Television ad-skipping, consumption complementarities and the consumer demand for advertising

Tuchman, Anna; Nair, Harikesh S.; Gardete, Pedro M.

doi:10.1007/s11129-017-9192-y

Cited by 53 publications

(22 citation statements)

References 37 publications

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“…For example, if a digital advertising platform is paid per click, the platform attempts to show ads to consumers with high predicted click probabilities, creating another source of confounding variation. Strategic consumer behavior . Consumers may pay attention to, or withhold attention from, advertisements according to ingrained habits or their valuation of the ad content (Becker and Murphy 1993; Tuchman, Nair, and Gardete 2018). As a result, it may be difficult for advertisers to distinguish incremental effects of ads from consumers’ baseline propensities to attend to the brand’s ads.…”

Section: Digital Advertising Effect Measurementmentioning

confidence: 99%

“…Strategic consumer behavior. Consumers may pay attention to, or withhold attention from, advertisements according to ingrained habits or their valuation of the ad content (Becker and Murphy 1993;Tuchman, Nair, and Gardete 2018). As a result, it may be difficult for advertisers to distinguish incremental effects of ads from consumers' baseline propensities to attend to the brand's ads.…”

Section: Measurement Challengesmentioning

confidence: 99%

See 1 more Smart Citation

Inefficiencies in Digital Advertising Markets

Gordon¹,

Jerath

Katona

et al. 2020

Journal of Marketing

112

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Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research.

show abstract

Section: Digital Advertising Effect Measurementmentioning

confidence: 99%

Section: Measurement Challengesmentioning

confidence: 99%

Inefficiencies in Digital Advertising Markets

Gordon¹,

Jerath

Katona

et al. 2020

Journal of Marketing

112

View full text Add to dashboard Cite

show abstract

“…Finer targeting affords better opportunities to incorporate individual households' past viewing and purchase data in targeting decisions. In this regard, the most closely related study is that of Tuchman, Nair, and Gardete (2017), who explore implications of individual-level targeting to consumers who are less likely to avoid the targeted advertisements and have a positive marginal advertising effect on purchase. One key point of departure in our analysis is that we model instantaneous show viewing, which enables us to forecast whether an advertisement is viewed at a given point in time.…”

Section: Relevant Literaturementioning

confidence: 99%

“…Second, the targeting strategies we propose do not consider potential complementarities between the consumption of goods and advertisements (Becker and Murphy 1993). According to a recent study by Tuchman, Nair, and Gardete (2017), the quantity of the advertised product purchased recently can explain advertising avoidance rates. These authors suggest that advertising efficacy depends on the compliance of the targeted households and that the firm can target the subset of households whose purchases and welfare will likely change in response to the advertising campaign.…”

Section: Advance Buymentioning

confidence: 99%

TV Viewing and Advertising Targeting

Deng

Mela²

2018

Journal of Marketing Research

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Television, the predominant advertising medium, is being transformed by the microtargeting capabilities of set-top boxes (STBs). By procuring impressions at the STB level (often denoted “programmatic television”), advertisers can now lower per-exposure costs and/or reach viewers most responsive to advertising creatives. Accordingly, this study uses a proprietary, household-level, single-source data set to develop an instantaneous show and advertisement viewing model to forecast consumers' exposure to advertising and the downstream consequences for impressions and sales. Viewing data suggest that person-specific factors dwarf brand- or show-specific factors in explaining advertising avoidance, thereby suggesting that device-level advertising targeting can be more effective than existing show-level targeting. Consistent with this observation, the model indicates that microtargeting lowers advertising costs and raises incremental profits considerably relative to show-level targeting. Further, these advantages are amplified when advertisers can buy in real time as opposed to up front.

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“…However the user and the accessing the internet in general can be located in anywhere of the world [9]. The purchasing advertisements cannot justify at present in many advertisers particularly local advertisers because the advertisers may far beyond the advertiser's area [10]. These type of advertisements are may reflect their potential of global reach and also they have no guarantee.…”

Section: Introductionmentioning

confidence: 99%

Random Forest with Harmony Search Optimization for Location Based Advertising

Rohilla¹,

Chakraborty²,

Kumar³

2019

IJITEE

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Location based services are essential for the mobile user for obtaining the information based on the specific location. Initially, the location information is obtained using the GIS system for getting accurate information about the location. Then relevant information is extracted based on the location then the features are extracted from the dataset. Extracted features are segmented in order to simplify the process of location based advertising. The segmented features are used for simplifying the processing of retrieved data. The random forest algorithm is utilized to effectively retrieve the user data. It is one of the Meta heuristic algorithms which provide best result for the retrieval process. The optimal solution is needed for the designed algorithm for the purpose of avoiding local optimization, thus it improves the performance with respect to accuracy. The optimization algorithm Harmony search is used for getting optimal result based on the location. The exact information for the query is obtained for the proposed approach based on the location.

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Television ad-skipping, consumption complementarities and the consumer demand for advertising

Cited by 53 publications

References 37 publications

Inefficiencies in Digital Advertising Markets

Inefficiencies in Digital Advertising Markets

TV Viewing and Advertising Targeting

Random Forest with Harmony Search Optimization for Location Based Advertising

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