Data-driven digital advertising: benefits and risks of online behavioral advertising | Emerald Insight

Prior research came up with complex theoretical frameworks that explain antecedents of OBA focusing only on ethical issues in marketing, on the effectiveness of a single OBA campaign or on how to create a successful advertising campaign. However, no study focuses on the intended or actual behavior of shoppers. Specifically, filling the gap in the existing literature, our research applies an SEM approach to identify both benefits and risks and the antecedents of the actual behavior of individuals in terms of actual purchases promoted by OBA.

OBA is a controversial type of advertising that activates opposing reactions on consumers’ perspective. Specifically, acceptance of the OBA is positively related to relevance, usefulness and credibility of the personalized advertisements, while the intention to avoid personalized ads is strictly related to the privacy concerns. Consequently, OBA acceptance and avoidance affected the click intention on the ad and the behavioral intention that are decisive for the success of data-driven digital advertising.

The research aims to investigate how individuals can be persuaded to make purchases through repeated and personalized messages. Specifically, the study proposes a framework of the potential benefits and risks of the online behavioral and data-driven digital advertising (OBA), which can help researchers and practitioners to better understand shopping behavior in the online retailing setting. In addition, the research focuses on the role of privacy concerns in affecting avoidance or adoption of OBA.

Copyright © 2021, Simone Aiolfi, Silvia Bellini and Davide Pellegrini

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Conclusions and implications

Our research makes a number of theoretical contribution and significant managerial implications. On the theoretical perspective, our work may contribute to advance the state of knowledge about personalized and data-driven digital advertising and its application in the new online retail environment. Prior research came up with theoretical frameworks that explain antecedents of OBA focusing only on ethical issues in marketing (Boerman et al., 2017) or only on the effectiveness of a single OBA campaign or how to create a successful advertising campaign (Varnali, 2019). Literature identifies factors controlled by advertisers and factors controlled by consumers in order to create comprehensive theoretical frameworks of the effectiveness of the OBA. However, besides being complex models, no study focuses on the intended or actual behavior of shoppers. Specifically, any research applies an SEM approach in order to identify the antecedents of the actual behavior of individuals in terms of actual purchases of products or services promoted by OBA. Filling the gap in the existing literature, the research, through an SEM approach, seeks to build up a simplified model that considers both the benefits (relevance, credibility and perceived usefulness of personalized online behavioral advertising) and the risks (privacy and ethical concerns) of the OBA.

According to prior studies, our research demonstrates how OBA is a controversial type of advertising. In fact, it activates opposing reactions on consumers’ perspective: relevance, usefulness and credibility on the one hand, and concerns and intrusiveness on the other. Acceptance of the OBA is positively related to the relevance and the credibility of the personalized advertisements, intended as the reliability and capability of the OBA of being a significant guide into the purchasing process, while the intention to avoid personalized ads is strictly related to the concerns for privacy. Consequently, acceptance and avoidance of OBA affected (positively and negatively respectively) the intention to click on the ad and the behavioral intention confirming a direct effect of click intention on behavioral intention, signal that they are decisive for the success of the data-driven digital advertising. Specifically, as far as OBA is concerned, behavioral intention refers to the likelihood that users would click on the ads and make a product purchase. Thus, our findings are consistent with literature that examined the effects of OBA on purchase intentions and actual purchases and identified the intention to click as an excellent predictor of the behavior in the stage of a consumer’s purchasing process (Urban et al., 2014): if the level of click intention increases, the likelihood of purchasing a product increases, and vice versa.

On the managerial perspective, the research suggests marketers to focus attention on relevance and credibility of advertising messages rather than worry about privacy.

