Reference Dependence
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.
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.
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 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 theory in economics that models how rational individuals make decisions under risk by maximizing the expected utility of their choices. Essential for understanding decision-making under risk.
A psychological phenomenon where a person who has done a favor for someone is more likely to do another favor for that person than if they had received a favor from them. Useful for building positive relationships and encouraging cooperative behavior in design and user interactions.
The use of natural language processing to identify and extract subjective information from text, determining the sentiment expressed. Crucial for understanding public opinion and customer feedback.
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 process of investigating and experimenting with new technologies to understand their potential applications and benefits. Essential for innovation and staying ahead in a rapidly changing technological landscape.
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 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.
Lifetime Value (LTV) is a metric that estimates the total revenue a business can expect from a single customer account throughout their relationship. Crucial for informing customer acquisition strategies, retention efforts, and overall business planning by providing insights into long-term customer profitability.
A behavior where users repeatedly bounce back and forth between a search engine results page and individual search results. Important for identifying issues in search result relevancy and user satisfaction.
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.
Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) is an acronym for describing the challenging conditions of the modern world. Important for understanding and navigating dynamic and unpredictable environments.
The style and attitude of the communication in a product, reflecting the brand's personality and affecting how messages are perceived by users. Important for creating a consistent and engaging user experience that aligns with the brand identity.
A type of artificial intelligence capable of generating new content, such as text, images, and music, by learning from existing data. Important for automating creative processes and generating novel outputs.
A Japanese term meaning "the real place," used in Lean management to describe the place where value is created. Important for understanding the actual processes and identifying areas for improvement.
The level of awareness or popularity a product or brand has among consumers. Essential for understanding brand perception and guiding marketing and product design strategies to enhance visibility and user adoption.
The practice of linking one page of a website to another page on the same website, improving navigation, user experience, and SEO. Essential for enhancing website structure, user engagement, and search engine optimization.
The risk that the product will not be financially or strategically sustainable for the business, potentially leading to a lack of support or profitability. Essential for ensuring that the product aligns with business goals and can be maintained and supported long-term.
A simple sorting algorithm that repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. Important for understanding basic algorithmic principles and their applications.
The process by which a measure or metric comes to replace the underlying objective it is intended to represent, leading to distorted decision-making. Important for ensuring that metrics accurately reflect true objectives and designing systems that prevent metric manipulation.
A tool used during brainstorming sessions to prompt and inspire creative thinking, often containing questions, scenarios, or constraints. Useful for facilitating structured ideation sessions and sparking new ideas.
A brief overview of the main points or sections of a document or web page. Crucial for helping users quickly understand the key takeaways and decide whether to read further.
The speed at which leads move through the sales funnel. Crucial for understanding and optimizing the sales process.
The risk that the product being developed will not deliver sufficient value to the users, meaning it won't meet their needs or solve their problems. Critical for ensuring the product will be desirable and valuable to the users, which is essential for its success.
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.
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 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.
A statistical method used to identify underlying relationships between variables by grouping them into factors. Crucial for simplifying data and identifying key variables in research.
The use of touch sensations to communicate information to users, often through vibrations or other tactile responses in devices. Essential for enhancing user interaction and providing sensory feedback.
A behavioral economics model that explains decision-making as a conflict between a present-oriented "doer" and a future-oriented "planner". Useful for understanding user decision-making and designing interventions that balance short-term and long-term goals.
The time it takes for a webpage to load and become interactive, impacting user experience and search engine rankings. Essential for improving user satisfaction and SEO performance.
A persuasion strategy that involves getting a person to agree to a small request to increase the likelihood of agreeing to a larger request later. Crucial for building user commitment and enhancing marketing and sales strategies.
A design pattern that combines human and machine intelligence to enhance decision-making and problem-solving. Important for leveraging AI to support and amplify human capabilities.
