Behavioral Insights
Practical applications of behavioral science to understand and influence human behavior in various contexts. Crucial for applying scientific insights to design and improve user experiences and outcomes.
Practical applications of behavioral science to understand and influence human behavior in various contexts. Crucial for applying scientific insights to design and improve user experiences and outcomes.
The study of the principles that govern human behavior, including how people respond to stimuli and learn from their environment. Crucial for designing user experiences that anticipate and influence user behavior.
Behavioral Science (BeSci) is the study of human behavior through systematic analysis and investigation. Essential for understanding and influencing user behavior in design and product development.
An organization that applies behavioral science to policy and practice to improve public services and outcomes. Important for understanding practical applications of behavioral science in policy and public services.
Managing product development with a focus on understanding and influencing user behavior through behavioral science principles. Essential for product managers to create user-centric products that drive desired behaviors.
The application of behavioral science principles to design products that influence user behavior in a desired way. Crucial for creating products that effectively guide user behavior and improve outcomes.
Capability, Opportunity, Motivation (COM...) is a framework for understanding Behavior (àB). Important for designing interventions that effectively change user behavior.
Designing products that leverage behavioral science to influence user behavior in positive ways. Crucial for creating products that are effective in shaping user behavior and improving engagement.
The application of behavioral science principles to improve the design and usability of digital products, focusing on user behavior and interactions. Important for creating user experiences that are intuitive and engaging by leveraging behavioral insights.
A framework that combines multiple theories to explain and predict behavior, focusing on intention, knowledge, skills, environmental constraints, and habits. Crucial for designing interventions that effectively change user behavior.
The study of computers as persuasive technologies, focusing on how they can change attitudes or behaviors. Important for designing systems that effectively influence user behavior ethically.
A decision-making paradox that shows people's preferences can violate the expected utility theory, highlighting irrational behavior. Important for understanding inconsistencies in user decision-making and designing better user experiences.
The design of environments in which people make decisions, influencing their choices and behaviors. Important for creating user experiences that guide decision-making processes effectively.
A behavioral economics model that explains decision-making as a conflict between a present-oriented "doer" and a future-oriented "planner". Useful for understanding user decision-making and designing interventions that balance short-term and long-term goals.
A decision-making strategy where individuals allocate resources proportionally to the probability of an outcome occurring, rather than optimizing the most likely outcome. Important for understanding decision-making behaviors and designing systems that guide better resource allocation.
A cognitive phenomenon where people are more likely to pursue goals or change behavior following a temporal landmark (e.g., new year, birthday). Useful for designing interventions and features that leverage these moments to encourage positive behavior.
The act of designing and implementing subtle interventions to influence behavior in a predictable way. Crucial for guiding user behavior effectively without limiting freedom of choice.
A strategic framework that designs user experiences to guide behavior and decisions towards desired outcomes. Crucial for creating effective and ethical influence in digital interfaces.
The practice of organizing the context in which people make decisions to influence the outcomes, often used to nudge users towards certain behaviors. Crucial for designing user experiences that guide decision-making and improve outcomes.
A strategy where engaging, preferred activities are used to motivate users to complete less engaging, necessary tasks. Useful for designing user interfaces and experiences that encourage desired behaviors by leveraging more enjoyable activities as rewards.
The study of social relationships, structures, and processes. Important for understanding the impact of social dynamics on user behavior and designing for social interactions.
A theory in economics that models how rational individuals make decisions under risk by maximizing the expected utility of their choices. Essential for understanding decision-making under risk.
The study of how individuals make choices among alternatives and the principles that guide these choices. Important for designing decision-making processes and interfaces that help users make informed choices.
An experimental design where different groups of participants are exposed to different conditions, allowing for comparison between groups. Important for understanding and applying different experimental designs in user research.
A rule-of-thumb or shortcut that simplifies decision-making and problem-solving processes. Essential for designing user-friendly interfaces that facilitate quick and efficient decision-making.
A cognitive bias where people tend to remember the first and last items in a series better than those in the middle, impacting recall and memory. Crucial for designing information presentation to optimize user memory and recall.
The series of actions or operations involved in the acquisition, interpretation, storage, and retrieval of information. Crucial for understanding how users handle information and designing systems that align with cognitive processes.
The study of dynamic systems that are highly sensitive to initial conditions, leading to unpredictable behavior. Important for recognizing and managing unpredictable elements in design and development processes.
The way information is presented to users, which can significantly influence their decisions and perceptions. Important for designing messages and interfaces that guide user choices effectively.
The tendency for people to value products more highly if they have put effort into assembling them. Important for understanding user satisfaction and product attachment.
The experience of noticing something for the first time and then frequently encountering it shortly after, also known as frequency illusion. Important for understanding user perception and cognitive biases in information processing.
A research method that involves forming a theory based on data systematically gathered and analyzed. Useful for developing design theories and solutions that are directly grounded in user research and data.
A statistical distribution where most occurrences take place near the mean, and fewer occurrences happen as you move further from the mean, forming a bell curve. Crucial for data analysis and understanding variability in user behavior and responses.
The study of how people acquire knowledge, skills, and behaviors through experience, practice, and instruction. Useful for creating educational content and interactive tutorials that enhance user learning.
The tendency to overestimate the duration or intensity of the emotional impact of future events. Important for understanding user expectations and satisfaction.
Human-Computer Interaction (HCI) is the study of designing interfaces and interactions between humans and computers. It ensures that digital products are user-friendly, efficient, and satisfying.
The application of neuroscience principles to design, aiming to create more effective and engaging user experiences based on how the brain processes information. Crucial for creating designs that align with human cognitive and emotional processes.
A logical fallacy that occurs when one assumes that what is true for a part is also true for the whole. Important for avoiding incorrect assumptions in design and decision-making.
The study of the relationships between people, practices, values, and technologies within an information environment. Helps in understanding and designing systems that are sustainable and adaptive to human and environmental changes.