“If you wish to persuade me, you must think my thoughts, feel my feelings, and speak my words.” — Marcus Tullius Cicero (c. 106-43 B.C.). In our quest to understand and predict human behavior, we’ve spent decades exploring the intricacies of personality. Studies across a wide variety of fields — from psychology to consumer behavior, human-computer interaction to decision theories — reveal that individuals have intrinsic traits that can be recognized and used to predict future behavior. But how can we leverage this in the digital age, where we communicate and interact more often with screens than with humans? How can we unleash the power of personality insights?
The answer lies in psychographics, a groundbreaking framework that leverages cognitive computing and social media data to generate deep, nuanced understandings of customer behavior. It’s a system that learns to “think your thoughts, feel your feelings, and speak your words,” offering companies unprecedented insight into their customers.
Personality insights: A deep dive
Knowing how to build an accurate and precise user profile is a way to offer a multifaceted framework for understanding individuals. Based on theories from psychology, consumer behavior, and human-computer interaction, it creates a “portrait” of a person encompassing multiple dimensions. These include lifestyle, events, beliefs, values, economic status, political beliefs, technological adaptiveness, motives, commitments, goals, ambitions, interests, sentiments, attitudes, perceptions, emotions, cognitive style, decision-making process, and more.
This holistic approach allows for a more sophisticated understanding of customer behavior, going far beyond traditional models that rely on demographic data alone. By combining insights from diverse fields, we can generate a detailed and accurate portrait of an individual, reflecting their unique identity and capturing their complex web of influences and decisions.
Understanding humans’ complexity can be done with psychographic data
Extracting psychographics from language
One of the most innovative aspects of psychographics is the use of psycholinguistic analysis. This approach, validated by numerous studies, allows traits to be inferred from the written language of individuals. In the digital age, where billions of people leave a linguistic “footprint” in the form of social media posts, this offers an unparalleled source of data.
To evaluate millions of documents in seconds, complex linguistic analysis provides real-time insight into the behaviors of individuals at scale. It can analyze text from various sources, including social media posts, emails, product reviews, and more.
Moreover, it can even adapt the text to portray a specific personality, offering a tool not only for understanding but also for influencing behavior. In essence, this tool converts raw data into actionable intelligence, making it a valuable resource for businesses.
Inferring personality from language
Opportunities for companies
Psychographic data has a myriad of applications for companies. It allows for more effective targeting of marketing campaigns, enabling businesses to understand who, what, how, and when to target. By delivering more relevant marketing and better-quality lead generation, businesses can improve customer satisfaction, manage their brand reputation actively, and capitalize on targeted revenue-generating opportunities.
Moreover, they allow for individualized customer care, facilitating real-time, personalized communication between customers and the company. The system provides real-time agent assistance, matching customers with agents who are likely to resonate with their personality type.
In addition to customer-facing applications, personality insights can also improve internal processes. It can be used in workforce optimization, helping to predict and improve employee performance. By offering individualized recommended training styles and identifying leadership potential, it can aid in recruitment and retention, job assignments, and team building.
Example of persona clustering
Example of data that can be collected on users
Psychographics in action
Let’s delve into how psychographic data can revolutionize different aspects of business operations with three NextUser’s use cases.
Alibris – Ecommerce
Alibris is the premiere independent online bookstore for new, used and out-of-print media. Alibris is a division of Monsoon Commerce with a $100 million in revenues and 120 employees. Since its launch in 1998, the mission is to connect people who love literature to the best independent sellers around the world. Alibris is the ideal choice for book, music, and movie lovers each day. For Alibris, we faced challenges in terms of engagement stickiness, and no discovery experience for 1st time visits. To address this, we built a database of author quotes to submit more than 800 words for each Alibris author to Watson User Modeling API. The results created a vector set for each author. We then engaged Alibris’ users by asking them about their favorite author and display their personality based on the vector set created for each author. This resulted in increasing session duration by 311%, decreasing bounce rate by 35%, and improving conversion rate by 61%.
