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 nd 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. |