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.
A user-centered design process that involves understanding users' needs and workflows through field research and applying these insights to design. Essential for creating designs that are deeply informed by user contexts and behaviors.
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.
Minimum Viable Product (MVP) is a version of a product with just enough features to be usable by early customers who can then provide feedback for future product development. Essential for validating product ideas quickly and cost-effectively, allowing teams to learn about customer needs without fully developing the product.
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.
A principle stating that as the flexibility of a system increases, its usability often decreases, and vice versa. Crucial for balancing versatility and ease of use in design.
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 evaluation of products based on their ability to influence and shape user behavior. Useful for assessing how well a product guides and influences user actions and decisions.
The practice of deeply understanding and sharing the feelings of users to create products and services that truly meet their needs. Crucial for creating user-centered designs that resonate with users' emotions and experiences.
A problem-solving method that explores all possible solutions by examining the structure and relationships of different variables. Useful for generating innovative design solutions and exploring a wide range of possibilities in digital product development.
Market Requirements Document (MRD) is a comprehensive document that outlines the market's needs, target audience, and business objectives for a product. It serves as a crucial tool for aligning product development efforts with market demands and business goals, ensuring that the final product meets customer needs and achieves market success.
Minimum Viable Experience (MVE) is the simplest version of a product that delivers a complete and satisfying user experience while meeting core user needs. Essential for rapidly validating product concepts and user experience designs while ensuring that even early versions of a product provide value and a positive impression to users.
The process of understanding user behaviors, needs, and motivations through various qualitative and quantitative methods. Essential for designing user-centered products and ensuring they meet actual user needs.
Information provided by users about their experience with a product, used to inform improvements and adjustments. Crucial for continuous improvement and user-centered design.
A brainstorming technique that involves listing all possible attributes of a product or problem to generate new ideas and solutions. Useful for generating creative solutions and improving product features.
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 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.
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.
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.
The ability to recognize, understand, and manage one's own emotions and the emotions of others. Essential for designing empathetic user experiences and effective team collaboration.
The stages a product goes through from introduction to growth, maturity, and decline, influencing marketing and development strategies. Crucial for planning product development and marketing strategies at each stage of the product's life.
An approach to design that relies on data and analytics to inform decisions and measure success. Crucial for making informed design decisions that are backed by evidence.
Product Development is the process of bringing a new product to market or improving an existing one. Crucial for innovation, meeting customer needs, and maintaining a competitive edge.
An experimental design where subjects are paired based on certain characteristics, and then one is assigned to the treatment and the other to the control group. Important for reducing variability and improving the accuracy of experimental results.
The speed at which users start using a new product, typically measured as a percentage of the target market over a specific period. Essential for evaluating the success of a product launch and planning subsequent strategies.
A pricing strategy where a core product is sold at a low price, but complementary products are sold at higher prices. Useful for designing pricing strategies that maximize revenue from complementary products.
New Product Development (NPD) is the complete process of bringing a new product to market, from idea generation to commercialization. Essential for companies to innovate, stay competitive, and meet evolving customer needs through a structured approach to creating and launching new offerings.
The risk that users will find the product difficult or confusing to use, preventing them from effectively utilizing its features. Crucial for making sure the product is user-friendly and intuitive, enhancing the user experience and adoption.
Minimum Marketable Feature (MMF) is the smallest set of functionality that delivers significant value to users and can be marketed effectively. Crucial for prioritizing development efforts and releasing valuable product increments quickly, balancing user needs with business objectives.
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 research technique that explores the context in which users interact with a product, service, or environment to understand their needs and behaviors. Crucial for gaining deep insights into user contexts and designing more relevant solutions.
A usability testing method where participants verbalize their thoughts while interacting with a product. Essential for understanding user thought processes and identifying usability issues.
A collaborative tool used to visualize what a user thinks, feels, says, and does to better understand their experiences and needs. Essential for gaining deep insights into user behavior and guiding design decisions.
A research method used to determine how desirable a product or feature is to potential users. Crucial for understanding user preferences and guiding product development.
A systematic evaluation of all features in a product to determine their usage, effectiveness, and alignment with business goals. Essential for optimizing product performance and user satisfaction.
Model-Based Systems Engineering (MBSE) is a methodology that uses visual modeling to support system requirements, design, analysis, and validation activities throughout the development lifecycle. Essential for managing complex systems, improving communication among stakeholders, and enhancing the overall quality and efficiency of systems engineering processes.
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.
The process of comparing design metrics to historical performance, competitive standards, or industry best practices to identify areas for improvement. Crucial for measuring progress, improving practice maturity, and evaluating competitive differentiation.
An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Essential for driving data-informed decision making, predicting trends, and uncovering valuable insights in digital product design and development.
Needs and expectations that are not explicitly stated by users but are inferred from their behavior and context. Crucial for identifying and addressing unarticulated user needs.
A research method that involves repeated observations of the same variables over a period of time. Crucial for understanding changes and developments over time.
Behavioral Science (BeSci) is the study of human behavior through systematic analysis and investigation. Essential for understanding and influencing user behavior in design and product development.
The value or satisfaction derived from a decision, influencing the choices people make. Crucial for understanding user preferences and designing experiences that maximize satisfaction.
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.
A principle stating that as investment in a single area increases, the rate of return on that investment eventually decreases. Important for understanding and optimizing resource allocation in product design and development.
A market in which vendors offer goods and services specific to an industry, trade, profession, or other group of customers with specialized needs. Important for developing targeted digital products that cater to the unique requirements of specific industries or sectors.
The area within a market where unmet needs or problems present potential for new products or services. Essential for identifying new business opportunities.
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.
A consensus-building technique where participants show their level of agreement or support by raising zero to five fingers. Useful for quickly gauging team agreement and making collaborative decisions in product design and development meetings.
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.
Also known as the 68-95-99.7 Rule, it states that for a normal distribution, nearly all data will fall within three standard deviations of the mean. Important for understanding the distribution of data and making predictions about data behavior in digital product design.
A statistical theory that states that the distribution of sample means approximates a normal distribution as the sample size becomes larger, regardless of the population's distribution. Important for making inferences about population parameters and ensuring the validity of statistical tests in digital product design.
A systematic process for determining and addressing needs or gaps between current conditions and desired outcomes. Important for identifying user requirements and guiding the development of digital products that meet those needs.
The percentage of users who start but do not complete a desired action, such as completing a form or purchasing a product. Important for identifying issues in user flows and improving conversion rates.
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.
The process of identifying user needs and market opportunities to inform the development of new products or features. Crucial for ensuring that products are user-centered and meet real market demands.
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 qualitative research method involving direct conversations with users to gather insights into their needs, behaviors, and experiences. Essential for gaining deep insights into user perspectives and informing design decisions.
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.
A behavioral economics concept where people categorize and treat money differently depending on its source or intended use. Crucial for understanding financial behavior and designing systems that align with users' mental accounting practices.