The OCEAN (Big Five) model describes personality in five clear dimensions - Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism - backed by decades of research. In marketing, these traits unlock deeper psychographic insights, letting you tailor messages that truly resonate. This article shows you how to infer OCEAN scores from social media, build meaningful audience segments, and craft campaigns that boost engagement and conversion.
What Is the OCEAN (Big Five) Model?
The OCEAN model - also known as the Big Five - arose from large-scale factor analyses of natural language descriptors of personality. Early lexical studies distilled thousands of trait adjectives into five broad, orthogonal dimensions, each explaining coherent clusters of behaviors and preferences.
Openness to Experience: Curiosity, imagination, and preference for novelty vs. routine.
Conscientiousness: Organization, discipline, and dependability vs. spontaneity or carelessness.
Extraversion: Sociability, energy, and sensation-seeking vs. reserve or introversion.
Agreeableness: Compassion and cooperativeness vs. antagonism or skepticism.
Neuroticism (Emotional Stability): Proneness to stress, anxiety, and negative emotions vs. calmness and resilience.
Costa and McCrae’s development of the NEO Personality Inventory further validated these dimensions, showing their cross-cultural applicability and predictive power. (Reference)
How OCEAN Can Help Marketers?
Short answer: Better marketing personalisation
Long answer: Segmenting audiences moves beyond broad demographics to uncover the psychological “why” behind consumer behaviors. Psychographic segmentation divides consumers by traits like values, lifestyle, and personality - providing deeper insight into motivations and decision-making processes.
By applying OCEAN (simplified) you can:
Reveal Core Drivers: Identify “high-Openness explorers” vs. “low-Openness traditionalists,” tailoring messages that emphasize novelty or familiarity accordingly.
Predict Preferences: Conscientious individuals may value reliability and detailed product information, while less conscientious consumers might respond to spontaneity and ease-of-use appeals.
Fine-Tune Tone and Channels: Extraverts often engage with community-focused, event-based promotions; introverts prefer one-on-one, informational content.
Align With Believes: Agreeable segments resonate with altruistic, cause-driven campaigns; low-Agreeableness segments may favor bold, humorous claims.
Address Emotional Needs: High-Neuroticism individuals seek reassurance and stress-relief messaging; emotionally stable consumers may be drawn to excitement and challenge.
OCEAN-based psychographics thus enable more precise, emotionally resonant campaigns that speak directly to the underlying personality drivers of each segment.
How it works? (in our case)
Step 1: Data Collection
We collect public data from users who engaged with our research topic by commenting, liking, or following. This includes their bios, profile pictures, posts, text, timestamps, comments, and videos—about 50,000 data points in total. (Yes - we process video, audio, and images with AI for each profile, and yes - it takes a lot of compute).
Step 2: Personality Traits Inference
We run each profile through our AI pipeline to estimate OCEAN scores. For example:
Diverse interests → Openness
Frequent friend tags or group photos → Extraversion
Polished grids or goal-oriented descriptions → Conscientiousness
Step 3: Clustering
We use clustering algorithms to group profiles with similar personality scores and build audience segments. Unlike demographic segmentation (which groups people by age, gender, or location), psychographic clustering uncovers each segment’s hidden motives, needs, and values—enabling marketers to craft messages that resonate on a deeper, emotional level.
Step 4: Segment Analysis
For each cluster, we dive into their common drivers, needs, and values. We look for patterns within a cluster and compare them to other segments to spot unique differences. These insights serve as clues for understanding what each group truly wants and, with the help of AI, defining the best-suited marketing approach for each segment.
Step 5: Synthesising Persona
Finally, we feed these insights into an AI assistant that “acts like” each segment - mimiking it’s behaviour, opinions, values and needs. This simulated persona helps you brainstorm content ideas, uncover deeper motivations, get feedback to your marketing messages, and understand each group’s core values and opinions.
Why This Matters?
Personalization boosts marketing efficiency by matching messages to each audience’s unique preferences and motivations. When consumers feel a message speaks directly to them, they pay more attention, engage more deeply, and convert at higher rates. By leveraging personality-based insights, brands can cut through generic noise, strengthen customer connections, and maximize return on ad spend.
Simple example:
In a field experiment with a UK-based beauty retailer, Matz et al. (2017) leveraged users’ inferred Extraversion scores to deliver two ad variants:
Extravert-Optimized Ad: Bold imagery, upbeat copy (“Dance like no one’s watching…”) and social-proof cues.
Introvert-Optimized Ad: Subdued visuals, calm copy (“Beauty doesn’t have to shout”) focusing on personal comfort.
Users who saw the ad matching their personality trait showed up to 40% higher click-through rates and 50% more purchases compared to those who saw the mismatched version Columbia Business SchoolTime. This demonstrates the power of psychographic targeting at scale.
Some more examples:
McKinsey “Next Frontier of Personalized Marketing” (Jan 2025):
Adoption of AI and generative AI for personalization at scale increases customer engagement and operational efficiency
Meta-Analysis of Personalized Digital Marketing (ResearchGate, Oct 2024):
Synthesizing multiple studies, this meta-analysis confirms that personalized ads significantly improve purchasing behavior across industries
Forrester: The State of US Consumer Personalization, 2024
Despite heavy investment, only one in three US consumers feels companies deliver truly relevant personalization—yet firms continue to double down on tailored marketing strategies
So yes-personalization is important. We help you understand your audience so you can tailor your marketing messaging and strategy in a right way.
Accuracy and Reliability: Strengths & Caveats
Our approach relies on roughly 50,000 data points per study—including photos, descriptions, tags, timestamps, bios, and profile pictures—ensuring a rich, multimodal foundation for trait inference.
Digital-footprint inference of OCEAN traits is scientifically grounded and provides actionable segmentation power.
Strengths:
Empirically validated across many studies and platforms.
Scalable, automated profiling with high precision at group level.
Enables deeper psychographic insight beyond demographics.
Limitations:
Some users curate their image online, so true traits can be obscured. For example, Instagram rarely shows high stress content, underestimating Neuroticism. But knowing that, you can “calibrate” your own perspective and understanding.
Psychology’s replication crisis reminds us that even established findings can vary by research team and method.
Best Practice: Treat OCEAN data as one input among many. Combine psychographics with demographic, behavioral, and survey data, and validate continuously with A/B tests and experiments.
Report examples
Conclusion
The OCEAN model offers a robust, research-backed framework for understanding personality across five dimensions. By inferring these traits from social media data and clustering profiles into psychographic segments, marketers can craft more personalized, emotionally resonant campaigns. While digital-footprint inference isn’t perfect, combining OCEAN insights with other data sources - and validating through testing—delivers deeper audience understanding and stronger marketing performance.
