The enhancement or diminishment of perception, cognition, or related performance as a result of exposure to a stimulus of greater or lesser value in the same dimension. Useful for designing interfaces that leverage contrasting elements to guide user attention and behavior.
Interaction Design (IxD) focuses on creating engaging interfaces with well-thought-out behaviors. Crucial for ensuring intuitive and effective user interactions.
The process of dividing a broad consumer or business market into sub-groups of consumers based on shared characteristics, needs, or behaviors. Important for tailoring marketing strategies and product offerings to specific customer groups.
A reading pattern where users skip over certain sections of content, often due to a lack of perceived relevance. Crucial for designing content that is engaging and relevant to prevent users from bypassing important information.
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 cognitive bias where individuals or organizations continue to invest in a failing project or decision due to the amount of resources already committed. Important for designers to recognize and mitigate their own risks of continuing unsuccessful initiatives.
The belief in one's ability to succeed in specific situations or accomplish a task, influencing motivation and behavior. Crucial for designing systems that enhance user confidence and encourage goal achievement.
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.
A system that suggests products, services, or content to users based on their preferences and behavior. Essential for personalizing user experiences and increasing engagement and conversion rates.
Measurements that track the effectiveness of each stage of the funnel, such as conversion rates and drop-off points. Crucial for identifying areas of improvement in the customer journey.
A research method that involves repeated observations of the same variables over a period of time. Crucial for understanding changes and developments over time.
A qualitative research method involving direct conversations with users to gather insights into their needs, behaviors, and experiences. Essential for gaining deep insights into user perspectives and informing design decisions.
A statistical method used to predict a binary outcome based on prior observations, modeling the probability of an event as a function of independent variables. Essential for predicting categorical outcomes in digital product analysis and user behavior modeling.
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.
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.
The path or sequence of actions users follow based on information scent to find their desired information. Crucial for understanding user behavior and optimizing content discovery paths.
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.
The ability of users to influence the behavior and outcomes of a system or product, allowing them to interact with it according to their preferences. Essential for creating user-friendly interfaces that allow for flexibility and customization.
The economic theory that suggests limited availability of a resource increases its value, influencing decision-making and behavior. Important for creating urgency and increasing perceived value in marketing.
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.
Numeronym for the word "Observability" (O + 11 letters + N), the ability to observe the internal states of a system based on its external outputs, facilitating troubleshooting and performance optimization. Crucial for monitoring and understanding system performance and behavior.
A decision-making strategy that involves choosing an option that meets the minimum requirements rather than seeking the optimal solution, balancing effort and outcome. Important for designing user experiences that accommodate decision-making under constraints.
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 cognitive bias where people attribute greater value to outcomes that required significant effort to achieve. Useful for designing experiences that recognize and reward user effort and persistence.
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.
A usability testing method that measures the first click users make on a webpage to determine if they can successfully navigate to their goal. Essential for evaluating and improving the navigational structure of a website.
A cognitive bias where people seek out more information than is needed to make a decision, often leading to analysis paralysis. Crucial for designing decision-making processes that avoid information overload for users.
A cognitive bias where people overestimate the probability of success for difficult tasks and underestimate it for easy tasks. Useful for designers to understand user confidence and design
A symmetrical, bell-shaped distribution of data where most observations cluster around the mean. Fundamental in statistics and crucial for many analytical techniques used in digital product design and data-driven decision making.
A cognitive bias where individuals believe that past random events affect the probabilities of future random events. Important for designers to understand user decision-making biases related to randomness.
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.
Zero Moment of Truth (ZMOT) is a concept in marketing that refers to the point in the buying cycle when the consumer researches a product before the seller even knows they exist. Crucial for understanding consumer behavior and optimizing marketing strategies to influence decision-making at this early stage.
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.
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.
Representativeness is a heuristic in decision-making where individuals judge the probability of an event based on how much it resembles a typical case. Crucial for understanding biases in human judgment and improving decision-making processes.
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.
The Principle of Objects is an information architecture guideline that treats content as living, distinct entities with behaviors and attributes. Crucial for creating modular, reusable, and flexible content structures.
The value or satisfaction derived from a decision, influencing the choices people make. Crucial for understanding user preferences and designing experiences that maximize satisfaction.
The tendency for people to feel more motivated and accelerate their efforts as they get closer to achieving a goal. Important for designing systems that motivate users effectively.
A tree-like model of decisions and their possible consequences, used in data mining and machine learning for both classification and regression tasks. Valuable for creating interpretable models in digital product design and user behavior analysis.
A field research method where researchers observe and interview users in their natural environment to understand their tasks and challenges. Crucial for gaining authentic insights into user behavior and needs.
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.
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.
A set of cognitive processes that include working memory, flexible thinking, and self-control, crucial for planning, decision-making, and behavior regulation. Crucial for designing interfaces and experiences that support users' cognitive abilities.
A cognitive bias where individuals overestimate the likelihood of extreme events regressing to the mean. Crucial for understanding decision-making and judgment under uncertainty.
The application of game-design elements and principles in non-game contexts to engage and motivate people to achieve their goals. Crucial for enhancing user engagement and motivation in various contexts.
A parameter that controls the randomness of AI-generated text, affecting creativity and coherence. Important for fine-tuning the behavior and output of AI models.
The tendency for the first items presented in a sequence to be remembered better than those in the middle. Crucial for designing information presentation and improving memory retention.
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.
A cognitive architecture model that explains how humans can learn and adapt to new tasks. Useful for understanding user learning and behavior adaptation, informing better user experience design.
A logical fallacy where people assume that specific conditions are more probable than a single general one. Important for understanding and addressing cognitive biases in user behavior.
A cognitive bias where individuals better remember the most recent information they have encountered, influencing decision-making and memory recall. Important for designing user experiences that leverage or mitigate the impact of recent information.
A cognitive bias where people judge the likelihood of an event based on its relative size rather than absolute probability. Important for understanding user decision-making biases and designing systems that present information accurately.
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.
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.
A concept that humans make decisions within the limits of their knowledge, cognitive capacity, and available time, leading to satisficing rather than optimal solutions. Crucial for designing systems and processes that account for human cognitive limitations and decision-making processes.
The percentage of visitors to a website who navigate away from the site after viewing only one page. Important for understanding user engagement and the effectiveness of a website's content and design.
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.
The tendency for individuals to put in less effort when working in a group compared to when working alone, due to reduced accountability. Crucial for understanding group dynamics and designing systems that ensure individual accountability.
A cognitive bias where people prefer familiar things over unfamiliar ones, even if the unfamiliar options are objectively better. Useful for designing interfaces and products that leverage familiar elements to enhance user comfort.