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.
An environment closer to production where final testing and validation occur. Crucial for ensuring that products are ready for production deployment.
The degree to which a product satisfies strong market demand, often considered a key indicator of a product's potential for success. Essential for validating the viability of a product in the market and guiding strategic decisions.
The process of testing product ideas and assumptions with real customers to ensure they meet market needs. Essential for reducing risk and ensuring product-market fit.
A framework for discovering and validating the right market for a product, building the right product features, and validating the business model. Important for ensuring that products meet market needs and customer expectations.
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.
A demonstration of the new features and functionalities of a product release, typically used to showcase progress and gather feedback before the official launch. Crucial for validating product features and gathering stakeholder feedback before a full release.
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.
The process of determining whether there is a need or demand for a product in the target market, often through testing and feedback. Crucial for ensuring that a product will meet market needs and be successful.
Proof of Concept (PoC) is a demonstration, usually in the form of a prototype or pilot project, to verify that a concept or theory has practical potential. Crucial for validating ideas, demonstrating feasibility, and securing support for further development in product design and innovation processes.
Minimum Viable Feature (MVF) is the smallest possible version of a feature that delivers value to users and allows for meaningful feedback collection. Crucial for rapid iteration in product development, enabling teams to validate ideas quickly and efficiently while minimizing resource investment.
The process of evaluating a product by testing it with real users to gather feedback and identify usability issues. Essential for validating design decisions and ensuring the product meets user needs.
Product Advisory Council (PAC) is a group of customers, industry experts, and stakeholders who provide feedback and guidance on a company's product strategy and development. Essential for aligning products with market needs and driving innovation.
A type of testing conducted to determine if the requirements of a specification are met, often the final step before delivery to the customer. Important for ensuring that a product meets the defined criteria and is ready for release.
A practice of performing testing activities in the production environment to monitor and validate the behavior and performance of software in real-world conditions. Crucial for ensuring the stability, reliability, and user satisfaction of digital products in a live environment.
The process of creating an early model of a product to test and validate ideas, features, and design choices before full-scale production. Essential for validating design choices and gathering user feedback early in the development process.
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.
The process of quickly creating a preliminary version of a product to test and validate ideas before full-scale development. Important for validating design concepts and gathering user feedback early.
A preliminary testing phase conducted by internal staff to identify bugs before releasing the product to external testers or customers. Crucial for ensuring product quality and functionality before broader release.
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.
Research conducted to assess the effectiveness, usability, and impact of a design or product. Essential for validating design decisions and improving user experiences.
A preliminary version of a project or system used to test and validate its feasibility before full-scale implementation. Crucial for identifying potential issues and making necessary adjustments to improve the final product.
The process of running a system for an extended period to detect early failures and ensure reliability. Important for ensuring the stability and performance of digital products before full-scale deployment.
A type of usability testing conducted at the end of the design process to evaluate the effectiveness and overall user experience. Important for assessing the final design's usability and identifying any remaining issues.
A testing methodology that verifies the complete workflow of an application from start to finish, ensuring all components work together as expected. Important for ensuring the reliability and performance of digital products, leading to better user satisfaction and fewer post-launch issues.
User Acceptance Testing (UAT) is the final phase of the software testing process where actual users test the software to ensure it meets their requirements. Crucial for validating that the software functions correctly in real-world scenarios before its release.
A statistical method used to assess the generalizability of a model to unseen data, involving partitioning a dataset into subsets for training and validation. Essential for evaluating model performance and preventing overfitting in digital product analytics.
The process of testing and evaluating a design to ensure it meets user needs and business goals before final implementation. Crucial for ensuring that designs are effective and meet intended objectives.
User-Centered Design (UCD) is an iterative design approach that focuses on understanding users' needs, preferences, and limitations throughout the design process. Crucial for creating products that are intuitive, efficient, and satisfying for the intended users.
The practice of quickly testing and iterating on ideas to validate assumptions and learn from user feedback in a short time frame. Essential for agile development and making data-driven decisions efficiently.
Also known as Expert Review, a method where experts assess a product or system against established criteria to identify usability issues and areas for improvement. Essential for leveraging expert insights to enhance product quality and usability.
Reasons to Believe (RTB) is a marketing concept that refers to the evidence or arguments that support a product's claims and persuade consumers of its benefits. Essential for building trust and credibility with customers.
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.
Know Your Customer (KYC) is a process used by businesses to verify the identity of their clients and assess potential risks of illegal intentions for the business relationship. Essential for preventing fraud, money laundering, and terrorist financing, particularly in financial services, while also ensuring compliance with regulatory requirements and building trust with customers.
A research method in which participants interact with a series of potential product concepts in quick succession, providing rapid feedback on multiple ideas. Useful for quickly gathering user feedback on various concepts and iterating based on their preferences.
An environment used for testing software to identify issues and ensure quality before production deployment. Important for detecting and fixing bugs to ensure the software's reliability and performance.
A bias that occurs when the sample chosen for a study or survey is not representative of the population being studied, affecting the validity of the results. Important for ensuring the accuracy and reliability of research findings and avoiding skewed data.
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 method of creating and testing user interfaces using hand-drawn sketches and mockups on paper. Essential for early-stage design validation and gathering user feedback.
A testing method where the internal structure of the system is not known to the tester, focusing solely on input and output. Essential for validating the functionality of digital products from an end-user perspective.
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.
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.
A research approach that starts with a theory or hypothesis and uses data to test it, often moving from general to specific. Essential for validating theories and making informed decisions based on data.
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 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 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 strategic approach where multiple potential solutions are tested to identify the most promising one. Crucial for innovation and reducing risk in decision-making.
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.
A model by Don Norman outlining the cognitive steps users take when interacting with a system: goal formation, planning, specifying, performing, perceiving, interpreting, and comparing. Important for designing user-friendly and effective products by understanding and supporting user behavior at each stage.
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.
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.
A theory of motivation that emphasizes the importance of autonomy, competence, and relatedness in fostering intrinsic motivation and psychological well-being. Important for understanding how to design experiences that support user motivation and well-being.
Design strategies aimed at preventing user errors before they occur. Crucial for enhancing usability and ensuring a smooth user experience.
Plan-Do-Check-Act (PDCA) is an iterative four-step management method used for continuous improvement of processes and products. Essential for quality control and operational efficiency.
A focus on the results or benefits of a project rather than the activities or deliverables produced. Crucial for ensuring that efforts are aligned with achieving meaningful results.
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.
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.
A Gestalt principle that states that objects that are similar in appearance are perceived as being more related than objects that are dissimilar. Essential for creating visually cohesive and intuitive designs.
A problem-solving approach that involves breaking down complex problems into their most basic, foundational elements. Crucial for developing innovative solutions by understanding and addressing core issues.
The process of encoding sensory input that has particular meaning or can be applied to a context, enabling deeper processing and memory retention. Important for understanding how information is processed and stored, enhancing design of educational content.