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Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com

机译:搜索引擎广告对实体零售的跨渠道影响:Google.com上的大规模现场实验的荟萃分析

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We investigate the cross channel effects of search engine advertising on Google.com on sales in brick and mortar retail stores. Obtaining causal and actionable estimates in this context is challenging: Brick and mortar store sales vary widely on a weekly basis; offline media dominate the marketing budget; search advertising and demand are contemporaneously correlated; and estimates have to be credible to overcome agency issues between the online and offline marketing groups. We report on a meta-analysis of a population of 15 independent field experiments, in which 13 well-known U.S. multi-channel retailers spent over $4 Million in incremental search advertising. In test markets category keywords were maintained in positions 1-3 for 76 product categories with no search advertising on these keywords in the control markets. Outcomes measured include sales in the advertised categories, total store sales and Return on Ad Spending. We estimate the average effect of each outcome for this population of experiments using a Hierarchical Bayesian (HB) model. The estimates from the HB model provide causal evidence that increasing search engine advertising on broad keywords on Google.com had a positive effect on sales in brick and mortar stores for the advertised categories for this population of retailers. There also was a positive effect on total store sales. Hence the increase in sales in the advertised categories was incremental to the retailer net of any sales borrowed from non-advertised categories. The total store sales increase was a meaningful improvement compared to the baseline sales growth rates. The average Return on Ad Spend (ROAS) is positive, but does not breakeven on average although several retailers achieved or exceeded break-even based only on brick and mortar sales. We examine the robustness of our findings to alternative assumptions about the data specific to this set of experiments. Our estimates suggest online and offline are linked markets, that media planners should account for the offline effects in the planning and execution of search advertising campaigns, and that these effects should be adjusted by category and retailer. Extensive replication and a unique research protocol ensure that our results are general and credible.
机译:我们调查了Google.com上搜索引擎广告对实体零售商店销售的跨渠道影响。在这种情况下,要获得因果关系和可行的估计是具有挑战性的:实体店的每周销售差异很大;线下媒体主导了营销预算;搜索广告和需求是同时相关的;并且估算值必须可信,才能克服在线和离线营销小组之间的代理问题。我们对15个独立的现场实验进行了荟萃分析,其中13个美国知名的多渠道零售商在增量搜索广告中花费了超过400万美元。在测试市场类别中,将关键字保留在76个产品类别的1-3位中,而在对照市场中没有针对这些关键字的搜索广告。衡量的结果包括广告类别中的销售额,商店总销售额和广告支出回报率。我们使用分级贝叶斯(HB)模型估计此实验群体每个结果的平均效果。 HB模型的估计提供了因果证据,表明针对该零售商群体的广告类别,越来越多的搜索引擎广告在Google.com上的广泛关键字上对实体店的销售产生了积极影响。对商店的总销售额也产生了积极影响。因此,从非广告类别借来的任何销售额中,广告类别的销售额增长对零售商而言是增量。与基线销售增长率相比,商店总销售增长是有意义的改进。平均广告支出回报率(ROAS)为正,但平均而言,收支平衡不会达到收支平衡,尽管一些零售商仅基于实体销售就能达到或超过收支平衡。我们检验了我们的发现对于针对这组实验的特定数据的替代假设的稳健性。我们的估计表明,在线和离线是相互关联的市场,媒体策划者应在搜索广告系列的规划和执行过程中考虑离线效应,并应根据类别和零售商来调整这些效应。广泛的复制和独特的研究方案确保我们的研究结果是通用且可信的。

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