Ideation
The process of generating a broad set of ideas on a given topic, with no attempt to judge or evaluate them initially. Crucial for creative problem-solving and developing innovative solutions in product design and development.
The process of generating a broad set of ideas on a given topic, with no attempt to judge or evaluate them initially. Crucial for creative problem-solving and developing innovative solutions in product design and development.
The study of mental processes such as perception, memory, reasoning, and problem-solving. Important for designing interfaces that align with how users process information and make decisions.
Situation-Complication-Resolution (SCR) is a communication and problem-solving framework used to structure information clearly and logically. Crucial for effectively conveying complex ideas and solutions in business and design contexts.
A cognitive bias where people tend to believe that others are more affected by media messages and persuasive communications than they are themselves. Important for understanding media influence and designing communications that account for this bias in user perception.
A type of data visualization that uses dots to represent values for two different numeric variables, plotted along two axes. Essential for identifying relationships, patterns, and outliers in datasets used in digital product design and analysis.
The phenomenon where taking a test on material improves long-term retention of that material more than additional study sessions. Crucial for designing educational tools and methods that enhance learning and retention.
The systematic computational analysis of data or statistics to understand and improve business performance. Essential for data-driven decision making in design, product management, and marketing.
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 tool used to organize ideas and data into groups based on their natural relationships. Essential for designers and product managers to synthesize information and generate insights.
A cognitive shortcut that relies on the recognition of one option over another to make a decision, often used when individuals have limited information. Crucial for designing interfaces and experiences that facilitate quick and effective decision-making.
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 method of testing two identical versions of a webpage or app to ensure the accuracy of the testing tool. Important for validating the effectiveness of A/B testing tools and processes.
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 theoretical approach that focuses on observable behaviors and dismisses internal processes, emphasizing the role of environmental factors in shaping behavior. Foundational for understanding how external factors influence user behavior and for designing behavior-based interventions.
The study of the practices and possibilities of music, covering elements like rhythm, melody, harmony, and form. Essential for understanding musical structure, composition, and performance.
Data points that differ significantly from other observations and may indicate variability in a measurement, experimental errors, or novelty. Crucial for identifying anomalies and ensuring the accuracy and reliability of data in digital product design.
Metrics that may look impressive but do not provide meaningful insights into the success or performance of a product or business, such as total page views or social media likes. Important for distinguishing between metrics that drive real business value and those that do not.
Call to Action (CTA) is a prompt that encourages users to take a specific action, such as signing up for a newsletter or making a purchase. Crucial for guiding user behavior and increasing engagement or conversions on digital platforms.
A phenomenon where new information interferes with the ability to recall previously learned information, affecting memory retention. Crucial for understanding memory dynamics and designing educational or training programs.
The use of AI and advanced analytics to divide users into meaningful segments based on behavior and characteristics. Crucial for personalized marketing and improving user experience.
The integration and application of knowledge and skills from multiple disciplines to enhance understanding and innovation. Crucial for fostering a holistic approach to problem-solving and design.
The process of self-examination and adaptation in AI systems, where models evaluate and improve their own outputs or behaviors based on feedback. Crucial for enhancing the performance and reliability of AI-driven design solutions by fostering continuous learning and improvement.
A range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter. Essential for making inferences about population parameters and understanding the precision of estimates in product design analysis.
The systematic investigation of competitor activities, products, and strategies to gain insights and inform decision-making. Crucial for staying competitive and improving product and service offerings.
A product development approach where teams start with the desired customer experience and work backwards to determine what needs to be built to achieve that outcome. Essential for ensuring that product development is aligned with customer needs and expectations.
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.
Social, Technological, Economic, Environmental, Political, Legal, and Ethical (STEEPLE) is an analysis tool that examines the factors influencing an organization. Crucial for comprehensive strategic planning and risk management in product design.
A brainstorming technique where participants draw their ideas instead of writing them down. Important for stimulating creative thinking and visual problem-solving.
Emotional states where individuals are calm and rational, often contrasted with hot states where emotions run high. Important for understanding decision-making processes and designing experiences that accommodate both states.
