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.
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 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 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 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 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.
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.
Impact, Confidence, and Ease of implementation (ICE) is a prioritization framework used in product management to evaluate features. Essential for making informed and strategic decisions about feature development and prioritization.
Explainable AI (XAI) are AI systems that provide clear and understandable explanations for their decisions and actions. This transparency is crucial for building trust and confidence in AI applications across various domains.
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.
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 type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
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.
An organizational structure that emphasizes flexibility, employee initiative, and decentralized decision-making. Useful for fostering innovation and rapid response to changes within an organization.
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.
Conversations with key stakeholders to gather insights, expectations, and feedback, ensuring their needs are understood and considered in the project. Essential for aligning project goals with stakeholder needs and obtaining valuable input for decision-making.
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.
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 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.
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 process of enabling users to take control of their interactions with a product or system, enhancing their confidence and satisfaction. Crucial for designing systems that provide users with the tools and information they need to make informed decisions.
The ability to intuitively understand what makes a product successful, including market needs, user experience, and competitive landscape. Important for making informed decisions that lead to successful product development.
A statistical measure that quantifies the amount of variation or dispersion of a set of data values. Essential for understanding data spread and variability, which helps in making informed decisions in product design and analysis.
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.
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.
The study of finding the best solution from a set of feasible solutions. Crucial for improving efficiency and performance in design and development processes.
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.
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.
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.
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.
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.
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.
The process of creating visual representations of data or information to enhance understanding and decision-making. Essential for organizing information and making complex data accessible.
The process of creating an interface that displays key performance indicators and metrics in a visually accessible way. Essential for monitoring performance and making data-driven decisions.
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.
The interpretation of historical data to identify trends and patterns. Important for understanding past performance and informing future 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.
Also known as "Maslow's Hammer," a cognitive bias where people rely too heavily on a familiar tool or method, often summarized as "if all you have is a hammer, everything looks like a nail.". Important for designers to recognize and avoid over-reliance on familiar methods in problem-solving and design.
Return on Investment (ROI) is a performance measure used to evaluate the efficiency or profitability of an investment or compare the efficiency of different investments. Crucial for assessing the financial effectiveness of business decisions, projects, or initiatives.
A research method that focuses on collecting and analyzing numerical data to identify patterns, relationships, and trends, often using surveys or experiments. Essential for making data-driven decisions and validating hypotheses with statistical evidence.
A tool used to prioritize tasks based on their impact and effort, helping to focus on high-value activities. Important for prioritizing tasks effectively to maximize impact with minimal effort.
A prioritization framework used to assess and compare the value a feature will deliver to users against the complexity and cost of implementing it. Crucial for making informed decisions about feature prioritization and resource allocation.
The practice of measuring and analyzing data about digital product adoption, usage, and performance to inform business decisions. Crucial for making data-driven decisions that improve product performance and user satisfaction.
Quantitative measures used to track and assess the performance and success of a product, such as usage rates, customer satisfaction, and revenue. Essential for making data-driven decisions to improve product performance and achieve business goals.
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.
The implied cost of additional rework caused by choosing an easy or limited solution now instead of using a better approach that would take longer. Essential for understanding and managing the long-term impacts of short-term technical decisions.
Numeronym for the word "Communications" (C + 12 letters + S). Essential for effective collaboration and information exchange.
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.
The final interaction a customer has with a brand before making a purchase. Important for understanding which touchpoints drive conversions.
The combined efforts of humans and AI systems to achieve better outcomes than either could alone. Important for leveraging the strengths of both humans and AI in various tasks.
A structured framework for product design that stands for Comprehend the situation, Identify the customer, Report customer needs, Cut through prioritization, List solutions, Evaluate trade-offs, and Summarize recommendations. Essential for guiding product managers through a comprehensive design process.
Extremely large data sets that can be analyzed computationally to reveal patterns, trends, and associations. Crucial for gaining insights and making data-driven decisions.
The representation of data through graphical elements like charts, graphs, and maps to facilitate understanding and insights. Essential for making complex data accessible and actionable for users.
Quantitative data that provides broad, numerical insights but often lacks the contextual depth that thick data provides. Useful for capturing high-level trends and patterns, but should be complemented with thick data to gain a deeper understanding of user behavior and motivations.
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 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.
A cognitive bias where people wrongly believe they have direct insight into the origins of their mental states, while treating others' introspections as unreliable. Important for designing experiences that account for discrepancies between user self-perception and actual behavior.
The process of making predictions about future trends based on current and historical data. Useful for anticipating user needs and market trends to inform design decisions.
Measurements used to evaluate the success of an organization, employee, or process in meeting goals. Necessary for assessing performance and driving continuous improvement.