Unilever – Online engagement and profiling
Unilever is a British multinational company specializing in consumer goods. The brand has an extensive product portfolio, which includes food, personal care, and home care products. Its products are sold in over 180 countries and are backed by a commitment to innovation, research, and development. Unilever’s brand CLEAR sought to gain a deeper understanding of its consumers and their behaviors, thoughts, and emotions. In fact, the brand needed this information to offer personalized recommendations. NextUser’s AI algorithms collected and analyzed demographic, lifestyle, education data, consumer behavior, and personality insights to drive effective segmentation and personalization efforts. This allowed CLEAR to gain a comprehensive understanding of its consumers. It also enabled the brand to create personalized recommendations that resonated with each individual user. To engage users through the site and discovery of the products, and to especially target Millennial users in a surprising way, we delivered 4 solutions to CLEAR: a product discovery, a personality match, a content discovery, and a retention strategy. We set up our personality match based on AI and social data, to find a beauty blogging corresponding to each user. This enabled the brand to recommend tailored products, tips, and articles to users, to ensure a hyper-personalized experience. This resulted in decreasing bounce rate by 52%, increasing session duration by 73% and the number of pages viewed in one session by 55%.
Diageo – Augmented research
Diageo is a multinational company with over 200 brands, renowned as a leader in the premium drinks sector. Smirnoff Vodka, one of its brands, is one of the best-selling distilled spirits globally, available in more than 130 countries. Diageo faced difficulty in gaining a comprehensive understanding of the consumers’ habits and preferences for the Smirnoff brand. They aimed to enhance their upper conversion funnel by gathering context on the why, how, and what of consumer behavior, and personalizing recommendations accordingly. We provided the brand with a comprehensive understanding of Smirnoff’s audience, social media presence, and consumption patterns. NextUser’s platform analyzed over 300 variables for each Smirnoff user, including images, texts, and personality, to build communities and gain insights into consumer behavior. NextUser’s AI algorithms provided context by analyzing Smirnoff’s competitive landscape and identifying key influencers. The data was consolidated and visualized in one platform, allowing Diageo to understand its consumers, discover brand influencers, and compare its performance with competitors. With NextUser’s AI-powered marketing solution, Diageo was able to gain a deep understanding of its consumers’ habits and preferences, allowing the company to personalize recommendations and improve the customer experience. This resulted in +700k text messages and 11 subspaces analyzed, and 30k Instagram influencers identified.
The evolution of AI in marketing
As AI continues to evolve and become more sophisticated, its potential to revolutionize marketing practices also increases. Companies are gradually moving towards more advanced, integrated apps that incorporate machine learning, which hold the greatest potential to create value.
Recent developments in AI for personality prediction are testament to this evolution. For instance, a large-scale implementation of the Big Five Personality Test using machine learning has been developed. The model uses an open dataset containing over a million questionnaire answers and employs K-means clustering to identify five distinct personality types. This innovative approach offers a comprehensive understanding of consumers’ personalities, facilitating highly personalized marketing strategies.
AI’s potential in precision personality prediction is also evident in real-world settings, such as a machine learning-based dating service developed in Japan. The service focuses on individuals’ values and personalities rather than just factors like age, income, and educational level, leading to more successful matches. This exemplifies the potential of AI in delivering personalized experiences based on a deep understanding of individual personalities.
Moreover, a recent study led by Professor Jinyan Fan found that an AI chatbot can infer personality traits as effectively as or better than traditional self-report personality measures. This could provide a more interactive experience and is harder to fake, making it a potentially valuable tool in contexts such as job applications and marketing efforts. The study predicts that AI-based personality assessment will eventually dominate traditional assessment methods, particularly as the psychometric properties of machine scores become further established.
The Big 5 Personality test
Conclusion
As AI continues to evolve and become more sophisticated, its potential to revolutionize marketing practices only increases. Businesses that are able to harness this potential will be well-positioned to succeed in the increasingly competitive marketplace.
However, the future of marketing isn’t just about adopting the latest technologies—it’s also about using these technologies responsibly. As businesses continue to incorporate AI into their marketing practices, it’s crucial that they do so in a way that respects the privacy and autonomy of their customers. This means not only ensuring transparency and fairness in their AI models but also using the insights they gain from these models ethically.
Moreover, businesses must continually adapt and innovate their AI technologies to stay ahead of the curve. As the digital landscape becomes increasingly complex, businesses will need to invest in advanced AI tools and talent. This includes not only hiring skilled AI practitioners but also upskilling existing employees to work effectively with AI.
The future of marketing is undeniably intertwined with the future of AI. As AI technologies become more sophisticated and their adoption becomes more widespread, they will play an increasingly important role in shaping marketing strategies.
Get started with NextUser to unleash the power of psychographic data.
