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The generation Z audience for in-app advertising
Journal of Indian Business Research ( IF 2.1 ) Pub Date : 2021-02-18 , DOI: 10.1108/jibr-08-2020-0275
Charles Graham , Ffion Young , Ammarah Marjan

Purpose

The audience for in-app mobile advertising is comparable in size and viewing rate to that for TV but divides its attention across a highly fragmented selection of apps, each competing for advertiser revenue. In market, the assumption is that this audience is deeply segmented, allowing individuals to be contextually targeted on the apps that define their interests and needs. But that assumption is not supported by the Laws of Double Jeopardy and Duplication of Viewing which closely predict usage in most mass media. The purpose of this study is to benchmark in-app audiences against these laws to better understand market structure.

Design/methodology/approach

The authors collected nearly 3,000 h of screen time data from a panel of Generation Z respondents and tested the predictive validity of two models against observed interactions with 23 popular apps in six categories over a week.

Findings

Results show that contrary to industry assumptions, audience for in-app advertising is not segmented. Engagement on individual apps and audience sharing rates between apps and app formats is predicted well.

Research limitations/implications

Optimising in-app advertising for short-term activation only limits its potential for brand building. These findings encourage advertisers to schedule online campaigns for brand reach as well as sales lift, by advancing current understanding of audience behaviour.

Originality/value

Many authors have called for consistency in metrics to compare on- and off-line media performance. This study bridges that gap, demonstrating how reach and frequency measures could inform digital scheduling.



中文翻译:

应用内广告的 Z 世代受众

目的

应用内移动广告的受众在规模和观看率上与电视相当,但其注意力分散在高度分散的应用选择上,每个应用都在争夺广告商的收入。在市场上,假设这些受众是深度细分的,允许个人根据上下文定位到定义他们兴趣和需求的应用程序。但这一假设不受双重危险和重复观看定律的支持,这些定律与大多数大众媒体的使用密切相关。本研究的目的是根据这些法律对应用内受众进行基准测试,以更好地了解市场结构。

设计/方法/方法

作者从一组 Z 世代受访者那里收集了近 3,000 小时的屏幕时间数据,并在一周内针对观察到的与六个类别的 23 个流行应用程序的交互,测试了两个模型的预测有效性。

发现

结果表明,与行业假设相反,应用内广告的受众并未细分。可以很好地预测单个应用程序的参与度以及应用程序和应用程序格式之间的受众共享率。

研究限制/影响

为短期激活优化应用内广告只会限制其品牌建设的潜力。这些发现鼓励广告商通过提高对受众行为的当前理解来安排在线广告活动以提高品牌影响力和销售量。

原创性/价值

许多作者呼吁保持指标的一致性,以比较在线和离线媒体的表现。本研究弥合了这一差距,展示了覆盖范围和频率测量如何为数字调度提供信息。

更新日期:2021-02-18
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