Key Takeaways:
- Extroverts prefer simple, people-centric visuals; open-minded individuals favor cool, unpopulated scenes. Neurotic users lean toward calm imagery.
- AI analyzed 89 image features (color diversity, saturation, etc.) and linked them to the Big 5 personality traits (openness, conscientiousness, agreeableness, extroversion, neuroticism).
- Ads matching users’ personalities boosted purchase intent by 34% in beauty, holiday, and tech categories.
- Personality-based ads can appeal to wider demographics beyond traditional age/gender segments.
Images used for advertising online and on television play an important role in shaping product impressions and triggering emotions. However, an ad that is appealing to one person might look irrelevant to another person. What if brands could tailor ads to match your personality? New research suggests they can and it boosts engagement by 34%.
Case study
People leave digital footprints on Google, Twitter, text blogs, Facebook, and other online sites. These footprints can determine if users are more introverted or extroverted by nature. They can also tell if users are open to trying new things or not. In a study, researchers show how digital data can be leveraged to personalize ads based on types of personality. The study was published in the Journal of Consumer Psychology.
The goal of the study is to create an experience that makes ads more relevant to consumers. This is according to study author Sandra Matz, PhD. She says that it is a way to provide better services to consumers.
Researchers began by using computer algorithms in the extraction of 89 features of images. The features include saturation, hue, color diversity, level of detail, and number of people. The researchers recruited 745 volunteers who they asked to rate their liking of the images on a scale of 1-7. The volunteers completed a personality test to evaluate them in 5 areas:
- Openness
- Conscientiousness
- Agreeableness
- Extroversion
- Neuroticism
The researchers used the data to determine the images that were more appealing to the five personality traits.
Findings
Researchers found, for instance, that extroverts preferred images that were simple and featured people. The open-minded people preferred images without people and images with cool colors like black and blue. Those high in neuroticism preferred calm and less stimulating scenes. The researchers then used the information to allocate personality types for every image.
In the study that followed, the researchers dug into whether the personality traits they assigned to the different images predicted consumer preferences accurately. The volunteers saw images that were related to products in one of 3 categories: beauty, holiday, or phone. They then rated the appeal level for different images. Matching the “personalities” of images to the participant’s self-reported personality considerably predicted the preference ratings.
The researchers learned that the fit between images and personalities played a part in manipulating a consumer’s interest in purchasing the product. People preferred images matching their personality and showed favorable attitudes towards these brands.
FAQs:
How do brands determine personality from digital footprints?
Algorithms analyze social media behavior (e.g., Twitter posts, blog tone) to assess traits like extroversion or openness.
Which personality trait most influences ad preferences?
Openness to experience—those scoring high prefer innovative, abstract visuals over conventional ones.
Do personalized ads benefit consumers?
Yes. Tailored ads reduce irrelevant content, though privacy concerns around data use persist.
Can this method work for all products?
Most effective for subjective categories (e.g., fashion, travel) vs. functional items (e.g., insurance).
What’s next for personality-based marketing?
Real-time ad adjustments using AI, like swapping images based on a user’s social media activity mid-scroll.
Conclusion
Brands mostly target certain age groups, genders, or social groups using ads. However, personality-matching advertisements could allow marketers to target wider groups of people. A consumer who might not be interested in online shopping at one store might discover items that are appealing to them. According to Matz, online marketers mostly focus on large audiences but they can now predict individual’s psychological traits giving them individualized experiences.
References
Sandra C. Matz, Cristina Segalin, David Stillwell, Sandrine R. Müller, Maarten W. Bos. Predicting the personal appeal of marketing images using computational methods. Journal of Consumer Psychology, 2019; http://dx.doi.org/10.1002/jcpy.1092
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