Measuring Consumer Sensitivity to Audio Advertising: A Long-Run Field Experiment on Pandora Internet Radio

45 Pages Posted: 22 Apr 2018

See all articles by Ali Goli

Ali Goli

University of Washington - Michael G. Foster School of Business

Jason Huang

Uber

David Reiley

Pandora Media, Inc.; UC Berkeley School of Information

Nick Riabov

Netflix

Date Written: April 21, 2018

Abstract

A randomized experiment with almost 35 million Pandora listeners enables us to measure the sensitivity of consumers to advertising, an important topic of study in the era of ad-supported digital content provision. The experiment randomized listeners into nine treatment groups, each of which received a different level of audio advertising interrupting their music listening, with the highest treatment group receiving more than twice as many ads as the lowest treatment group. By maintaining consistent treatment assignment for 21 months, we measure long-run demand effects and find ad-load sensitivity three times greater than what we would have obtained from a month-long experiment. We show the negative impact on the number of hours listened, days listened, and probability of listening at all in the final month. Using an experimental design that separately varies the number of commercial interruptions per hour and the number of ads per commercial interruption, we find that listeners primarily respond to the total number of ads per hour, with a slight preference for more frequent but shorter ad breaks. Lastly, we find that increased ad load led to an increase in the number of paid ad-free subscriptions to Pandora, particularly among older listeners. Importantly, we show that observational methods often lead to biased or even directionally incorrect estimates of these effects, highlighting the value of experimental data.

Suggested Citation

Goli, Ali and Huang, Jason and Reiley, David H. and Riabov, Nickolai M., Measuring Consumer Sensitivity to Audio Advertising: A Long-Run Field Experiment on Pandora Internet Radio (April 21, 2018). Available at SSRN: https://ssrn.com/abstract=3166676 or http://dx.doi.org/10.2139/ssrn.3166676

Ali Goli

University of Washington - Michael G. Foster School of Business ( email )

Box 353200
Seattle, WA 98195-3200
United States

Jason Huang

Uber ( email )

1455 Market St
San Francisco, CA 94103-1331
United States

David H. Reiley (Contact Author)

Pandora Media, Inc. ( email )

2101 WEBSTER ST 16TH FLOOR
Oakland, CA 94612
United States

UC Berkeley School of Information ( email )

102 South Hall
Berkeley, CA 94720-4600
United States

Nickolai M. Riabov

Netflix ( email )

Los Gatos, CA
United States

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