Using Internet Behavior to Deliver Relevant Television Commercials

Bellman, Steven; Murphy, Jamie; Treleaven-Hassard, Shiree; O'Farrell, James; Qiu, Lili; Varan, D.

doi:10.1016/j.intmar.2012.12.001

Cited by 25 publications

(12 citation statements)

References 54 publications

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“…Many studies agree that the relevance of an ad is one of the main reasons for which OBA could excel in performance compared with non-personalized ads. According to Bellman et al (2013), changes in the relevance of an ad affect the attention and exposure to it. This is consistent with the elaboration likelihood model, so that the more personal and relevant a massage is, the more likely the message is to be noticed, making it more effective (Petty et al, 1983).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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

Aiolfi

Bellini

Pellegrini

2021

IJRDM

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PurposeThe 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.Design/methodology/approachThe authors apply a structural equation modeling (SEM) approach with partial least square (PLS) regression method to test the research hypotheses through data coming from a structured questionnaire.FindingsOBA 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.Originality/valuePrior 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.

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Section: Theoretical Backgroundmentioning

confidence: 99%

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

Aiolfi

Bellini

Pellegrini

2021

IJRDM

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“…There is already some research on this topic (e.g. Bellman et al 2013). RQ6: Past behavioural and third-party data have been used for years in direct marketing.…”

Section: Rq1mentioning

confidence: 99%

Understanding programmatic TV advertising

Malthouse

Masłowska

Franks

2018

International Journal of Advertising

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Television is undergoing tremendous technological developments, which will enable marketers to direct commercial messages to more specific audiences at the individual and/or household level. Traditional ways of buying TV advertising are being challenged by the programmatic approach, which originated with search and display ads, and uses data and technology and real-time auctions to automate transactions between buyers and sellers. We discuss the changes to TV that enable the rise of programmatic models and propose that its future success depends on the coordination and availability of three factors, abbreviated DAD: distribution, ad inventory and data. We also elaborate on the effects of media context and how the TV program environment matters for advertising effectiveness. Finally, we discuss the future of TV advertising and related research needs.

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“…The lower sensitivity to in-store incentives in the online environment calls for promotional tactics that are better tailored to the specific online environment (e.g., personalized promotions, cross-selling opportunities, tailored in-store displays; Bellman et al 2013;Breugelmans and Campo 2011;Punj 2011) and that may stimulate purchases of impulse categories in the online channel. In addition, marketing communication can play an important role in reducing the perceived risk and uncertainty of online purchases and help customers to adjust decision rules to the new shopping environment (Weathers et al 2007).…”

Section: Managerial Implicationsmentioning

confidence: 99%

Buying Groceries in Brick and Click Stores: Category Allocation Decisions and the Moderating Effect of Online Buying Experience

Campo

Breugelmans

2015

Journal of Interactive Marketing

108

120

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The large majority of online grocery shoppers are multichannel shoppers, who keep visiting offline grocery stores to combine convenience advantages of online shopping with selfservice advantages of offline stores. An important retail management question, therefore, is how these consumers divide grocery purchases across the retailer's online and offline channel. We provide a comprehensive analysis of the impact of category characteristics on the allocation pattern of multichannel grocery shoppers, and find that category allocation decisions are not only affected by marketing mix differences between the online and offline channel, but also by intrinsic category characteristics like perceived purchase risk and shopping convenience. In addition, we examine the effect of online buying experience. In line with expectations, we find that it can affect allocation patterns in different ways: (i) it attenuates the perceived risk of buying sensory categories online, thereby reducing differences in online category share, (ii) it reinforces marketing mix (assortment) effects, thereby making online category share differences more pronounced, and (ii) it has no effect for factors such as promotions that are easy to evaluate without experience, thereby leaving the online category share stable. In addition to different experience effects across allocation factors, we also observe variations in experience effects across consumer segments.

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Using Internet Behavior to Deliver Relevant Television Commercials

Cited by 25 publications

References 54 publications

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

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

Understanding programmatic TV advertising

Buying Groceries in Brick and Click Stores: Category Allocation Decisions and the Moderating Effect of Online Buying Experience

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