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.
98 topics found for:
“behavioral science”
Behavioral Strategy
The use of behavioral science insights to inform and guide strategic decision-making in organizations. Crucial for developing strategies that effectively influence behavior and drive business success.
Behavioral Theory
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.
BeSci
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.
Behavioral Insights Team
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.
Behavioral Product Management
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.
Behavioral Design
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.
Behavioral Product Critique
The evaluation of products based on their ability to influence and shape user behavior. Useful for assessing how well a product guides and influences user actions and decisions.
COM-B Model
Capability, Opportunity, Motivation (COM...) is a framework for understanding Behavior (àB). Important for designing interventions that effectively change user behavior.
Behavioral Product Design
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.
Behavioral User Experience
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.
Integrated Behavior Model
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.
Captology
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.
Allais Paradox
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.
Decision Architecture
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.
Dual Self Model
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.
Reward Power
The ability to influence others' behavior by offering positive incentives or rewards, commonly used in organizational and social contexts. Crucial for understanding dynamics of motivation and influence in team and organizational settings.
Negativity Bias
The tendency to give more weight to negative experiences or information than positive ones. Crucial for understanding user behavior and designing systems that balance positive and negative feedback.
Commitment Device
A technique or tool used to lock oneself into following through on a commitment, often by adding a cost to failing to do so. Useful for designing interventions that help users stick to their goals and commitments.
Probability Matching
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.
Automaticity
The ability to perform actions or behaviors automatically due to learning, repetition, and practice. Important for understanding user habits and designing intuitive user interfaces.
Fresh Start Effect
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.
Reciprocal Determinism
A theory that a person's behavior is influenced by and influences personal factors and the environment, creating a continuous loop of interaction between these elements. Important for understanding how behavior, personal factors, and environmental contexts dynamically interact to shape user experiences and outcomes.
Nudging
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.
Persuasion Architecture
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.
Sludge
Any process or administrative barrier that unnecessarily complicates transactions and creates friction, discouraging beneficial behaviors. Important for identifying and eliminating unnecessary obstacles that hinder user experiences.
Premack Principle
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.
Digital Phenotyping
The use of data from digital devices to measure and understand individual behavior and health patterns. Crucial for developing personalized user experiences and health interventions.
Choice Architecture
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.
Relativity
A principle often used in behavioral economics that suggests people evaluate options based on relative comparisons rather than absolute values. Important for understanding decision-making and designing choices that highlight beneficial comparisons.
Hedonic Adaptation
The observed tendency of humans to quickly return to a relatively stable level of happiness despite major positive or negative events or life changes. Useful for designing experiences that maintain user engagement and satisfaction over time.
Present Bias
A cognitive bias where individuals give stronger weight to payoffs that are closer to the present time compared to those in the future. Important for understanding user time-related decision-making and designing systems that encourage long-term thinking.
Qualitative Research
A research method that focuses on understanding phenomena through in-depth exploration of human behavior, opinions, and experiences, often using interviews or observations. Essential for gaining deep insights into user needs and behaviors to inform design and development.
Dual Process Theory
A framework suggesting there are two systems of thinking: System 1 (fast, automatic) and System 2 (slow, deliberate), influencing decision-making and behavior. Crucial for understanding how users process information and make decisions.
Social Theory
The study of social relationships, structures, and processes. Important for understanding the impact of social dynamics on user behavior and designing for social interactions.
Reciprocal Altruism
A behavior in which an individual provides a benefit to another with the expectation that the favor will be returned in the future, fostering mutual cooperation and long-term relationships. Important for building trust, cooperation, and mutually beneficial relationships in various social and professional contexts.
Expected Utility Theory
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.
Crowding Out Effect
The phenomenon where external incentives diminish intrinsic motivation, leading to reduced performance or engagement. Important for designing motivational strategies that do not undermine intrinsic motivation.
Irrational Escalation
The phenomenon where people continue a failing course of action due to the amount of resources already invested. Important for recognizing and mitigating biased decision-making.
Pessimism Bias
A cognitive bias that causes people to overestimate the likelihood of negative outcomes. Important for understanding user risk perception and designing systems that address irrational pessimism.
Backfire Effect
A cognitive bias where individuals strengthen their beliefs when presented with evidence that contradicts them. Important for understanding user resistance to change and designing strategies to address and mitigate this bias.
Decision Theory
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.
Zero-Risk Bias
A cognitive bias where people prefer the option that seems to eliminate risk entirely, even if another option offers a greater overall benefit. Important for understanding decision-making and designing risk communication for users.
Intrinsic Motivation
The drive to perform an activity for its inherent satisfaction rather than for some separable consequence. Crucial for designing experiences that engage users through inherent enjoyment and interest.
Ingroup Bias
A cognitive bias where people favor members of their own group over those in other groups. Important for designing inclusive and equitable experiences for users.
Category Size Bias
A cognitive bias where people judge the likelihood of an event based on the size of its category rather than its actual probability. Crucial for designers to understand how category size influences user perception and decision-making processes.
Belief Perseverance
The tendency to cling to one's beliefs even in the face of contradictory evidence. Important for understanding resistance to change and designing interventions that address this bias.
Google Effect
The tendency to forget information that can be easily found online, also known as digital amnesia. Important for understanding how access to information impacts memory and designing experiences accordingly.
Omission Bias
A cognitive bias where people judge harmful actions as worse, or less moral, than equally harmful omissions (inactions). Important for understanding user decision-making and designing systems that mitigate this bias.
Decision Utility
The value or satisfaction derived from a decision, influencing the choices people make. Crucial for understanding user preferences and designing experiences that maximize satisfaction.
Motivation Wave
A concept describing how motivation fluctuates over time, influenced by various factors such as goals, rewards, and external circumstances. Crucial for designing systems that align with users' motivational states to maximize engagement and productivity.
Subadditivity Effect
A cognitive bias where the total probability assigned to a set of events is less than the sum of the probabilities assigned to each event individually. Important for understanding how users estimate probabilities and make decisions under uncertainty.
Longitudinal Study
A research method that involves repeated observations of the same variables over a period of time. Crucial for understanding changes and developments over time.
Salience Bias
A cognitive bias where people focus on the most noticeable or prominent information while ignoring less conspicuous details. Important for understanding user decision-making and ensuring balanced presentation of information.
Between Subjects Design
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.
Pseudocertainty Effect
A cognitive bias where people perceive an outcome as certain while it is actually uncertain, based on how information is presented. Crucial for understanding and mitigating biased user decision-making.
Confirmation Bias
The tendency to search for, interpret, and remember information in a way that confirms one's preexisting beliefs or hypotheses. Crucial for understanding cognitive biases that affect user decision-making and designing interventions to mitigate them.
Messenger Effect
The phenomenon where the credibility of the source of information influences how the message is received and acted upon. Crucial for designing communication strategies that leverage trusted sources.
Serial Position Effect
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.
Reciprocity
A social norm of responding to a positive action with another positive action, fostering mutual benefit and cooperation. Important for designing user experiences and systems that encourage positive reciprocal interactions.