Lookalike Targeting on Others' Journeys: Brand Versus Performance Marketing

K. Sudhir (), Seung Yoon Lee and Subroto Roy
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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 2302, 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 assess if and how seeding by others' journey stages impact clickthrough (upstream behavior desirable for brand marketing) and donation (downstream behavior desirable in performance marketing). Overall, we find that lookalike targeting using other's journeys can be effective-third parties can indeed identify factors unobserved to the advertiser merely from others' journey stage to improve targeting. Further, while it is sufficient to seed on upstream journey stages for brand marketing, seeding on more downstream stages improves performance marketing outcomes. Second, we assess the effectiveness of expanding the target audience with lower match ranks between seed and lookalikes. The drop in effectiveness with lower match rank range is much greater for performance marketing (donation) than for brand marketing (click-through). However, performance marketers can alleviate the reduction in ad effectiveness for low match ranks by making targeting more salient; but increasing salience has little impact for high match rank. Overall, by increasing salience, performance marketers can make acquisition cost comparable for 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: 47 pages
Date: 2021-09
New Economics Papers: this item is included in nep-isf and nep-mkt
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