow consumers to search or order products. We investigate how consumer brand and technology preferences may interact with the functionalities of technology-enabled shopping (TES) devices to determine the channel structure and market competition.

In specific, we break the functionalities of the TES devices into two: (1) the shopping support functionality (SSF), and (2) the ordering convenience functionality (OCF). Via a series of experiments, we document that stronger brand preferences are negatively correlated with the willingness to use a TES device that offers SSF. However, there is no association with brand preferences and desire to use a TES device when it offers OCF.

We build an analytical model integrating the findings from these experiments, and then derive the equilibrium channel and pricing strategies for two competing retailers. Our findings show that the functionality of TES devices results in vastly different distribution and pricing strategies in retail markets. In particular, consumers’ heterogeneous valuation of the SSF results in a monopolistic adoption of TES devices by the retailers in equilibrium, and generates Pareto improvements for both. In contrast, when the TES devices offer OCF, in equilibrium, retailers adopt TES channels competitively, resulting in a prisoners' dilemma outcome. In the extensions, studying a third-party technology developer's decision to invest in OCF and SSF technologies, we show that the contrast between the channel strategies under the OCF and the SSF also impact the incentives to develop TES. We show that in some cases, in an effort to mitigate downstream retail competition, the provider may prefer not to offer the best possible OCF technology to consumers. These findings shed light on the future adoption and the functionalities of shopping technologies offered by retailers.

As artificial intelligence (AI) applications proliferate, their creators seemingly anticipate that users will make similar trade-offs between costs and benefits across various commercial and public applications, due to the technological similarity of the provided solutions. With a multimethod investigation, this study reveals instead that users develop idiosyncratic evaluations of benefits and costs depending on the context of AI implementation. In particular, the tensions that drive AI adoption depend on perceived personal costs and choice autonomy relative to the perceived (personal vs. societal) benefits. The tension between being served rather than exploited is lowest for public AI directed at infrastructure (cf. commercial AI), due to lower perceived costs. Surveillance AI evaluations are driven by fears beyond mere privacy breaches, which overcome the societal and safety benefits. Privacy-breaching applications are more acceptable when public entities implement them (cf. commercial). The authors provide guidelines for public policy and AI practitioners, based on how consumers trade off solutions that differ in their benefits, costs, data transparency, and privacy enhancements.

The pandemic has led to a significant increase in the use of video conferencing platforms such as Zoom, Google Meet and Microsoft Teams. Yet little is known about the impact of video conferencing on subsequent consumer decisions. Across six studies, we examine the effects of video conferencing in both consumption (e.g., sales) and nonconsumption (e.g., school and work) contexts and find that video conferencing can trigger greater interest in products that can enhance the self - physically, intellectually, and/or mentally - due to heightened social appearance anxiety. This effect is attenuated when technology allows users to reduce social appearance anxiety (e.g., the use of ring lights or the ability to turn off web cameras) but accentuated when social anxiety is increased (e.g., the use gallery/speaker views) and is more pronounced among consumers who are low in self-esteem.

In this research, we examine the role of reviewer badges in the spread of opinion in the context of online reviews. Specifically, we investigate how ratings from badged and non-badged reviewers influence the opinions of subsequent reviewers, how this influence varies depending on whether the subsequent reviewer is badged, and the dynamics of review time and recent product popularity. Using a multimethod approach and archival data covering a two-year period of 458,305 reviews for products in both hedonic and utilitarian categories on Amazon (with data from TripAdvisor as a robustness check), we uncover several unique insights. First, badged reviewers tend to give lower ratings than non-badged reviewers. Second, prior ratings from badged reviewers have a smaller positive influence on subsequent reviewers than ratings from non-badged reviewers. Third, when we distinguish between badged and non-badged subsequent reviewers, we find that ratings from prior non-badged reviewers have a negative effect on ratings awarded by subsequent badged reviewers. These three effects are consistent with badged reviewers’ drive to differentiate their reviews. Finally, we find that badged reviewers tend toward stronger differentiation behavior when the reviewed product has recently become available online and when it has a high proportion of recent reviews from non-badged reviewers. The findings have important implications for marketing managers seeking to influence the review-generation process for their products and for platform managers working to incentivize the quantity and quality of reviews on their websites by awarding badges or other forms of recognition.

The literature on pharmaceutical marketing devotes little attention to the promotion of branded drugs after generic competitors enter the market. This paper addresses this gap in the literature and explores how the sales of branded drugs respond to specific promotional strategies following generic entry. We focus on physician detailing, and specifically, firms’ post-generic-entry decisions regarding overall detailing spending and physician-level allocation (i.e., which physicians to visit). We utilize a novel, custom-built dataset containing information on aggregate-level sales, prescriptions, and promotional budget for 72 brands and their competitors; our dataset further includes detailed physician-level data on detailing visits and prescription behavior for 25 of these brands. We first describe the detailing strategies that brands use in practice, and then analyze the outcomes associated with changes in detailing spending and allocation. Our analyses reveal that, on average, brands’ detailing spending decreases after generic entry, yet the ROI on such spending increases compared to before generic entry. Refocusing of detailing efforts after generic entry such that physicians with higher brand preference are targeted is more likely to lead to an increase in detailing ROI than other allocation strategies post entry. However, in practice, many brands do not undertake such reallocation and do not enhance their ROIs. Our findings are of clear practical relevance to manufacturers of branded drugs, as well as to policy makers who wish to curb detailing efforts for branded drugs when generic alternatives are available, so as to lower healthcare costs.

Customer Success (CS) Management is an emerging B2B marketing strategy. The task of CS management is to increase customer retention through dedicated and ongoing proactive attention to improving the value customers realize from a product or solution. Leveraging a theories-in-use approach, we demonstrate the adoption of CS management across a wide range of B2B settings and unpack how the implementation of a CS strategy can complement existing sales and service efforts to increase customer retention. We find that a central element to CS management is the tracking of customer health, which is a new marketing metric that is viewed as the pulse of CS strategy. Customer health is a formative metric comprised of objective and subjective data points that track (1) relationship quality, (2) product usage, and (3) customer value realization. CS managers leverage customer health data to proactively manage B2B relationships and reduce churn. While CS management has been widely adopted, we also find that not all CS implementations are initially successful. As such, we describe contingency factors related to short-term ambiguities within the organization and long-term factors that impact implementation of CS management. Given the nascent nature of research on CS management in the marketing literature, our article closes with a comprehensive set of future research opportunities and emerging challenges for firms focusing on customer success.