Although concern for privacy is one of the central problems for the digital advertising industry as well as one of the negative effects of the OBA, our findings show that privacy affects OBA acceptance, but this, in turn, has no effect on click intention. This result can be consistent with the possible effect of the so-called privacy paradox, that is, that people say they care about their privacy and are not willing to share their information, but actually, they give their data in exchange for small benefits or for convenience (Norberg et al., 2007). Thus, although people say they are opposed to the OBA, they do not take measures to protect their data and they click on the ads or accept cookies managed by websites. Therefore, people are worried by privacy risks, but express the opposite. Thus, negative perceptions about the OBA are not in line with consumers’ actual behavior or their expectations (Boerman et al., 2017). However, due to its privacy implications, the OBA will soon enter the political agenda of several states, forcing companies to increase transparency and ensure greater data protection (Boerman et al., 2017).

Our research should help advertisers consider the level of ad personalization since ads perceived as too personal could be perceived as too intrusive and, consequently, lead to lower levels of click intentions and purchases. Consumers, indeed, will tend to accept OBA only if the benefits outweigh the costs. Therefore, our research suggests marketers to invest in the relevance and credibility of OBA messages.

Specifically, the topic of relevance underlines the importance of big data analytics, a necessary condition for creating personalized content and messages. Therefore, as a result of digitalization, it becomes essential for companies to invest in big data analytics and hire specialized personnel able to manage the personalization of data-driven digital advertising.

In addition, the positive effect of the message’s credibility on OBA acceptance suggests companies pay attention to the choice of information sources and intermediaries, especially nowadays when the consumer is more informed, critical and wary. In this panorama emerges the figure of the influencer, often considered more credible and reliable than the company itself, to which companies could turn in the future to improve the credibility of messages conveyed to the market.

To conclude, the Internet and new media have changed individuals’ habits and the way they use advertising messages, revolutionizing the way companies invest, promote and define measurement metrics, and despite its negative effects, personalized and data-driven digital advertising seems to be the future of advertising.

Limitations and future research

Some limitations are associated with the online survey and the sample size. First, respondents may have been influenced by the presence of the visual stimulus and then distorted the answers in order to accomplish the research. Another concern is about the generalizability of the results. Our sample, interviewed online, is probably neither truly random nor necessarily representative of any larger population. Although some authors identified our sample of 128 respondents as acceptable for a PLS approach to structural equation model (Boomsma, 1982, 1985; Hair et al., 2016), we intend, for future research, to enlarge the sample.

In addition, some relationships in our model may have been influenced by the level of familiarity of users with the context in which the personalized ad is inserted, namely, the Zalando company. Specifically, if respondents are not familiar with the company, it becomes difficult for them to evaluate the level of usefulness of the personalized ad. This limit should be overcome by measuring the familiarity with the company presented in the ad or keeping under control its effects with an experimental approach. This latter approach could let research overcome other limitations related to the proposed research and contextual aspects such as the effect of the level of consciousness of targeting tactic. In the proposed model, we are not able to measure the different levels of consciousness of the targeting tactic, and so we cannot include this variable in this specific mode. However, we intend to consider this issue in future research and future SEM models by considering the level of consciousness of the targeting tactic (or better the awareness of the OBA tactic) as a moderator or control variable. Our study, in fact, is a type of stimulus-response model based on framing a situation, but no comparisons are provided with a frameless approach. This is a weakness of the methodology that should be overcome through experimental approach. In addition, in order to simplify the model, we considered only the most cited variables and potentially we may have overlooked other variables affecting the outcomes of the OBA. For example, consumers’ perception of the OBA might also depend on individual characteristics, such as age or familiarity with the online environment. Specifically, future research should investigate if younger people are less likely to avoid the OBA compared to older ones, or vice versa. In addition, researchers might investigate deeply if the OBA has a positive effect on people with high levels of online experience and vice versa, or if its effects might change according to different levels of privacy concerns.

Finally, we invite all the researchers who want to investigate this topic to adopt a general framework on digital communications that could grant an excellent opportunity for a deeper discussion of related topics that might be considered in the effect of OBA on purchase intentions such as multiple touchpoints, attribution, social media and influencer marketing.