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.
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.
An environment closer to production where final testing and validation occur. Crucial for ensuring that products are ready for production deployment.
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.
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.
The extent to which a measure represents all facets of a given construct, ensuring the content covers all relevant aspects. Important for ensuring that assessments and content accurately reflect the intended subject matter.
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 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.
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.
A time-constrained, intensive process that helps teams quickly design, prototype, and test ideas. Important for rapidly developing and validating design solutions.
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.
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.
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.
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 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.
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.
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.
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.
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 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.
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 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.
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 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.
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 used to determine how desirable a product or feature is to potential users. Crucial for understanding user preferences and guiding product development.
A method used in AI and machine learning to ensure prompts and inputs are designed to produce the desired outcomes. Essential for improving the accuracy and relevance of AI responses.
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.
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.
An experimental design where different groups of participants are exposed to different conditions, allowing for comparison between groups. Important for understanding and applying different experimental designs in user research.
A statistical phenomenon where two independent events appear to be correlated due to a selection bias. Important for accurately interpreting data and avoiding misleading conclusions.
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.
Design strategies aimed at preventing user errors before they occur. Crucial for enhancing usability and ensuring a smooth user experience.
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 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 meeting at the end of a sprint where the development team presents their completed work to stakeholders. Crucial for gathering feedback and demonstrating progress.
A quick and cost-effective usability testing method where feedback is gathered from users in informal settings, often in public places. Useful for gaining rapid insights into user behavior and improving designs iteratively.
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.
The belief in one's ability to succeed in specific situations or accomplish a task, influencing motivation and behavior. Crucial for designing systems that enhance user confidence and encourage goal achievement.
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 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.
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.
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.
A set of fundamental principles and guidelines that inform and shape user research practices. Crucial for maintaining consistency and ensuring high-quality user insights.
A principle that states the time it takes to make a decision increases with the number and complexity of choices available. Crucial for designing user interfaces that minimize cognitive load and enhance decision-making efficiency.
Software Requirements Specification (SRS) is a detailed document that outlines the functional and non-functional requirements of a software system. Crucial for ensuring clear communication and understanding between stakeholders and the development team.
In AI, the generation of incorrect or nonsensical information by a model, particularly in natural language processing. Important for understanding and mitigating errors in AI systems.
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 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 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.
A tendency for respondents to answer questions in a manner that is not truthful or accurate, often influenced by social desirability or survey design. Important for understanding and mitigating biases in survey and research data.
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 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 tendency for negative information to have a greater impact on one's psychological state and processes than neutral or positive information. Important for understanding and mitigating the impact of negative information.
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.
Human in the Loop (HITL) integrates human judgment into the decision-making process of AI systems. Crucial for ensuring AI reliability and alignment with human values.
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.