Journal of Interactive Marketing

Recent studies indicate that transparency about data collection practices for personalized advertising in the form of disclosures increases advertising effectiveness. This work, however, demonstrates that for advertising platforms with an untrustworthy reputation, personalization disclosures may backfire because the motives of placing such disclosures are perceived as insincere. Study 1 shows that a personalization disclosure framed as a warning that is placed alongside an advertisement by the untrustworthy platform itself decreases advertising effectiveness compared to when the personalization disclosure is placed by a more trusted third party. Notably, these effects of disclosure source decrease when the disclosure is merely framed as notification. Study 2 replicates this backfire effect for a different disclosure source and examines the underlying process. When a disclosure is placed by the untrustworthy platform itself, the effect of the disclosure backfires because the motives of placing the disclosure are perceived to be insincere, which decreases advertising effectiveness. When the disclosure source is external, the backfire effect reverses, decreasing the perceived insincerity of motives and increasing advertising effectiveness. Study 3 manipulates a fictive platform's trustworthiness and replicates the backfire effect, confirming the notion that especially for untrustworthy platforms placement of personalization disclosures by a company source decreases advertising effectiveness.

Buddies, serving as in-group influencers to aid demographically similar cobuddies, are extensively used in face-to-face support groups to enhance positive social influence. The authors examine the efficacy of buddies in online support groups and investigate underlying mediating processes using social network analysis. They observe what happens when members of support groups for quitting smoking, including members who are relatively active and less active in the group, after a few days are called on to be buddies and assigned to specific cobuddies. The findings indicate that, consistent with normative expectations for buddies, members form especially strong ties with their designated cobuddies. The more active buddies are in the group, the stronger the ties they form with their cobuddies and, in turn, their cobuddies form stronger ties with group members overall, which then relates to cobuddy goal attainment. The findings suggest that interactive marketers should consider using buddies in online support groups but observe activity levels before making buddy assignments, because positive outcomes are contingent on buddies being active in the group. Marketers should also ensure that online support group members post to everyone, not just their buddies, because ties formed among group members as a whole are crucial for goal attainment.

Predicting future purchase levels is an important and constant challenge for marketing professionals, as purchase patterns often vary over time and across customers. Moreover, purchases often follow individual and cross-sectional seasonal patterns, which affect forecasts of purchase propensity and customer dropout. The authors develop the hierarchical Bayesian seasonal model with dropout (HSMDO), which captures the interrelation between individual and cross-sectional seasonality, purchase, and dropout rates, with the aim of improving forecast accuracy at specific points in time. They perform (1) a parameter recovery analysis with synthetic data; (2) an empirical validation on three noncontractual retail data sets; (3) an analysis of different model variants to isolate the effects of dropout, seasonality, and hierarchical seasonality; and (4) a comparison with several probabilistic models from the marketing literature. The results demonstrate that the HSMDO provides increased forecast accuracy and that tracking errors decrease further with data exhibiting strong seasonality and high customer retention. The HSMDO yields a measure of individual seasonality that has high discriminative power even with sparse data sets and is useful to customer relationship management analysts for customer segmentation, portfolio management, and improvement in the timing of marketing actions.

Social media influencers (SMIs) have become an effective channel for reaching targeted customers. The present study explores the influence process of advertising recognition on consumer responses in the SMI marketing context. The authors examined an Instagram post featuring the endorsement of a brand and created an experimental design with four conditions related to advertising recognition and the parasocial relationship. Findings from a partial least squares structural equation modeling procedure indicate that advertising recognition results in overall negative consumer responses to SMI brand endorsements. The results also indicate parallel mediating effects of source credibility and attitude toward endorsements as well as moderating effects of the parasocial relationship and consumer skepticism toward influencer marketing. The study sheds light on the influence process of SMI brand endorsements and the boundary conditions under which consumer responses to advertising recognition are moderated.

This article highlights how social media data and language analysis can help managers understand brand positioning and brand competitive spaces to enable them to make various strategic and tactical decisions about brands. The authors use the output of topic models at the brand level to evaluate similarities between brands and to identify potential cobrand partners. In addition to using average topic probabilities to assess brands’ relationships to each other, they incorporate a differential language analysis framework, which implements scientific inference with multi-test-corrected hypothesis testing, to evaluate positive and negative topic correlates of brand names. The authors highlight the various applications of these approaches in decision making for brand management, including the assessment of brand positioning and future cobranding partnerships, design of marketing communication, identification of new product introductions, and identification of potential negative brand associations that can pose a threat to a brand's image. Moreover, they introduce a new metric, “temporal topic variability,” that can serve as an early warning of future changes in consumer preference. The authors evaluate social media analytic contributions against offline survey data. They demonstrate their approach with a sample of 193 brands, representing a broad set of categories, and discuss its implications.

