Can Marketers Tailor Advertising Imagery to the Personalities of their Target Audience?

Clifford Donovan
Nov 4 · 3 min read

In the era of digital — specifically social media — marketing, the immense options available for targeted advertising are nearly limitless. It is no longer the case that audiences are broken down by simple demographics such as age, gender, and socioeconomic status. Marketers can now segment their audiences based on their likes and dislikes, their hobbies, their colleges, etc.

Some marketers are taking advantage of these capabilities through more specific ad copy in which a city’s jargon may be used, a familiar landmark is shown, or a college’s colours are used in the content. Content relevance is now the backbone of any good content marketing strategy. Gary Vaynerchuk describes this in his Ericsson Keynote (link is timestamped):


To take this a step further, what if ad imagery could be tailored to individual personalities?

A recent study in the Journal of Consumer Psychology investigated this idea (Matz et al., 2019). Researchers had 745 participants each rate how much they liked each of 52 images. Each participant then took a well established 50-item personality test as a measure of the five-factor model of personality:

Image courtesy of Wikipedia Commons

The researchers used the correlations of the resultant image likeness scores with each of the personality test results to develop a model for prediction of images that a specific individual may find more or less appealing.

Researchers then asked a new group of 468 participants to take the same personality test and then make 190 judgements of which image they preferred (from a pair of images). They found general appeal of the image was more predictive of image choice than their personality profile. However, the personality appeal of the image had a statistically significant incremental increase on the appeal of the images.

Lastly, the researchers completed a 3rd study to investigate whether participants would show stronger purchase intent and more positively assess brands that used imagery their personality results would predict to be more appealing (by the model established from the first study).

399 participants were asked to indicate their opinion and rate their intent to purchase products from a “brand” based on a set of 36 images. Although the general appeal of the images was the strongest predictor of positive brand assessment, and a stronger intent to purchase, the personality predicted preferences were also a significant predictor.

In sum — this research showed, in design of advertising imagery — the first concern should be general image appeal. However, matching imagery to the personality profiles of the individual consumers may increase their positive perception of the brand and purchase intent.

Furthermore, the authors cite Kosinski et al.’s 2013 paper in PNAS in which a thorough analysis of the pages participants liked on Facebook was able to predict the personality scores of participants with relative accuracy (see the green bars):

Predictive capability of Facebook profiles to the Big-Five Personality Traits. Results from Kosinksi et al., 2013.

Marketers have already been built out extensive customer personas for their target segments. With the targeting power available in digital marketing platforms, maybe it’s time to go a step further and build out personas based on personality profiles, each with their own targeted imagery and ad copy.

References:

Matz, S.C., Segalin, C., Stillwell, D., Müller, S.R., Bos, M.W., 2019. Predicting the Personal Appeal of Marketing Images Using Computational Methods. J. Consum. Psychol. 29, 370–390. https://doi.org/10.1002/jcpy.1092

Kosinski, M., Stillwell, D., Graepel, T., 2013. Private traits and attributes are predictable from digital records of human behavior. Proc. Natl. Acad. Sci. U. S. A. 110, 5802–5805. https://doi.org/10.1073/pnas.1218772110

Clifford Donovan

Written by

I’m a Neuroscience master’s graduate and co-founder of LIV Lavish Goods — a small personal care products business.

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