Incentive Misalignments in Programmatic Advertising: Evidence from a Randomized Field Experiment

• 成果类型: Article
• 署名作者: Frick, Thomas W.; Belo, Rodrigo; Telang, Rahul
• 署名单位: Universidade Nova de Lisboa; Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam; Carnegie Mellon University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.4438
• 发表日期: 2023
• 页码: 1665-1686
• 关键词: economics of advertising; field experiment; incentive misalignment; programmatic advertising

摘要

In programmatic advertising, firms outsource the bidding for ad impressions to ad platforms. Although firms are interested in targeting consumers that respond positively to advertising, ad platforms are usually rewarded for targeting consumers with high overall purchase probability. We develop a theoretical model that shows if consumers with high baseline purchase probability respond more positively to advertising, then firms and ad platforms agree on which consumers to target. If, conversely, consumers with low baseline purchase probability are the ones for which ads work best, then ad platforms target consumers that firms do not want to target-the incentives are misaligned. We conduct a large-scale randomized field experiment, targeting 208,538 individual consumers, in a display retargeting campaign. Our unique data set allows us to both causally identify advertising effectiveness and estimate the degree of incentive misalignments between the firm and ad platform. In accordance with the contracted incentives, the ad platform targets consumers that are more likely to purchase. Importantly, we find no evidence that ads are more effective for consumers with higher baseline purchase probability, rendering the ad platform's bidding suboptimal for the firm. A welfare analysis suggests that the ad platform's bidding optimization leads to a loss in profit for the firm and an overall decline in welfare. To remedy the incentive misalignment, we propose a solution in which the firm restricts the ad platform to target only consumers that are profitable based on individual consumer-level estimates for baseline purchase probability and ad effectiveness.