Multiobjective Personalization of Marketing Interventions

Omid Rafieian (), Anuj Kapoor () and Amitt Sharma ()
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Omid Rafieian: Marketing, Cornell Tech and SC Johnson College of Business, Cornell University, New York, New York 10044
Anuj Kapoor: Department of Marketing, University of Missouri, Columbia, Missouri 65203
Amitt Sharma: vdo.ai, Vancouver, British Columbia V5Y 0E3, Canada

Marketing Science, 2025, vol. 44, issue 2, 457-477

Abstract: Marketing interventions usually affect multiple outcomes of interest. However, finding an intervention that improves all desired outcomes is often rare, creating a trade-off for managers and decision makers. In this paper, we develop a multiobjective personalization framework that identifies personalized policies to balance multiple objectives at the individual level. We apply our framework to a canonical example of multiobjective conflict between sponsored and organic content consumption outcomes. Partnering with vdo.ai , we conduct a field experiment and randomly assign users to the skippable/long and nonskippable/short versions of the same ad. We document substantial substitution between sponsored and organic content consumption; the version that increases sponsored consumption reduces organic consumption. We find that multiobjective personalized policies can significantly improve both sponsored and organic consumption outcomes over single-objective policies. We show that compared with a single-objective policy optimized for organic consumption, there exists a multiobjective policy that increases sponsored consumption by 61% at the expense of only a 4% decrease in organic consumption. Similarly, compared with the single-objective policy optimized for sponsored consumption, there is a multiobjective policy that increases organic consumption by 53% while decreasing sponsored consumption by just 15%.

Keywords: multiobjective personalization; causal inference; machine learning; field experiments; video advertising (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:44:y:2025:i:2:p:457-477

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