Lookalike Targeting on Others' Journeys: Brand Versus Performance Marketing

K. Sudhir (), Seung Yoon Lee and Subroto Roy
Additional contact information
K. Sudhir: Cowles Foundation and Yale School of Management, https://som.yale.edu/faculty/k-sudhir
Seung Yoon Lee: Yale School of Management
Subroto Roy: Dept. of Marketing, University of New Haven

No 2302R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: Lookalike targeting is a widely used model-based ad targeting approach that uses a seed database of individuals to identify matching “lookalikes” for targeted customer acquisition. An advertiser has to make two key choices: (1) who to seed on and (2) seed-match rank range. First, we find that seeding on others’ journey stage can be effective in new customer acquisition; despite the cold start nature of customer acquisition using Lookalike audiences, third parties can indeed identify factors unobserved to the advertiser that move individuals along the journey and can be correlated with the lookalikes. Further, while journey-based seeding adds no incremental value for brand marketing (click-through), seeding on more downstream stages improves performance marketing (donation) outcomes. Second, we evaluate audience expansion strategies by lowering match ranks between the seed and lookalikes to increase acquisition reach. The drop in effectiveness with lower match rank range is much greater for performance marketing than for brand marketing. Performance marketers can alleviate the problem by making the ad targeting explicit, and thus increase perceived relevance; however, it has no incremental impact for higher match lookalikes. Increasing perceived targeting relevance makes acquisition cost comparable for both high and low match ranks.

Keywords: Digital advertising; Targeting; Algorithmic targeting; Lookalike targeting; Nonprofit marketing (search for similar items in EconPapers)
JEL-codes: C93 L31 M31 M37 (search for similar items in EconPapers)
Pages: 41 pages
Date: 2021-09, Revised 2022-06
New Economics Papers: this item is included in nep-mkt
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