Competitive Advertising on Brand Search: Traffic Stealing and Customer Selection

63 Pages Posted: 19 Jul 2018 Last revised: 16 May 2019

See all articles by Andrey Simonov

Andrey Simonov

Columbia University - Columbia Business School

Shawndra Hill

Microsoft Corporation - Microsoft Research, New York City

Date Written: May 14, 2019

Abstract

We study the effectiveness of competitive advertising on brand search using a large-scale randomized ad allocation on Bing. Competitors can steal traffic from the focal brand, and they steal an order of magnitude more clicks if the focal brand's link is exogenously removed from the top paid position (6-15% instead of 1-2% of traffic). The traffic stealing is primarily done by the competitor in the top paid link (6-9% of traffic). However, the probability of an immediate conversion on these ``stolen'' clicks is low, with 46% of consumers returning to Bing in less than 30 seconds after the click, compared to 3.5-6% for consumers clicking on the focal brand's link. The high probability of quick returns after a click on a competitors' link is due both to negative selection by customers and an incremental increase in the overall number of unsuccessful clicks, with the latter being consistent with both customer confusion and deliberate search. More relevant competitors get more clicks with lower quick-back probability. We discuss the implications of these results for the focal brand's and competitors' advertising strategies, propose an exclusive ad placement mechanism for the platform, and discuss the degree of customer confusion and the social costs imposed by competitive advertising.

Keywords: sponsored search, competitive advertising, brand advertising, customer confusion, adverse selection, field experiments

JEL Classification: M31, M37, D44

Suggested Citation

Simonov, Andrey and Hill, Shawndra, Competitive Advertising on Brand Search: Traffic Stealing and Customer Selection (May 14, 2019). Columbia Business School Research Paper No. 18-59. Available at SSRN: https://ssrn.com/abstract=3204394 or http://dx.doi.org/10.2139/ssrn.3204394

Andrey Simonov (Contact Author)

Columbia University - Columbia Business School ( email )

3022 Broadway
New York, NY 10027
United States

Shawndra Hill

Microsoft Corporation - Microsoft Research, New York City ( email )

641 Avenue of Americas
New York, NY 10011
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
227
Abstract Views
1,338
rank
144,259
PlumX Metrics