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.
The tendency to attribute positive qualities to one's own choices and downplay the negatives, enhancing post-decision satisfaction. Useful for understanding user satisfaction and designing experiences that reinforce positive decision outcomes.
The speed at which leads move through the sales funnel. Crucial for understanding and optimizing the sales process.
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 complex systems and how interactions within these systems give rise to collective behaviors. Useful for understanding and managing the complexity in design processes and systems.
A behavioral economics concept where people categorize and treat money differently depending on its source or intended use. Crucial for understanding financial behavior and designing systems that align with users' mental accounting practices.
A usability testing method where participants verbalize their thoughts while interacting with a product. Essential for understanding user thought processes and identifying usability issues.
A cognitive bias that causes people to believe they are less likely to experience negative events and more likely to experience positive events than others. Crucial for understanding user risk perception and designing systems that account for unrealistic optimism.
A temporary increase in the frequency and intensity of a behavior when reinforcement is first removed. Useful for understanding user behavior changes in response to modifications in design or system features.
The ability to perform actions or behaviors automatically due to learning, repetition, and practice. Important for understanding user habits and designing intuitive user interfaces.
A psychological state where individuals lose their sense of self-awareness and personal responsibility in groups, often leading to atypical behavior. Crucial for understanding group dynamics and designing experiences that promote positive group interactions.
A cognitive bias where the perception of one positive trait influences the perception of other unrelated traits. Important for designers to manage and utilize this bias effectively in user experience design.
The final interaction a customer has with a brand before making a purchase. Important for understanding which touchpoints drive conversions.
The perception of a brand in the minds of consumers, shaped by interactions and experiences with the brand. Crucial for understanding consumer perceptions and guiding brand strategy.
The tendency for individuals to favor information that aligns with their existing beliefs and to avoid information that contradicts them. Crucial for understanding how users engage with content and designing systems that present balanced perspectives.
The error of making decisions based solely on quantitative observations and ignoring all other factors. Important for ensuring a holistic approach to decision-making.
A clear and concise list of criteria that a product or task must meet to be considered complete, ensuring alignment and understanding within a team. Essential for maintaining quality and consistency in agile project management.
The percentage of users who start but do not complete a desired action, such as completing a form or purchasing a product. Important for identifying issues in user flows and improving conversion rates.
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.
A cognitive bias where individuals overlook or underestimate the cost of opportunities they forego when making decisions. Crucial for understanding user decision-making behavior and designing systems that highlight opportunity costs.
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.
A psychological theory that predicts an individual's behavior based on their intention, which is influenced by their attitudes and subjective norms. Important for understanding and predicting user behavior and designing interventions to influence actions.
Information Visualization (InfoVis) is the study and practice of visual representations of abstract data to reinforce human cognition. Crucial for transforming complex data into intuitive visual formats, enabling faster insights and better decision-making.
A cognitive bias where decision-making is affected by the lack of information or uncertainty. Important for understanding and mitigating user decision-making biases due to uncertainty or lack of information.
The value a brand adds to a product or service beyond the functional benefits, encompassing factors like brand awareness, perceived quality, and customer loyalty. Crucial for understanding the long-term value of a brand and its impact on business success.
A cognitive bias where people disproportionately prefer smaller, immediate rewards over larger, later rewards. Important for understanding and designing around user decision-making and reward structures.
A cognitive approach that involves meaningful analysis of information, leading to better understanding and retention. Crucial for designing educational and informational content that promotes deep engagement and learning.
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.
The change in opinions or behavior that occurs when individuals conform to the information provided by others. Important for understanding social dynamics and designing systems that leverage social proof and peer influence.
A cognitive bias where people place too much importance on one aspect of an event, causing errors in judgment. Important for understanding decision-making and designing interfaces that provide balanced information.
A phenomenon where users fail to notice significant changes in their visual field. Important for understanding and designing around potential user perception issues.
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.
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 theory that emphasizes the role of emotions in risk perception and decision-making, where feelings about risk often diverge from cognitive assessments. Important for designing systems that account for emotional responses to risk and improve decision-making.
