In a recent media release from Universiti Teknologi Malaysia, research scholar Dr Ikusan R. Adeyemi said, ’Our research suggests a person's personality traits can be deduced by their general internet usage,’ and it could do so using machine learning algorithms by analyzing just half an hour of web browsing.

This idea that personality traits can be determined by analyzing online behavior is nothing new, but it is only recently that is has started to really be applied by marketers. The potential impact it could have is profound.

Personality tests such as Myers-Briggs have been around since the 1920s. The idea that you can gain such insight based simply on someone’s behavior online may seem imprecise, but a wide body of research suggests to the contrary. In a research paper released by the university, it was noted that a ‘study presented in Golbeck et al. (2011) showed that humans reveal their personality trait in online communication through self-description and online statistical updates on social networking sites through which the FFM (someone who displays personality traits such as openness to new experience, conscientiousness, extraversion, agreeableness, and neuroticism) can provide a well-rounded measure of the human–computer relationship. The study observed that the personality trait of users can be estimated (in social media) to a degree of ≅11% accuracy for each factor based on the mean square error of observed online statistics. This implies that personality trait prediction can be achieved within 1/10 of its actual value.’

The ability to predict someone’s personality presents a clear opportunity for targeting advertising, enabling marketers to segment audiences according to personality type, test campaigns that will most appeal to that kind of person, and send them the marketing materials most appropriate based on this. The benefits of personalization are well proven. In a 2015 Harris Poll study, 95% of respondents say they’d be more likely to respond to personalized outreach, yet around a third say that they don’t get them. The Aberdeen Group also found that agencies best at personalization companies achieved up to a 36% higher conversion average and a 21% stronger lead acceptance rate.

While many marketers already personalize their campaign material based on basic metrics such as age and sex, segmenting by personality is likely to provide far greater returns, as people’s wants and needs often vary wildly within specific age groups and genders. Take, for example, two middle-aged women from the same area who are both interested in buying a new dress. One is an extrovert and wants people to notice her, while the other is an introvert and would prefer to fly under the radar. Having applied behavioral analytics and realized this, a fashion retailer can customize their messages and campaign accordingly.

Total digital ad spending in 2017 is estimated to reach $77.37 billion in the US alone. With ad blocking software growing rapidly - up 48% in 2015 - it is becoming increasingly important to make sure you are presenting people with things they want to see. Analyzing people’s data to gauge their personality type is not easy, and it raises justified concerns around online privacy. However, anonymity should be guaranteed simply by removing any identifiers, such as a name or phone number, before the data is passed on to the marketer. Assuming this is always the case, it is potentially game changing.