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In this study, we capture the trade-off between effective and annoying display advertising. We investigate both the enduring impact of display advertising on consumers' purchase decisions and the potential of persistent display advertising to stimulate annoyance in consumers. Additionally, we study the structural dynamics of these advertising effects by allowing them to be contingent on the latent state of the purchase funnel in which each consumer resides. The findings, based on the hidden Markov model that we propose, demonstrate that a tension exists between generating interest and triggering annoyance in consumers; whereas display advertising has an enduring impact on transitioning consumers farther down the purchase funnel, persistent display advertising exposures beyond a frequency threshold can have an adverse effect by increasing the chances that consumers will be annoyed. Investigating the dynamics of these annoyance effects, we reveal that consumers who reside in different stages of the purchase funnel exhibit considerably different tolerance for annoyance stimulation. Our findings also reveal that the format of display advertisements and the level of diversification of ad creatives as well as consumer demographics moderate consumers' thresholds for annoyance elicitation. For instance, advertisers can reduce annoyance elicitation as a result of frequent display advertising exposures when they diversify the display ad creatives shown to consumers as well as when they use static rather than animated display ads. Digital advertisers often harness technology-enabled advertising-scheduling strategies, such as ad repetition at the individual consumer level, in order to improve advertising effectiveness. However, such strategies might elicit annoyance in consumers as indicated by anecdotal evidence, such as the popularity of ad-blocking technologies. Our study captures this trade-off between effective and annoying display advertising. We propose a hidden Markov model that allows us to investigate both the enduring impact of display advertising on consumers’ purchase decisions and the potential of persistent display advertising to stimulate annoyance in consumers. Additionally, we study the structural dynamics of these advertising effects by allowing them to be contingent on the latent state of the funnel path in which each consumer resides. Our findings demonstrate that a tension exists between generating interest and triggering annoyance in consumers; whereas display advertising has an enduring impact on transitioning consumers further down the purchase funnel, persistent display advertising exposures beyond a frequency threshold can have an adverse effect by increasing the chances that consumers will be annoyed. Investigating the dynamics of these annoyance effects, we reveal that consumers who reside in different stages of the purchase funnel exhibit considerably different tolerance for annoyance stimulation. Our findings also reveal that the format of display advertisements and the level of diversification of ad creatives as well as consumer demographics moderate consumers’ thresholds for annoyance elicitation. For instance, advertisers can reduce annoyance elicitation as a result of frequent display advertising exposures when they use static rather than animated display ads as well as when they diversify the display ad creatives shown to consumers. Our paper contributes to the literature on digital advertising and consumer annoyance and has significant managerial implications for the online advertising ecosystem.

Word of mouth (WOM) plays an increasingly important role in shaping consumers’ behavior and preferences. In this paper, we examine whether latent personality traits of online users accentuate or attenuate the effectiveness of WOM in social media platforms. To answer this question, we leverage machine-learning methods in combination with econometric techniques utilizing a novel quasi-experiment. Our analysis yields two main results. First, there is a positive and statistically significant effect of the level of personality similarity between two social media users on the likelihood of a subsequent purchase from a recipient of a WOM message after exposure to the WOM message of the sender. In particular, exposure to WOM messages from similar users in terms of personality, rather than dissimilar users, increases the likelihood of a postpurchase by 47.58%. Second, there are statistically significant effects of specific pairwise combinations of personality characteristics of senders and recipients of WOM messages on the effectiveness of WOM. For instance, introverted users are responsive to WOM, in contrast to extroverted users. Besides this, agreeable, conscientious, and open social media users are more effective disseminators of WOM. In addition, WOM originating from users with low levels of emotional range affects similar users, whereas for high levels of emotional range, increased similarity usually has the opposite effect. The examined effects are also of significant economic importance, as, for instance, a WOM message from an extrovert user to an introvert peer increases the likelihood of a subsequent purchase by 71.28%. Our findings are robust to several alternative methods and specifications, such as controlling for latent user homophily and network structure roles based on deep-learning models. By extending the characteristics that have been theorized to affect the effectiveness of WOM from the observable to the latent space, tapping into users’ latent personality characteristics, and illustrating how companies can leverage the abundance of unstructured data in social media, our paper provides actionable insights regarding the future potential of social media advertising and advanced microtargeting based on big data and deep learning. The online appendix is available at https://doi.org/10.1287/isre.2017.0768 .

The increasing availability of individual-level data has raised the standards for measurability and accountability in digital advertising. Using a massive individual-level data set, our paper captures the effectiveness of display advertising across a wide range of consumer behaviors. Two unique features of our data set that distinguish this paper from prior work are (1) the information on the actual viewability of impressions as on average 55% of the display ads are not rendered viewable and (2) the duration of exposure to the display advertisements, both at the individual-user level. Employing a quasi-experiment enabled by our setting, we use difference-in-differences and corresponding matching methods as well as instrumental variable techniques to control for unobservable and observable confounders. We empirically demonstrate that mere exposure to display advertising increases users’ propensity to search for the brand and the corresponding product; consumers engage both in active search exerting effort to gather information, and in passive search using information sources that arrive exogenously. We also find statistically and economically significant effects of display advertising on increasing consumers’ propensity to make a purchase. Furthermore, our findings reveal that the longer the duration of exposure to display advertising, the more likely the consumers are to engage in direct search behaviors (e.g., direct visits) rather than indirect ones (e.g., search engine inquiries). We also study the effects of various types of display advertising (e.g., prospecting, retargeting, affiliate targeting, video advertising, etc.) and the different goals they achieve. Our framework for evaluating display advertising effectiveness constitutes a stepping stone toward causally addressing the digital attribution problem.

The increasing availability of individual-level data has raised the standards for measurability and accountability in digital advertising. Using a massive individual-level data set, our paper captures the effectiveness of display advertising across a wide range of consumer behaviors. Two unique features of our data set that distinguish this paper from prior work are (1) the information on the actual viewability of impressions as on average 55% of the display ads are not rendered viewable and (2) the duration of exposure to the display advertisements, both at the individual-user level. Employing a quasi-experiment enabled by our setting, we use difference-in-differences and corresponding matching methods as well as instrumental variable techniques to control for unobservable and observable confounders. We empirically demonstrate that mere exposure to display advertising increases users’ propensity to search for the brand and the corresponding product; consumers engage both in active search exerting effort to gather information, and in passive search using information sources that arrive exogenously. We also find statistically and economically significant effects of display advertising on increasing consumers’ propensity to make a purchase. Furthermore, our findings reveal that the longer the duration of exposure to display advertising, the more likely the consumers are to engage in direct search behaviors (e.g., direct visits) rather than indirect ones (e.g., search engine inquiries). We also study the effects of various types of display advertising (e.g., prospecting, retargeting, affiliate targeting, video advertising, etc.) and the different goals they achieve. Our framework for evaluating display advertising effectiveness constitutes a stepping stone toward causally addressing the digital attribution problem.