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.
The cognitive bias where people treat a set of items as more significant when they are perceived as a cohesive group. Important for understanding user perception and decision-making.
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.
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 people's decisions are influenced by how information is presented rather than just the information itself. Crucial for designers to minimize bias in how information is presented to users.
A cognitive bias where individuals overestimate the likelihood of extreme events regressing to the mean. Crucial for understanding decision-making and judgment under uncertainty.
A phenomenon where the success or failure of a design or business outcome is influenced by external factors beyond the control of the decision-makers, akin to serendipity. Important for recognizing and accounting for external influences in performance evaluations to ensure fair assessments and informed decisions.
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.
A cognitive bias where individuals evaluate outcomes relative to a reference point rather than on an absolute scale. Essential for understanding decision-making and consumer behavior.
The tendency to overvalue new innovations and technologies while undervaluing existing or traditional approaches. Important for balanced decision-making and avoiding unnecessary risks in adopting new technologies.
A phenomenon where individuals' preferences between options change when the options are presented in different ways or contexts. Important for understanding and designing around inconsistencies in user choices.
Business Rules Engine (BRE) is a software system that executes one or more business rules in a runtime production environment. Crucial for automating decision-making processes and ensuring consistency and compliance in digital products.
A cognitive bias where individuals' expectations influence their perceptions and judgments. Relevant for understanding how expectations skew perceptions and decisions among users.
A cognitive bias where the pain of losing is psychologically more powerful than the pleasure of gaining. Important for designing user experiences that account for and mitigate loss aversion.
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.
A cognitive bias where people prefer a greater variety of options when making simultaneous choices compared to sequential choices. Important for designers to consider user preferences for variety when designing choice architectures and product offerings.
The process of using statistical analysis and modeling to explore and interpret business data to make informed decisions. Essential for improving business performance, identifying opportunities for growth, and driving strategic planning.
Key Performance Indicators (KPIs) are quantifiable measures used to evaluate the success of an organization, employee, or project in meeting objectives for performance. Essential for tracking progress, making informed decisions, and aligning efforts with strategic goals across various business functions, including product design and development.
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 time management tool that helps prioritize tasks based on their urgency and importance, dividing them into four quadrants. Essential for designing productivity tools and strategies.
The tendency to overestimate the duration or intensity of the emotional impact of future events. Important for understanding user expectations and satisfaction.
The process of triggering particular aspects of a person's identity to influence their behavior or decisions. Important for designing personalized and effective user experiences.
A cognitive bias where people prefer a smaller set of higher-quality options over a larger set with lower overall quality. Useful for designing product offerings and experiences that emphasize quality over quantity for users.
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.
The tendency to overestimate how much our future preferences and behaviors will align with our current preferences and behaviors. Important for understanding user behavior and designing experiences that account for changes over time.
A cognitive bias where individuals underestimate the time, costs, and risks of future actions while overestimating the benefits. Important for realistic project planning and setting achievable goals for designers.
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.
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.
A cognitive bias where individuals favor others who are perceived to be similar to themselves, affecting judgments and decision-making. Crucial for understanding biases in team dynamics and decision-making processes among designers.
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.
A cognitive bias where people overestimate the importance of information that is readily available. Essential for designers to understand and mitigate how easily accessible information can disproportionately influence decisions.
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.
A cognitive bias where individuals tend to avoid risks when they perceive potential losses more acutely than potential gains. Important for understanding decision-making behavior in users and designing systems that mitigate risk aversion.
A cognitive bias where people rely too heavily on their own perspective and experiences when making decisions. Important for designers to recognize and mitigate their own perspectives influencing design decisions.
The study of how psychological influences affect financial behaviors and decision-making. Essential for understanding and influencing financial decision-making and behavior.
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.
A strategic approach where multiple potential solutions are tested to identify the most promising one. Crucial for innovation and reducing risk in decision-making.
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 that occurs when conclusions are drawn from a non-representative sample, focusing only on successful cases and ignoring failures. Crucial for making accurate assessments and designing systems that consider both successes and failures.
A cognitive bias where people ignore the relevance of sample size in making judgments, often leading to erroneous conclusions. Crucial for designers to account for appropriate sample sizes in research and analysis.
A prioritization technique where stakeholders use a limited budget to "buy" features they believe are most valuable, helping to prioritize the development roadmap. Useful for involving stakeholders in the decision-making process and aligning development priorities with business value.
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 strategic approach where decisions and direction are set by top-level management and flow down through the organization, often aligned with overarching business goals. Crucial for ensuring strategic alignment and coherence across all levels of an organization.
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 prioritization framework used in product management to evaluate features based on Reach, Impact, Confidence, and Effort. Crucial for making informed decisions about which product features to prioritize and develop.
Also known as Parkinson's Law of Triviality, is the tendency to spend excessive time on trivial details while neglecting more important issues. Crucial for improving project management and team efficiency.
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 process of predicting how one will feel in the future, which often involves biases and inaccuracies. Important for understanding user behavior and decision-making, aiding in the design of better user experiences.
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.
Business Intelligence (BI) encompasses technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. Crucial for making data-driven decisions and improving business performance.
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.
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.
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.
A theory that explains how individuals determine the causes of behavior and events, including the distinction between internal and external attributions. Crucial for understanding user behavior and designing experiences that address both internal and external factors.
The study of finding the best solution from a set of feasible solutions. Crucial for improving efficiency and performance in design and development processes.
Customer Advisory Board (CAB) is a group of key customers who provide feedback and insights to a company to help guide its strategic decisions. This group is crucial for aligning products and services with customer needs and expectations.
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 practice of using data analytics and metrics to make informed decisions, focusing on measurable outcomes and efficiency rather than intuition or traditional methods. Important for optimizing design processes, improving product performance, and making data-driven decisions that enhance user experience and business success.
An analysis comparing the costs and benefits of a decision or project to determine its feasibility and value. Important for making informed business and design decisions.
Bottom of Funnel (BoFu) refers to the stage in the sales funnel where prospects are close to making a purchase decision. Important for tailoring marketing and sales efforts to convert leads into customers.