Paid media and measurement · Large-scale randomized field experiment
Incentive Misalignments in Programmatic Advertising: Evidence from a Randomized Field Experiment
Frick, T. W., Belo, R., & Telang, R. (2023). Management Science, 69(3), 1665–1686.
Plain-English take
Ads increased purchase and return probabilities, but consumers targeted more aggressively were not more responsive to ads. For your marketing: Highlights the difference between predicting who will buy and identifying who changes behavior because of an ad.
How much weight to give this
4.5/5 Strong design for its specific question
The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.
Random assignment provides a strong comparison for effects in the tested setting.
Large sample reported (208,538); size alone does not guarantee a representative sample.
Randomized comparison; confirm the control condition and analysis in the paper.
This profile could be checked against an abstract or metadata, not the full paper.
Double-blind? Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used.
Research question
What the authors investigated
Do ad platforms target users who are persuadable, or users who were already likely to purchase?
Design
Randomized retargeting field experiment; consumers were assigned to retargeting ads or orthogonal public-service ads, with a separate welfare analysis.
Sample and setting
208,538 consumers eligible for retargeting at a European consumer-electronics e-retailer over 49 days.
Reported result
What the study found
Ads increased purchase and return probabilities, but consumers targeted more aggressively were not more responsive to ads. The authors estimate the platform's bidding optimization reduced advertiser profit and overall welfare by about 6% relative to a firm-optimal regime.
This is a paraphrase of the source. Check the original paper for definitions, estimates, statistical uncertainty and analysis details.
Scope and transfer
Limitations to keep in view
One retailer and one retargeting campaign. The design does not capture defensive advertising against competitors, and the analysis observes only winning bids.
Possible founder application
Highlights the difference between predicting who will buy and identifying who changes behavior because of an ad. Ask for incrementality tests and examine whether optimization targets persuadable users.
Evidence access
Publisher abstract; full text may require access
INFORMS publisher abstract retrieved with Firecrawl; sample, randomization, findings and stated limitations were available on the page.
If only an abstract or metadata was available, the profile is limited to claims supported there. A paper's paywall does not change its evidentiary status, but it limits what we can substantiate from accessible text.