Technical Feasibility
The practicality of implementing a solution based on technical constraints and capabilities. Crucial for evaluating the viability of design and development projects.
The practicality of implementing a solution based on technical constraints and capabilities. Crucial for evaluating the viability of design and development projects.
A logical fallacy in which it is assumed that qualities of one thing are inherently qualities of another, due to an irrelevant association. Important for avoiding incorrect associations in user research and data interpretation.
The ability to use learned knowledge and experience, often increasing with age and accumulated learning. Important for understanding how expertise and knowledge accumulation impact design and decision-making.
The process by which search engines organize and store web content to facilitate fast and accurate information retrieval. Crucial for understanding how search engines work and ensuring that web content is accessible and searchable.
The phenomenon where people remember information better when it is presented through multiple sensory modalities rather than a single modality. Crucial for enhancing memory retention and understanding through multimodal presentations.
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.
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.
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.
A behavioral economic theory that describes how people choose between probabilistic alternatives that involve risk, where the probabilities of outcomes are known. Crucial for understanding decision-making under risk and designing systems that align with user behavior.
A usability technique used to evaluate the findability and labeling of topics in a website's structure by having participants find specific items in a simplified text version of the site. Crucial for improving information architecture and ensuring users can navigate a website effectively.
A logical fallacy where anecdotal evidence is used to make a broad generalization. Crucial for improving critical thinking and avoiding misleading conclusions.
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 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.
Code added to a webpage to help search engines understand the content and provide more informative results for users, enhancing SEO. Essential for improving SEO and ensuring that search engines can accurately interpret webpage content.
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.
Domain-Driven Design (DDD) is an approach to software development that focuses on modeling the business domain and its logic. Essential for aligning software development with business needs and creating maintainable systems.
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.
A mental shortcut that relies on immediate examples that come to mind when evaluating a specific topic, concept, method, or decision. Crucial for understanding how people make decisions and the biases that influence their choices.
A phenomenon where people perceive an item as more valuable when it is free, leading to an increased likelihood of choosing the free item over a discounted one. Important for understanding consumer behavior and designing effective marketing strategies.
A situation in which an individual is unable to make a decision due to the overwhelming number of options available. Important for designing interfaces that streamline decision-making processes for users.
A set of fundamental principles and guidelines that inform and shape user research practices. Crucial for maintaining consistency and ensuring high-quality user insights.
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.
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.
The spread and pattern of data values in a dataset, often visualized through graphs or statistical measures. Critical for understanding the characteristics of data and informing appropriate analysis techniques in digital product development.
The degree to which the operations and decisions of an AI system are understandable and explainable to users. Crucial for building trust and ensuring ethical AI use.
A metric that predicts how well a specific page will rank on search engine result pages (SERPs). Important for understanding and improving a webpage's search engine performance.
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.
The complete set of experiences that customers go through when interacting with a company, from initial contact to post-purchase. Essential for understanding and optimizing each touchpoint in the customer lifecycle.
A step-by-step guide that helps users complete a complex task by breaking it down into manageable steps. Crucial for improving usability and ensuring users can successfully complete multi-step processes.
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.
An economic approach that treats human attention as a scarce commodity, focusing on capturing and retaining user attention. Crucial for understanding user engagement and designing products that effectively capture and retain attention.
The emotional attachment an employee feels toward their organization, which influences their desire to stay. Useful for understanding employee retention and motivation in organizational design and management.
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.
Moment of Truth (MoT) refers to any instance where a customer interacts with a brand, product, or service in a way that leaves a significant impression. Crucial for identifying key touchpoints in the customer journey and optimizing them to enhance overall user experience and brand perception.
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.
A search method that seeks to improve search accuracy by understanding the contextual meaning of terms in a query rather than just matching keywords. Important for understanding modern search algorithms and optimizing content accordingly.
A statistical phenomenon where a large number of hypotheses are tested, increasing the chance of a rare event being observed. Crucial for understanding and avoiding false positives in data analysis.
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 document that provides a high-level overview of a product, including its objectives, target market, key features, and requirements, used to guide development efforts. Essential for ensuring that all stakeholders have a clear and consistent understanding of the product.
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.
Garbage In-Garbage Out (GIGO) is a principle stating that the quality of output is determined by the quality of the input, especially in computing and data processing. Crucial for ensuring accurate and reliable data inputs in design and decision-making processes.
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.
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.
Research conducted in natural settings to collect data on how people interact with products or environments in real-world conditions. Crucial for gaining authentic insights into user behaviors and contexts.
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 statistical method that models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data. Essential for predicting outcomes and understanding relationships between variables in digital product design and analysis.
A learning method that involves teaching a concept to a novice to identify gaps in understanding and reinforce knowledge. Important for enhancing comprehension and retention of complex subjects.
A cognitive bias where individuals evaluate the value of bundled items differently than they would if the items were evaluated separately. Important for understanding user behavior and designing effective product bundles and pricing strategies.
Visual cues or instructions integrated into an interface to guide users on how to use certain features or functionalities. Important for improving user onboarding and enhancing the user experience.
Ontology is a comprehensive model that includes entities, their attributes, and the complex relationships between them, while taxonomy is a hierarchical classification system that organizes entities into parent-child relationships. Essential for understanding the depth and scope of data organization, helping to choose the appropriate structure for information management and retrieval.
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.
A research method that involves observing subjects in their natural environment. Crucial for gathering authentic data and insights into real-world behaviors and interactions.
The technology of transmitting and understanding information through touch. Crucial for enhancing user interactions with devices and systems through tactile feedback.
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.
A statistical rule stating that nearly all values in a normal distribution (99.7%) lie within three standard deviations (sigma) of the mean. Important for identifying outliers and understanding variability in data, aiding in quality control and performance assessment in digital product design.
The dynamic system of content creation, distribution, and interaction within an environment. Important for understanding how content flows and interacts within a system.
An algorithm used by Google Search to rank web pages in their search engine results, based on the number and quality of links to a page. Essential for understanding search engine optimization and improving website visibility.
An event where developers, designers, and other stakeholders collaborate intensively on software projects, typically within a short timeframe. Important for fostering innovation, team collaboration, and rapid prototyping of new ideas in digital product development.
The final interaction a customer has with a brand before making a purchase. Important for understanding which touchpoints drive conversions.
Numeronym for the word "Internationalization" (I + 18 letters + N), enabling localization for different languages, regions, and cultures without requiring extensive rework. Important for expanding product reach to global markets.