Quantitative Marketing and Economics

, Volume 16, Issue 1, pp 1–42 | Cite as

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

  • Kirthi Kalyanam
  • John McAteer
  • Jonathan Marek
  • James Hodges
  • Lifeng Lin
Article
  • 158 Downloads

Abstract

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.

Keywords

Search engine advertising Cross channel impact Field experiments Bayesian meta analysis Retail marketing Advertising Retail sales Replication 

JEL Classification

M31 M37 L86 C39 C21 C11 L81 

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Kirthi Kalyanam
    • 1
  • John McAteer
    • 2
  • Jonathan Marek
    • 3
  • James Hodges
    • 4
  • Lifeng Lin
    • 4
  1. 1.Santa Clara UniversitySanta ClaraUSA
  2. 2.Google Inc.Menlo ParkUSA
  3. 3.Applied Predictive TechnologiesArlingtonUSA
  4. 4.Division of BiostatisticsUniversity of MinnesotaMinneapolisUSA

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