A psychological phenomenon where the desire for harmony and conformity in a group results in irrational or dysfunctional decision-making. Crucial for recognizing and mitigating the risks of poor decision-making in teams.
Knowledge Organization System (KOS) refers to a structured framework for organizing, managing, and retrieving information within a specific domain or across multiple domains. Essential for improving information findability, enhancing semantic interoperability, and supporting effective knowledge management in digital environments.
A psychological phenomenon where individuals are perceived as more likable if they make a mistake, provided they are generally competent. Important for understanding human perception and leveraging relatability in marketing and leadership.
Marketing Qualified Lead (MQL) is a prospective customer who has shown interest in a company's product or service and meets specific criteria indicating a higher likelihood of becoming a customer. Essential for prioritizing leads and optimizing the efficiency of sales and marketing efforts by focusing resources on prospects most likely to convert.
The process of turning potential customers into paying customers, often measured by the conversion rate. Essential for understanding and optimizing the customer journey.
A research method where participants record their activities, experiences, and thoughts over a period of time, providing insights into their behaviors and needs. Important for gaining in-depth, longitudinal insights into user experiences.
A concise statement of what the team aims to achieve during a sprint, providing direction and a shared understanding of the sprint's purpose. Crucial for ensuring team alignment and focus on the most important outcomes during a sprint.
A sales technique used to uncover a prospect's pain points through a series of targeted questions. Important for understanding customer needs and driving effective sales conversations.
A framework for prioritizing product features based on their impact on customer satisfaction, classifying features into categories such as basic, performance, and delight. Crucial for understanding customer needs and prioritizing features that enhance satisfaction.
A strategic research process that involves evaluating competitors' products, services, and market positions to identify opportunities and threats. Essential for informing product strategy, differentiating offerings, and gaining a competitive advantage in the market.
Systematic errors in AI models that arise from the data or algorithms used, leading to poor outcomes. Important for ensuring fairness and accuracy in AI systems.
A guided, interactive overlay that introduces users to features or tasks within an application. Crucial for onboarding new users and enhancing user understanding of complex features.
The organizational structure and dynamics of teams within a company, designed to enhance collaboration and delivery. Important for optimizing team performance and project outcomes.
A structured framework for organizing information, defining the relationships between concepts within a specific domain to enable better understanding, sharing, and reuse of knowledge. Important for creating clear and consistent data models, improving communication, and enhancing the efficiency of information retrieval and management.
Data points that represent an individual's, team's, or company's performance in the sales process. Essential for tracking progress, identifying issues, and optimizing sales strategies.
A pattern of rapid and sustained growth after a period of linear or stagnant growth, resembling the shape of a hockey stick. Crucial for understanding and planning for rapid expansion phases in digital product lifecycle and business strategy.
The principle that the more a metric is used to make decisions, the more it will be subject to corruption and distort the processes it is intended to monitor. Important for understanding the limitations and potential distortions of metrics in design and evaluation.
A type of bias that occurs when the observer's expectations or beliefs influence their interpretation of what they are observing, including experimental outcomes. Essential for ensuring the accuracy and reliability of research and data collection.
A cognitive bias where people perceive past events as having been more predictable than they actually were. Important for understanding and mitigating biases in user feedback and decision-making.
A distributed version control system for tracking changes in source code during software development. Essential for collaborative development and managing codebase evolution in digital product design.
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.
The study of strategic decision making, incorporating psychological insights into traditional game theory models. Useful for understanding complex user interactions and designing systems that account for strategic behavior.
The tendency for people to defer purchasing decisions to a later time, often leading to procrastination. Important for understanding consumer behavior and optimizing sales strategies.
A structured classification of risks into categories, helping organizations identify, assess, and manage different types of risks. Important for understanding and managing risks effectively within an organization.
A skill set that combines deep knowledge in a single area (the vertical stroke) with a broad understanding across multiple disciplines (the horizontal stroke). Valuable for fostering versatility and collaboration within teams, enhancing problem-solving and innovation.