Multi-Objective Personalization of Marketing Interventions

55 Pages Posted: 30 Mar 2023 Last revised: 18 Oct 2024

See all articles by Omid Rafieian

Omid Rafieian

Cornell University - Cornell Tech NYC; Cornell SC Johnson College of Business

Anuj  Kapoor

Indian Institute of Management Ahmedabad

Amitt Sharma

vdo.ai

Date Written: March 21, 2023

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 multi-objective personalization framework that identifies personalized policies to balance multiple objectives at the individual level. We apply our framework to a canonical example of multi-objective 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 Non-Skippable/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 multi-objective personalized policies can significantly improve both sponsored and organic consumption outcomes over single-objective policies. We show that compared to a single-objective policy optimized for organic consumption, there exists a multi-objective policy that increases sponsored consumption by 61% at the expense of only a 4% decrease in organic consumption. Similarly, compared to the single-objective policy optimized for sponsored consumption, there is a multi-objective policy that increases organic consumption by 53% while decreasing sponsored consumption by just 15%.  

Keywords: video advertising, ad skippability, multi-objective personalization, causal inference, machine learning, field experiments

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JEL Classification: M31, M37, C93, C22

Suggested Citation

Rafieian, Omid and Kapoor, Anuj  and Sharma, Amitt, Multi-Objective Personalization of Marketing Interventions (March 21, 2023). Available at SSRN: https://ssrn.com/abstract=4394969 or http://dx.doi.org/10.2139/ssrn.4394969

Omid Rafieian (Contact Author)

Cornell University - Cornell Tech NYC ( email )

2 West Loop Rd.
New York, NY 10044
United States

Cornell SC Johnson College of Business ( email )

Ithaca, NY 14850
United States

Anuj  Kapoor

Indian Institute of Management Ahmedabad ( email )

Vastraour
Ahmedabad, 380015
India

Amitt Sharma

vdo.ai

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