The use of statistical techniques and algorithms to analyze historical data and make predictions about future outcomes. Important for optimizing marketing strategies and anticipating customer needs.
A model of organizational change management that involves preparing for change (unfreeze), implementing change (change), and solidifying the new state (refreeze). Important for successfully implementing and sustaining changes in product design processes and organizational practices.
A method in natural language processing where multiple prompts are linked to generate more complex and contextually accurate responses. Essential for enhancing the capability and accuracy of AI models in digital products that rely on natural language understanding.
A research approach that starts with observations and develops broader generalizations or theories from them. Useful for discovering patterns and generating new theories from data.
A visual representation of the user or customer journey, highlighting key interactions, emotions, and pain points. Essential for identifying opportunities to improve user or customer experiences.
A mode of thinking, derived from Dual Process Theory, that is fast, automatic, and intuitive, often relying on heuristics and immediate impressions. Important for understanding how users make quick decisions and respond to design elements instinctively, aiding in the creation of intuitive and user-friendly interfaces.
A cognitive bias that causes people to attribute their own actions to situational factors while attributing others' actions to their character. Essential for helping designers recognize their own situational influences on interpreting user behavior and feedback.
The tendency for people to overestimate their ability to control events. Important for understanding user behavior and designing experiences that manage expectations.
A graphical representation of the distribution of numerical data, typically showing the frequency of data points in successive intervals. Important for analyzing and interpreting data distributions, aiding in decision-making and optimization in product design.
The process of designing, developing, and managing tools and techniques for measuring performance and collecting data. Essential for monitoring and improving system performance and user experience.
A data visualization technique that shows the intensity of data points with varying colors, often used to represent user interactions on a website. Essential for understanding user behavior and identifying areas of interest or concern in digital product interfaces.
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 technique used to evaluate a product or system by testing it with real users to identify any usability issues and gather qualitative and quantitative data on their interactions. Crucial for identifying and resolving usability issues to improve user satisfaction and performance.
A cognitive bias where individuals overestimate the accuracy of their judgments, especially when they have a lot of information. Important for understanding and mitigating overconfidence in user decision-making.
A usability test to see what impression users get within the first 10 seconds of interacting with a product or page. Important for designers to quickly gauge initial user impressions and improve immediate engagement.
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 mathematical framework used to analyze strategic interactions where the outcomes depend on the actions of multiple decision-makers. Useful for designing systems and processes that involve competitive or cooperative interactions.
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.
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.
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 research method that involves repeated observations of the same variables over a period of time. Crucial for understanding changes and developments over time.
The degree to which a product or system can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in a specified context of use. Essential for creating products that are easy to use and meet user needs effectively.
A psychological phenomenon where people remember uncompleted or interrupted tasks better than completed tasks. Crucial for designing engaging experiences that leverage task incompletion to maintain user interest.
A usability testing method where users interact with a system they believe to be autonomous, but which is actually operated by a human. Essential for testing concepts and interactions before full development.
The psychological discomfort experienced when parting with money, influenced by the payment method and context. Crucial for understanding spending behavior and designing payment systems that mitigate discomfort.
Large Language Model (LLM) is an advanced artificial intelligence system trained on vast amounts of text data to understand and generate human-like text. Essential for natural language processing tasks, content generation, and enhancing human-computer interactions across various applications in product design and development.
An ongoing process of learning about user needs and validating assumptions through continuous research and experimentation. Crucial for staying responsive to user needs and improving products iteratively.
Happiness, Engagement, Adoption, Retention, and Task (HEART) is a framework used to measure and improve user experience success. Important for systematically evaluating and enhancing user experience.
The perception of a relationship between two variables when no such relationship exists. Crucial for understanding and avoiding biases in data interpretation and decision-making.
The mental and physical effort required to complete a task, influencing user experience and performance. Crucial for designing systems that minimize cognitive and physical load, enhancing usability and efficiency.
The tendency for people to value products more highly if they have put effort into assembling them. Important for understanding user satisfaction and product attachment.