Psychological Targeting

Psychological targeting is predicting a person's personality from digital traces and then tailoring a persuasive message to the prediction. The term is Sandra Matz's in the sense the industry uses. The first meta-analysis of the question, by Raphael Perla and colleagues, finds the prediction step modest, the targeting step indistinguishable from zero under the only design that can identify a personalisation effect, and the two chained together close to zero again.
What it is
That meta-analysis covers 41 studies across marketing, psychology and computer science, and splits the question into its two halves. On prediction, about five per cent of the variance in personality can be recovered from digital footprints once studies with data leakage are excluded. On targeting, only a third of eligible studies used a design capable of an unbiased estimate, and the difference is stark: three-quarters of the estimates from biased designs reached significance against under a fifth of those from the trait-by-treatment interaction design, whose pooled interval includes zero. The authors' reading is that previously reported targeting effects may have been capturing main effects of message design or of personality rather than any targeting benefit. Attenuating the targeting effect by realistic prediction accuracy gives an end-to-end effect close to zero, and their first practical recommendation is to prioritise advertisement quality over microtargeting.
In effect
The field's flagship result points the other way and is worth reading in full rather than in headline. Matz, Michal Kosinski, Gideon Nave and David Stillwell reached over 3.5 million individuals in three field experiments and reported up to 40 per cent more clicks and up to 50 per cent more purchases, which are the most favourable cells rather than the pooled estimates. Their own table shows the first study producing 390 purchases from over three million impressions and a flat null on clicks, the install effect in the second study driven only by the low-openness audience, and the third study comparing standard copy against one tailored message rather than matching anything. Two published critiques then attacked different things: Dean Eckles and colleagues showed the campaigns were not randomised, that platform optimisation produces imbalance in who sees what, and that biases of 25, 9 and 5 per cent would be enough to account for the three conversion results, while Byron Sharp and colleagues objected that two of the three studies compared targeted against deliberately mistargeted advertisements and that creative quality was never controlled. The authors replied to both in print.
What it does not say
It does not say psychological targeting does not work. The meta-analytic estimate under the identifying design cannot be distinguished from zero, which is a statement about what the evidence can resolve rather than a proof of absence, and the authors note that small positive effects could in principle accumulate at scale. It does not say Matz and colleagues were wrong: two sets of critics found two different problems, the authors answered both, and the meta-analysis excluded the largest study's arm on a stated statistical ground about converting rare-event odds rather than on any judgement about the work, which means the best-known study in the field sits outside the headline estimate. The honest sentence is that the flagship result is contested on design, on comparison and on analysis, and that nine years on, after the authors themselves invited replication in print, no direct replication could be located. The best positive result in reach, from Brahim Zarouali and colleagues, is political rather than commercial, measures persuasion on scales rather than money spent, and uses the congruent-against-incongruent comparison the critics object to.
Sources
- Perla, R., Maran, T., Bagci, B., Kraus, S., Kanbach, D. K., & Bouncken, R. B. (2026). "The (In)Effectiveness of Psychological Targeting: A Meta-Analytic Review." Psychology & Marketing, 43(3), 575-590. doi:10.1002/mar.70073. Full text read, open access. 41 studies. Online 28 October 2025, print issue March 2026.
- Matz, S. C., Kosinski, M., Nave, G., & Stillwell, D. J. (2017). "Psychological targeting as an effective approach to digital mass persuasion." PNAS, 114(48), 12714-12719. doi:10.1073/pnas.1710966114. Full text read, including Table 1 and the declared interests. Stillwell received revenue as owner of the myPersonality application until 2012; no author was compensated for the campaigns.
- Eckles, D., Gordon, B. R., & Johnson, G. A. (2018). "Field studies of psychologically targeted ads face threats to internal validity." PNAS, 115(23), E5254-E5255. doi:10.1073/pnas.1805363115. Full text read. Code archived at osf.io/y8nuk.
- Matz, S. C., Kosinski, M., Nave, G., & Stillwell, D. J. (2018). "Reply to Eckles et al." PNAS, 115(23), E5256-E5257. doi:10.1073/pnas.1806854115.
- Sharp, B., Danenberg, N., & Bellman, S. (2018). "Psychological targeting." PNAS, 115(34), E7890. doi:10.1073/pnas.1810436115. With Correction, PNAS, 115(39), E9257, doi:10.1073/pnas.1814739115, which records that the conflict of interest statement was omitted at publication and that the three authors are employed by an institute that receives funding from Facebook as well as its competitors. Printed as a disclosure; no inference is drawn from it.
- Matz, S. C., Kosinski, M., Nave, G., & Stillwell, D. J. (2018). "Reply to Sharp et al." PNAS, 115(34), E7891. doi:10.1073/pnas.1811106115.
- Zarouali, B., Dobber, T., De Pauw, G., & de Vreese, C. H. (2022). "Using a Personality-Profiling Algorithm to Investigate Political Microtargeting." Communication Research, 49(8), 1066-1091. doi:10.1177/0093650220961965. Sample sizes and effect sizes are not established and none is printed.