More “Bank” for the Buck: Microtargeting and Normative Appeals to Increase Social Marketing Efficiency

Author:

Metcalf Alexander L.1ORCID,Angle Justin W.2,Phelan Conor N.1,Muth B. Allyson3,Finley James C.3

Affiliation:

1. W. A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA

2. College of Business, University of Montana, Missoula, MT, USA

3. Center for Private Forests, Penn State University, University Park, PA, USA

Abstract

Successful conservation in the United States relies on collective stewardship by millions of private landowners, challenging those agencies and nongovernment organizations tasked with engagement and outreach. Perennially limited resources compound this challenge, highlighting a deep need for efficient social marketing. In the following research, we test the efficacy of two social marketing strategies—microtargeting and normative appeals—through a randomized controlled trial of an integrated social marketing campaign targeting riparian landowners in the Pennsylvania portion of the Chesapeake Bay Watershed. We used a microtargeting algorithm to predict landowners’ likelihood of responding to a conservation outreach campaign to create treatment groups of high-likelihood prospects versus random prospects (i.e., no microtargeting). A normative appeal was also included as an experimental factor in the campaign communicating that forested riparian buffer investments were common among similar landowners. Among microtargeted landowners, we observed a 66% increase in response to a riparian restoration survey compared to the control group. Additionally, we found a significant influence of a normative message among random (nonmicrotargeted) prospects, increasing response by 23% over the control group. We conclude conservation outcomes may be more efficiently achieved by deploying these marketing techniques on a wider scale to a variety of conservation challenges.

Funder

Richard King Mellon Foundation

Publisher

SAGE Publications

Subject

Marketing,Economics and Econometrics

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