Personalysis is the process of analyzing personal data to gain insights into an individual’s personality, values, abilities, and preferences. It combines concepts from various fields like psychology, statistics, and computer science to examine how a person thinks, feels and behaves. With the growth of digital footprints and availability of personal data, personalysis has become an emerging field with applications in many sectors like marketing, healthcare, education, human resources etc.
Some key questions that personalysis tries to answer are:
– What kind of personality does an individual have? Are they introverted or extroverted? Risk-taking or cautious? Agreeable or antagonistic?
– What are an individual’s strengths, talents and abilities? How do they learn and process information best?
– What are an individual’s interests, values, opinions and attitudes? What do they care deeply about?
– How does an individual behave in various contexts and situations? How do they make decisions? How do they interact with others?
Data Sources for Personalysis
There are various sources of personal data that can feed into personalysis:
– **Explicit data**: Information that a person directly provides about themselves like social media profiles, resumes, psychometric test results, medical records, shopping habits etc.
– **Observational data**: Data gathered by observing an individual’s behaviors, choices and actions. This could include social media activity, browsing history, smartphone usage patterns, etc.
– **Integrated data**: Combining data from multiple sources like social, demographic, behavioral, transactional, biometric data etc. to get a comprehensive view.
– **Self-reported data**: Asking individuals to provide subjective information about themselves through interviews, questionnaires, surveys, diaries etc.
| Data Source | Examples |
|---|---|
| Explicit data | Social media profiles, resumes, psychometric tests, shopping history |
| Observational data | Browsing history, social media activity, smartphone usage |
| Integrated data | Combining social, demographic, behavioral and other data |
| Self-reported data | Interviews, questionnaires, surveys, diaries |
Methods Used in Personalysis
Various analytical techniques are leveraged in personalysis to extract insights from personal data:
– **Descriptive analytics**: Using statistical techniques like clustering, correlation analysis, cross-tabulation to identify patterns and connections in an individual’s behaviors and preferences.
– **Predictive modeling**: Building models using machine learning algorithms to make predictions about an individual’s future actions, preferences or performance. Common techniques include regression, random forests, support vector machines.
– **Psychometric testing**: Using scientifically designed questionnaires and assessments based on psychological theories to measure an individual’s abilities, personality traits, values and attitudes.
– **Network analysis**: Mapping connections and information flows between an individual and other people, organizations or entities. This can reveal influences, relationships and position within a network.
– **Natural language processing**: Analyzing text and speech data like social media posts, emails, documents, call transcripts to understand communication style, thinking patterns, interests etc.
– **Computer vision**: Applying deep learning techniques to analyze facial expressions, gestures and other visual cues to gain insights into an individual’s emotional state, engagement levels, reactions etc.
| Method | Description |
|---|---|
| Descriptive analytics | Statistical techniques to identify behavioral patterns |
| Predictive modeling | ML models to predict future actions and preferences |
| Psychometric testing | Assess personality traits, values and attitudes |
| Network analysis | Map connections and relationships |
| NLP | Analyze text and speech data |
| Computer vision | Analyze facial expressions and visual cues |
Applications of Personalysis
Here are some key sectors where personalysis is being used:
Marketing and Advertising
Personalysis enables more relevant, targeted marketing:
– Create detailed customer persona profiles based on interests, values, personality, demographics.
– Segment audiences and customize messaging to resonate with different personality types. Introverts may prefer different ads vs extroverts.
– Predict which customers are more likely to purchase a product, respond to an offer or engage with a brand.
– Recommend products and services aligned to an individual’s preferences.
Healthcare
Personalysisapplications in healthcare:
– Provide personalized treatment plans tailored to a patient’s unique needs and characteristics.
– Assess risk factors based on lifestyle, behaviors, genetics and health history.
– Monitor patient health through wearables and IoT devices and analyze data to provide timely interventions.
– Chatbots and virtual assistants powered by personalysis to provide comfort, information and motivation to patients.
Education
How personalysis helps enhance learning:
– Assess student strengths, weaknesses, learning styles, motivations and recommend personalized learning paths, teaching methods.
– Predict student performance and risk of dropping out.
– Provide adaptive learning platforms where curriculum adapts based on real-time insights on each student.
– Chatbots acting as virtual tutors using personalysis to teach, guide, motivate students.
Human Resources
HR applications of personalysis include:
– Evaluate job candidates beyond resumes using personalysis for culture fit, potential and capability assessments.
– Provide personalized career development paths based on employee strengths, passions and growth areas.
– Analyze employee engagement levels, satisfaction and predict retention risks.
– Suggest teams and roles where an employee is likely to thrive and be motivated.
Finance
Financial use cases for personalysis:
– Customize investment portfolio based on risk appetite, life stage and financial goals of the account holder.
– Assess creditworthiness through alternative lenses beyond credit score using behavioral and psychographic data.
– Recommend financial products aligned to personal financial needs and circumstances.
– Detect financial crimes like fraud, money laundering etc. by analyzing transactions for suspicious patterns.
Benefits of Personalysis
Some key benefits that personalysis provides:
– **Hyper-personalization** – Provides tailored solutions aligned closely to individual needs and preferences.
– **Deeper insights** – Goes beyond demographics to uncover psychological drivers, relationships and patterns.
– **Improved experience** – More relevant interactions and recommendations result in better engagement.
– **Efficiency** – Automates manual personalization to scale impact. AI does the heavy-lifting.
– **Risk assessment** – Helps estimate risks and future outcomes related to individuals.
– **Objectivity** – Minimizes human bias in evaluation and decision making.
Risks and Ethical Concerns
While personalysis offers many benefits, some risks and ethical challenges need attention:
– **Privacy violations** – Collecting excessive personal data without consent raises privacy issues.
– **Misuse of insights** – Personal data could be misused for manipulation, discrimination, targeting vulnerabilities.
– **Inaccurate profiles** – Imperfect algorithms and biased data can create misleading profiles.
– **Loss of agency** – People feeling out of control as algorithms make decisions about their lives.
– **Lack of transparency** – Individuals not understanding what data is used and how decisions are made about them.
– **Group attribution** – Judging people as homogeneous groups without regarding individual differences.
Conclusion
Personalysis leverages the huge amounts of personal data available today to uncover deep insights into how people think, feel and behave. It powers personalized experiences and decision-making across many sectors but also poses ethical risks if not implemented responsibly. Overall, personalysis marks an evolution in how individuals are evaluated and engaged with, elevating personal context while preserving individual agency and choice. With proper governance, personalysis can usher in an age of customization and human-centric services based on a nuanced understanding of the person.
