PreprintCited by 313Psychology of Social InfluenceAI in Service InteractionsEthics and Social Impacts of AI

The Potential of Generative AI for Personalized Persuasion at Scale

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Matz, Sandra, Teeny, Jake, Vaid, Sumer Sumeet, Peters, Heinrich, Harari, Gabriella M., Cerf, Moran·2023·Scientific Reports

Abstract

Matching the language or content of a message to the psychological profile of its recipient (known as “personalized persuasion”) is widely considered to be one of the most effective messaging strategies. We demonstrate that the rapid advances in large language models (LLMs), like ChatGPT, could accelerate this influence by making personalized persuasion scalable. Across four studies (consisting of seven sub-studies; total N = 1,788), we show that personalized messages crafted by ChatGPT exhibit significantly more influence than non-personalized messages. This was true across different domains of persuasion (e.g., marketing of consumer products, political appeals for climate action), psychological profiles (e.g., personality traits, political ideology, moral foundations), and when only providing the LLM with a single, short prompt naming or describing the targeted psychological dimension. Thus, our findings are among the first to demonstrate the potential for LLMs to automate, and thereby scale, the use of personalized persuasion in ways that enhance its effectiveness and efficiency. We discuss the implications for researchers, practitioners, and the general public.

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  • Personalized marketing content is more effective than a one-content-fits-all approach.

    “or other personality traits as personalized marketing content is more effective than a one-content-fits-all approach (Matz et al. 2023).”

    From Generative AI (2024) · cites this paper as Matz et al. 2023

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Research works printed but not linked: 4

  1. Youyou, W., Kosinski, M. & Stillwell, D. Computers judge personalities better than humans. Proc. Natl. Acad. Sci. 112, 1036-1040 (2015).
  2. Stachl, C., et al. Behavioral Patterns in Smartphone Usage Predict Big Five Personality Traits (PsyArXiv, 2019).
  3. Matz, S. C., Kosinski, M., Nave, G. & Stillwell, D. Psychological targeting as an effective approach to digital mass persuasion. Proc. Natl. Acad. Sci. 20, 20 (2017).
  4. Fazio, R. H. & Olson, M. A. The MODE Model: Attitude-Behavior Processes as a Function of Motivation and Opportunity. In Dual- Process Theories of the Social Mind 155-171 (The Guilford Press, 2014).

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Authors
Matz, S., Teeny, J., Vaid, S. S., Peters, H., Harari, G. M., & Cerf, M.
Affiliations
  • Columbia University (US)
  • Harvard University (US)
  • Stanford University (US)
Corresponding author
Matz, Sandra
Venue
Scientific Reports
Published
2023-04-22
Volume
14
Issue
1
Pages
4692-4692
ISSN
2045-2322 (ISSN-L)
OpenAlex
W4392153984
Cited by
312
References
74
Citations by year
2026: 131 · 2025: 120 · 2024: 58 · 2023: 3
FWCI
220.91
Type
journal article
Language
en
Open access
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • OSF Preprints (OSF Preprints) (submittedVersion)
  • PsyArXiv (OSF Preprints) (submittedVersion)
  • PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
Topics
  • Social Sciences › Sociology and Political Science › Psychology of Social Influence
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
personalized persuasion, generative AI, large language models, ChatGPT, message tailoring, psychological profiling, persuasiveness, political appeal, climate action, political ideology, moral foundations, personality traits
MeSH terms
Climate, Language, Morals, Persuasive Communication, Marketing

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