We apply a proven blueprint to understand why people behave the way they do, create demand, and engage with consumers on a much more personal level.
We apply a proven blueprint to understand why people behave the way they do, create demand, and engage with consumers on a much more personal level.
Openness
Degree of intellectual curiosity, creativity and a preference for novelty
Low levels
High levels
Doesn’t like change
Extremely creative
Not interested in new things
Trying new things
Doesn’t welcome new ideas
Extremely focused on handling new challenges
Isn’t very imaginative
Thinks about abstract concepts
Conscientiousness
Tendency to be organized and dependable
Low levels
High levels
Spends more time preparing
Doesn’t like structures and scheduling
Focuses and finishes tasks on time
Doesn’t like to take care of things
Pays extra attention to details
Fails to complete important or assigned tasks
Likes having a set-out schedule
Extraversion
Tendency to seek the company of others and talk
Low levels
High levels
Loves being the center of attention
Unable to start new things
Conversation starter
Doesn't like completing small tasks
Enjoys meeting new people
Thinks a lot before speaking
Naturally being able to make new frinds
Agreeableness
Measure of one’s trusting and helpful nature
Low levels
High levels
Shows alot of interest in other people
Shows less interest in other people
Usually cares about others
Has low interest in other people's problems
Feels empathetic towards other people
Doesn't care about how other people feel
Loves helping
Neuroticism
Predisposition to phycological stress
Low levels
High levels
Gets upset often
Very emotionally stable
Dramatic mood swings
Handles stress well
Feels anxious
Rarely feels upset or depressed
Source: Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual Review of Psychology, 41, 417–40.Goldberg, Lewis R. "The development of markers for the Big-Five factor structure." Psychological assessment 4.1(1992): 26.
Each persona is the result of an in-depth analysis of specific traits possessed by users withsimilar patterns, interests, and app- personalities. These traits allow us to identify connectionsamongst individuals that traditional, generic demographic filters can’t. We combine the two to deliver you with a better picture of who your customers really are.
Enthusiast
Likely to be outgoing, effective people who like to take on the world and win
Organiser
Likely to be no-nonsense who want strategy and efficiency, engaged with productivity tools
Hedonist
Likely to consume entertaining content and like fun and escape
Realist
Likely to engage with pragmatic content and functional reasoning
Artist
Likely to engage withartistic content andbe open to new things
The Augmented lifecycle of an App (with Credolab)
Retailer
Tailored messages to women’s psychological needs and motivations.
One set of ads spoke to extroverts’ craving for stimulation, excitement, and attention, and another set played into introverts’ desire for quiet, high-quality “me time".
The extroverted ads were colourful, featuring women in highly social settings (say, in the middle of the dance floor) and alluding to their need to be seen (“Dance like no one’s watching, but they totally are”).
The introverted ads were subtle, showing a single woman in a peaceful context (using a cosmetic face mask to relax) and hinting at her reserved nature in the copy (“Beauty doesn’t have to shout”).
The ads that were customised by personality were 50% more effective at attracting purchases and generating revenue than those that were not.
Travel
Personality-based travel and vacation recommendations.
For instance, if our algorithm suggested that a customer was introverted, that person would get a “soloist” profile with recommendations for quiet and relaxing destinations.
If the algorithm indicated that someone was neurotic, we’d offer an “all-inclusive” traveller package with recommendations for worry- free vacations with nothing left to chance.
The campaign reached 60,000 users in three months led to the hotel chain winning an award for the most innovative travel marketing campaign from the Chartered Institute of Marketing, and higher click-through and social-engagement rates meant a higher return on investment and brand visibility for the company.
Source: What Psychological Targeting Can Do And how to use it ethically,, Sandra Matz, Harvard Business Review, March 2023
Example of academic support
Extraversion
Uses of Internet
-0.26
Total duration of incoming calls
0.20
Average duation of incoming calls
0.18
Uses of Camera
-0.15
Avg. word length (sent)
-0.15
Media word lenth (sent)
-0.15
Calls received
0.13
SMS sent
-0.13
No. unique BT IDs
-0.13
Extraversion
Incoming calls
-0.26
Uses of Office
0.20
Uses of Calendar
0.18
Unique contacts called
-0.15
Total duration incoing calls
-0.15
Unique contacts SMS sent to
-0.15
BT IDs seen more than 4 times
0.13
BT IDs accounting for 50%of IDs seen
-0.13
Source: Peltonen, E., Sharmila, P., Asare, K. O., Visuri, A., Lagerspetz, E., & Ferreira, D. (2020). When phones get personal: Predicting Big Five personality traits from application usage. Pervasive and Mobile Computing, 69, 101269. Chittaranjan, G., Blom, J., & Gatica-Perez, D. (2011, June). Who's who with big-five: Analyzing and classifying personality traits with smartphones. In 2011 15th Annual international symposium on wearable computers (pp. 29-36). IEEE. Stachl, C., Au, Q., Schoedel, R., Buschek, D., Völkel, S., Schuwerk, T., ... & Bühner, M. (2019). Behavioral patterns in smartphone usage predict big five personality traits. Stachl, C., Au, Q., Schoedel, R., Gosling, S. D., Harari, G. M., Buschek, D., ... & Bühner, M. (2020). Predicting personality from patterns of behavior collected with smartphones. Proceedings of the National Academy of Sciences, 117(30), 17680-17687.Kambham, N. K., Stanley, K. G., & Bell, S. (2018, November). Predicting personality traits using smartphone sensor data and app usage data. In 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (pp. 125-132). IEEE.