The Library
Overwhelming targeting options : selecting audience segments for online advertising
Tools
Ahmadi, Iman, Abou Nabout, Nadia, Skiera, Bernd, Maleki, Elham and Fladenhofer, Johannes (2024) Overwhelming targeting options : selecting audience segments for online advertising. International Journal of Research in Marketing, 41 (1). pp. 24-40. doi:10.1016/j.ijresmar.2023.08.004 ISSN 0167-8116.
|
PDF
WRAP-Overwhelming-targeting-options-selecting-audience-segments-online-advertising-23.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (917Kb) | Preview |
Official URL: http://doi.org/10.1016/j.ijresmar.2023.08.004
Abstract
Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Apple’s introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.
Item Type: | Journal Article | ||||||||
---|---|---|---|---|---|---|---|---|---|
Subjects: | H Social Sciences > HF Commerce | ||||||||
Divisions: | Faculty of Social Sciences > Warwick Business School | ||||||||
Library of Congress Subject Headings (LCSH): | Internet advertising, Internet marketing, Marketing -- Decision making | ||||||||
Journal or Publication Title: | International Journal of Research in Marketing | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 0167-8116 | ||||||||
Official Date: | March 2024 | ||||||||
Dates: |
|
||||||||
Volume: | 41 | ||||||||
Number: | 1 | ||||||||
Page Range: | pp. 24-40 | ||||||||
DOI: | 10.1016/j.ijresmar.2023.08.004 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Re-use Statement: | Data Availability: We provide the dataset necessary to replicate Study 2. Yet, we cannot share the dataset for the other two studies (Study 1 & 3) due to NDAs. | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Copyright Holders: | © 2023 The Author(s). Published by Elsevier B.V. | ||||||||
Date of first compliant deposit: | 10 August 2023 | ||||||||
Date of first compliant Open Access: | 11 August 2023 | ||||||||
RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year