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Effect of temporal spacing between advertising exposures: Evidence from online field experiments

机译:广告曝光之间时间间隔的影响:在线现场实验的证据

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This paper aims to understand the impact of temporal spacing between ad exposures on the likelihood of a consumer purchasing the advertised product. I create an individual-level data set with exogenous variation in ad exposure and its spacing by running online field experiments. Using this data set, I first show that (1) ads significantly increase the likelihood of the consumers purchasing from the advertiser and (2) this increase carries over to future purchase occasions. Importantly, I also find evidence for the spacing effect: the likelihood of a product's purchase increases if it's ads are spread apart rather than bunched together, even if spreading apart involves shifting some ads away from the purchase occasion. Accounting for the spacing effect is important to detect the effects of repeated advertising. Because the traditional models of advertising do not explain the data patterns, I build a new memory-based model of how advertising influences consumer behavior. Using a nested test, I reject the restrictions imposed by the canonical goodwill stock model (Nerlove and Arrow, Economica, 29(114):129-142, 1962), in favor of the memory-based model I propose. Additionally, I use the estimated parameters to simulate counterfactual scenarios and show that the advertisers' profits might be lower if the features of the memory model are not accounted for.
机译:本文旨在了解广告曝光之间的时间间隔对消费者购买广告产品的可能性的影响。通过运行在线现场实验,我创建了一个个人级别的数据集,该数据集的广告展示率及其间隔存在外源性变化。使用该数据集,我首先表明(1)广告显着增加了消费者从广告商那里购买的可能性,并且(2)这种增加会延续到将来的购买场合。重要的是,我还发现了间距效应的证据:如果产品的广告分散而不是捆在一起,那么购买产品的可能性就会增加,即使分散涉及将某些广告从购买时机移开。考虑间距效应对于检测重复广告的效应很重要。因为传统的广告模型无法解释数据模式,所以我建立了一个基于内存的新模型来说明广告如何影响消费者的行为。使用嵌套测试,我拒绝了规范的商誉存量模型(Nerlove and Arrow,Economica,29(114):129-142,1962)施加的限制,转而支持我提出的基于内存的模型。此外,我使用估计的参数来模拟反事实场景,并表明如果不考虑内存模型的功能,广告商的利润可能会降低。

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