The Unfavorable Economics of Measuring the Returns to Advertising

S-Tier
Journal: Quarterly Journal of Economics
Year: 2015
Volume: 130
Issue: 4
Pages: 1941-1973

Authors (2)

Randall A. Lewis (Google, Inc.) Justin M. Rao (not in RePEc)

Score contribution per author:

4.022 = (α=2.01 / 2 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Twenty-five large field experiments with major U.S. retailers and brokerages, most reaching millions of customers and collectively representing $2.8 million in digital advertising expenditure, reveal that measuring the returns to advertising is difficult. The median confidence interval on return on investment is over 100 percentage points wide. Detailed sales data show that relative to the per capita cost of the advertising, individual-level sales are very volatile; a coefficient of variation of 10 is common. Hence, informative advertising experiments can easily require more than 10 million person-weeks, making experiments costly and potentially infeasible for many firms. Despite these unfavorable economics, randomized control trials represent progress by injecting new, unbiased information into the market. The inference challenges revealed in the field experiments also show that selection bias, due to the targeted nature of advertising, is a crippling concern for widely employed observational methods. JEL Codes: L10, M37, C93.

Technical Details

RePEc Handle
repec:oup:qjecon:v:130:y:2015:i:4:p:1941-1973
Journal Field
General
Author Count
2
Added to Database
2026-01-25