Globally, consumers and firms are negotiating rising privacy expectations. This article advances research by developing a multidimensional privacy measure that captures the idea of privacy as an expectation to be left alone through control and access of their personal information, time, and space. Drawing on boundary regulation perspectives from law and environmental psychology, the authors conceptualize, develop, and measure the meeting privacy expectations (MPE) scale. Six studies show the reliability and stability of the 12-item MPE scale in depicting the three subdimensions and in meeting reliability and validity criteria. The results indicate that the MPE scale is not only distinct from previously established privacy scales but also a better predictor of behavioral intentions. Moreover, the scale is invariant across different cultures and influences cognitive trust and emotional violation. The authors find that meeting privacy expectations vary in their levels and outcomes cross-culturally. Marketers can use the MPE scale to globally track, assess, manage, and plan for meeting the changing consumer privacy expectations. The MPE scale is a good candidate to address the rising public policy issues related to privacy.

Previous interactive marketing literature has concluded that banner attributes are key drivers of ad effectiveness and online consumer behaviors. In particular, prior advertising studies have largely defined the two most commonly used ad appeals in online settings: hedonic (i.e., visually attractive, joy-focused, and interactive) and utilitarian (i.e., informative, convenient, and functional). However, no unanimous conclusions have been drawn about their effects on online consumer behavior. Furthermore, no studies have assessed the psychological mechanisms underlying the processing of hedonic and utilitarian banner ads, which could be crucial given the unconscious, internal, and introspective nature of ad evaluation and online purchasing decisions. In this research, the authors used neuroimaging (functional magnetic resonance imaging [fMRI]) to identify the neural mechanisms underlying the evaluation of hedonic and utilitarian banners. The results reveal that whereas hedonic layouts engage brain areas associated with reward, self-relevance, and emotion, utilitarian banner ads trigger brain networks related to object identification and recognition, reasoning, executive function, and cognitive control. This research also examines the extent to which neural data derived from processing hedonic and utilitarian banners complement the ability of self-reported banner effectiveness to predict online consumer behavior. The results reveal that neural data from banner appeals help predict between 9% and 18% of online consumer behavior beyond that indicated by the perceived ad effectiveness reported by consumers. Taken together, these results provide new insights into the connection between neuropsychological data and real-world online consumer behavior.

Marketing managers increasingly monitor their company's online reputation and respond to online consumer reviews on various digital platforms. The current literature provides valuable insights into effectively initiating management response (MR) to negative reviews. However, research on how companies should respond to positive reviews is limited, despite their prevalence in MR practice. In this study, we postulate that using humor in MR for positive reviews can be an effective response strategy to enhance positive attitudinal and behavioral responses. Drawing on parasocial interaction theory, we conducted a field investigation and two experimental studies to demonstrate that humorous (vs. humorless) MRs to positive reviews fostered perceived parasocial interaction between prospective consumers and brands, which enhanced brand attitude and purchase intention. Furthermore, the proposed effects were stronger for consumers with communal norms than for those with exchange norms. This research advances the emerging literature on MR to consumer reviews of different valences and suggests important guidelines for effective MRs.

To quickly develop awareness of time-limited offers, marketers use an increasing number of eWOM solicitations, whereby they ask their customers to spread statements to their friends and acquaintances about products or a company. Despite growing interest in this communication tool, very little is known about what makes an efficient solicitation strategy. This research examines the drivers of consumers’ willingness to generate solicited eWOM for a time-limited offer. Using an experimental framework, this research shows that the most efficient strategy for generating solicited eWOM when it is the most valuable is to solicit well before the deadline using a gain- (loss-) framing solicitation on engaged (nonengaged) individuals.

Many firms use augmented reality (AR) that projects lifelike product holograms into the physical environment to assist customers in bridging so-called “imagination gaps,” which can arise on their path to purchase. However, research has not yet studied whether and how AR might help customers address two pertinent sources of such imagination gaps: (1) increased cognitive load when evaluating multiple products together (e.g., in a bundle) and (2) extended physical distance to the point-of-sale (e.g., out-of-store, at home). Building on mental imagery theorizing, we explain how AR supports customers in bridging these gaps, and, through a series of field and experimental studies, we evidence effects on customer purchase intentions and behavior. Specifically, we show that AR-generated imagery of bundled (versus individual) products enhances intended and actual purchases at the point-of-sale. Furthermore, when deployed at distant points in the purchase funnel (out-of-store, at-home), AR increases purchases through improved self-projection, which we describe as the psychological mechanism customers use to mentally bridge distance to the point-of-sale. We qualify this mediating mechanism through an important moderating process, where the effect of AR-generated imagery on self-projection is suppressed for customers with a holistic (versus analytic) thinking style.