Cross Channel Effects of Search Engine Advertising on Brick & Mortar Retail Sales: Meta Analysis of Large Scale Field Experiments on Google.com

53 Pages Posted: 3 Nov 2015 Last revised: 3 Jun 2017

See all articles by Kirthi Kalyanam

Kirthi Kalyanam

Santa Clara University

John McAteer

Google Inc.

Jonathan Marek

Applied Predictive Technologies

James A Hodges

University of Minnesota - Minneapolis

Lifeng Lin

University of Minnesota - Minneapolis

Date Written: May 2017

Abstract

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 provides 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, 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: Cross Channel Advertising, Search Engine Advertising, Advertising Effectiveness, Causal Effects, Field Experiments, Meta Analysis, Replication, Hierarchical Bayes.

Suggested Citation

Kalyanam, Kirthi and McAteer, John and Marek, Jonathan and Hodges, James A and Lin, Lifeng, Cross Channel Effects of Search Engine Advertising on Brick & Mortar Retail Sales: Meta Analysis of Large Scale Field Experiments on Google.com (May 2017). Available at SSRN: https://ssrn.com/abstract=2684110 or http://dx.doi.org/10.2139/ssrn.2684110

Kirthi Kalyanam (Contact Author)

Santa Clara University ( email )

500 El Camino Real
Santa Clara, CA 95053
United States

John McAteer

Google Inc. ( email )

1600 Amphitheatre Parkway
Second Floor
Mountain View, CA 94043
United States

Jonathan Marek

Applied Predictive Technologies ( email )

James A Hodges

University of Minnesota - Minneapolis ( email )

110 Wulling Hall, 86 Pleasant St, S.E.
308 Harvard Street SE
Minneapolis, MN 55455
United States

Lifeng Lin

University of Minnesota - Minneapolis ( email )

A450 Mayo Building, MMC 303
420 Delaware Street SE
Minneapolis, MN 55455
United States

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