A clear, concise description of the issue(s) that need to be addressed, focusing on the specific challenge and its impact. Essential for guiding problem-solving efforts and ensuring a clear understanding of the issue at hand.
A cognitive bias that leads individuals to prefer things to remain the same rather than change, often resisting new options or changes. Crucial for understanding resistance to change and designing strategies to overcome it among users.
A cognitive bias where people give greater weight to outcomes that are certain compared to those that are merely probable. Important for designers to consider how users weigh certain outcomes more heavily in their decision-making.
The study of structures of consciousness as experienced from the first-person point of view. Important for designing user experiences that are intuitive and empathetic.
The theory that people adjust their behavior in response to the perceived level of risk, often taking more risks when they feel more protected. Important for designing safety features and understanding behavior changes in response to risk perception.
A network of real-world entities and their interrelations, organized in a graph structure, used to improve data integration and retrieval. Crucial for enhancing data connectivity and providing deeper insights.
A strategic framework used to analyze the external macro-environmental factors affecting an organization: Political, Economic, Social, Technological, Environmental, and Legal. Essential for strategic planning and understanding market dynamics.
A philosophy that emphasizes reason and logic as the primary sources of knowledge and truth. Useful for understanding the foundations of logical thinking and decision-making in design and development.
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 concept in behavioral economics that describes how future benefits are perceived as less valuable than immediate ones. Important for understanding user preferences and designing experiences that account for time-based value perceptions.
A cognitive bias where people remember scenes as being more expansive than they actually were. Important for understanding how users perceive and recall visual information, aiding in better visual design decisions.
A combination of software tools, technologies, and services used to develop, manage, and deliver a product. Crucial for understanding the infrastructure that supports product development and management.
The mistaken belief that a person who has experienced success in a random event has a higher probability of further success in additional attempts. Crucial for understanding and designing around user decision-making biases.
User-Centered Design (UCD) is an iterative design approach that focuses on understanding users' needs, preferences, and limitations throughout the design process. Crucial for creating products that are intuitive, efficient, and satisfying for the intended users.
A phenomenon where group members make decisions that are more extreme than the initial inclination of its members due to group discussions and interactions. Crucial for understanding and mitigating the risks of extreme decision-making in group settings.
A theoretical framework in economics that assumes individuals act rationally and seek to maximize utility, used to predict economic behavior and outcomes. Important for understanding traditional economic theories and designing systems that account for rational decision-making.
A motivational theory suggesting that individuals are motivated to act based on the expected outcomes of their actions and the attractiveness of those outcomes. Important for understanding motivation and behavior, distinct from decision-making under uncertainty.
The tendency for people's perception to be affected by their recurring thoughts at the time. Important for understanding how current thoughts influence user perception and decision-making.
A cognitive bias where people attribute group behavior to the characteristics of the group members rather than the situation. Crucial for understanding team dynamics and avoiding misattribution in collaborative settings.
The process by which attention is guided by internal goals and external stimuli, affecting how information is processed and remembered. Useful for designing user interfaces that direct user attention effectively.
The practice of identifying and analyzing search terms that users enter into search engines, used to inform content strategy and SEO. Essential for understanding user intent and optimizing content to meet search demand.
The tendency to perceive a greater quantity as a better value, regardless of the actual utility. Important for understanding consumer behavior and designing effective marketing strategies.
The number of pixels per inch (PPI) on a display, affecting the sharpness and clarity of visual elements. Crucial for optimizing visual content for different devices.
A machine learning-based search engine algorithm used by Google to help process search queries and provide more relevant results. Important for understanding modern SEO practices and how search engines interpret and rank web content.
The tendency for individuals to recall information that is consistent with their current mood. Important for understanding how mood affects memory and designing experiences that account for emotional states.
Retrieval-Augmented Generation (RAG) is an AI approach that combines retrieval of relevant documents with generative models to produce accurate and contextually relevant responses. Essential for improving the accuracy and reliability of AI-generated content.