Zero-Risk Bias
A cognitive bias where people prefer the option that seems to eliminate risk entirely, even if another option offers a greater overall benefit. Important for understanding decision-making and designing risk communication for users.
A cognitive bias where people prefer the option that seems to eliminate risk entirely, even if another option offers a greater overall benefit. Important for understanding decision-making and designing risk communication for users.
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 set of algorithms, modeled loosely after the human brain, designed to recognize patterns and perform complex tasks. Essential for developing advanced AI applications in various fields.
A network of real-world entities and their interrelations, organized in a graph structure, used to improve data integration and retrieval. Crucial for enhancing data connectivity and providing deeper insights.
An analysis that assesses the practicality and potential success of a proposed project or system. Crucial for determining the viability and planning of new initiatives.
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 cognitive bias where individuals strengthen their beliefs when presented with evidence that contradicts them. Important for understanding user resistance to change and designing strategies to address and mitigate this bias.
A mental shortcut that relies on immediate examples that come to mind when evaluating a specific topic, concept, method, or decision. Crucial for understanding how people make decisions and the biases that influence their choices.
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 cognitive bias where individuals or organizations continue to invest in a failing project or decision due to the amount of resources already committed. Important for designers to recognize and mitigate their own risks of continuing unsuccessful initiatives.
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance. Fundamental for developing and evaluating machine learning models in digital product design.
The process of training an AI model on a large dataset before fine-tuning it for a specific task. Crucial for building robust AI models that perform well on various tasks.
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.
Numeronym for the word "Multilingualization" (M + 17 letters + N), enabling a product or system to support multiple languages, allowing users to switch between languages as needed. Crucial for ensuring smooth adaptation to various languages.
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.
Technologies that enable machines to understand and interpret data on the web in a human-like manner, enhancing connectivity and usability of information. Essential for improving data interoperability and accessibility on the web.
A project or venture that starts from scratch, with no constraints imposed by prior work, enabling innovation and flexibility in development. Essential for recognizing opportunities for innovation and fresh development in business initiatives.
A search method that seeks to improve search accuracy by understanding the contextual meaning of terms in a query rather than just matching keywords. Important for understanding modern search algorithms and optimizing content accordingly.
Ontology is a comprehensive model that includes entities, their attributes, and the complex relationships between them, while taxonomy is a hierarchical classification system that organizes entities into parent-child relationships. Essential for understanding the depth and scope of data organization, helping to choose the appropriate structure for information management and retrieval.
Business Rules Engine (BRE) is a software system that executes one or more business rules in a runtime production environment. Crucial for automating decision-making processes and ensuring consistency and compliance in digital products.
Business Process Management Software (BPMS) refers to tools and systems that help organizations design, model, execute, monitor, and optimize their business processes. Essential for improving operational efficiency and ensuring that digital products support effective business processes.
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 Principle of Exemplars is an information architecture guideline that uses representative examples to illustrate content categories. Crucial for enhancing user understanding and facilitating content discovery.
Software agents that can perform tasks or services for an individual based on verbal commands. Crucial for enhancing user experience through hands-free interaction and automation.
The process of assigning target keywords to specific pages on a website to optimize each page for relevant search terms and improve overall SEO strategy. Crucial for creating a structured and effective SEO strategy.
A visual representation of the stages a sales opportunity goes through, helping to track progress and forecast revenue. Important for managing sales processes and predicting future sales.
The systematic process of capturing, evaluating, and implementing ideas to drive innovation, reflecting a collective commitment to continuous improvement and product excellence. Essential for harnessing team creativity and maintaining the entrepreneurial spirit that characterizes successful product development.
The tendency to cling to one's beliefs even in the face of contradictory evidence. Important for understanding resistance to change and designing interventions that address this bias.
The condition in which two or more versions of a product or system offer the same features and functionalities, ensuring consistency and uniformity across different platforms or updates. Important for providing a consistent user experience, reducing confusion, and ensuring all users have access to the same capabilities regardless of the platform they use.
Numeronym for the word "Virtualization" (V + 12 letters + N), creating virtual versions of physical resources, such as servers, storage devices, or networks, to improve efficiency and scalability. Crucial for optimizing resource use and improving scalability.
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.
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.
Guidelines and principles designed to ensure that AI systems are developed and used in a manner that is ethical and responsible. Crucial for building trust and ensuring the responsible use of AI technologies.
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 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 metric that shows the revenue that a company can expect to receive annually from its customers for subscriptions or services. Essential for understanding business performance and growth potential.
Customer Experience Management (CEM) is the process of managing and improving the interactions and experiences customers have with a brand across all touchpoints. This process is essential for building strong customer relationships and enhancing brand loyalty.
The stages a customer goes through from awareness to purchase and post-purchase activities. Important for designing strategies that optimize customer acquisition, retention, and satisfaction.
Enterprise Architecture (EA) is a strategic framework used to align an organization's business strategy with its IT infrastructure. Crucial for optimizing processes, improving agility, and ensuring that technology supports business goals.
A problem-solving method that involves asking "why" five times to identify the root cause of a problem. Useful for designers and product managers to uncover underlying issues and improve processes and solutions.
Balanced Scorecard (BSC) is a strategic planning and management system used to align business activities to the vision and strategy of the organization. Essential for aligning business activities with organizational strategy and improving performance.
Test-Driven Development (TDD) is a software development methodology where tests are written before the code that needs to pass them. Essential for ensuring high code quality and reducing bugs.
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 process of evaluating and categorizing potential customers based on their likelihood to purchase. Essential for prioritizing sales efforts and improving conversion rates.
Don't Repeat Yourself (DRY) is a software development principle for reducing repetition and redundancy. Essential for creating efficient, maintainable, and scalable code in digital product design.
A mindset and approach that embodies the entrepreneurial spirit, passion for improvement, and deep sense of ownership typically associated with a company's founders. Essential for maintaining agility, innovation, and customer-centricity as organizations grow and mature.
An AI-driven assistant or tool that helps users accomplish tasks more efficiently, often by providing suggestions and automating routine actions. Important for enhancing productivity and user experience through AI assistance.
The Principle of Disclosure is an information architecture guideline that promotes revealing information progressively as users need it. Crucial for managing complexity and preventing information overload.
The speed at which leads move through the sales funnel. Crucial for understanding and optimizing the sales process.
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 Japanese word meaning excessive strain on people or processes. Crucial for preventing burnout and maintaining sustainable work practices.
Integrated Business Planning (IBP) is a process that aligns strategic, operational, and financial planning to optimize business performance. It ensures cohesive and efficient planning across all functions.
The ability to influence others' behavior by offering positive incentives or rewards, commonly used in organizational and social contexts. Crucial for understanding dynamics of motivation and influence in team and organizational settings.
A type of model architecture primarily used in natural language processing tasks, known for its efficiency and scalability. Essential for state-of-the-art NLP applications.
Customer Experience (CX) is the overall perception and feeling a customer has when interacting with a company, its products, or services. Crucial for ensuring positive interactions with a company, driving loyalty and satisfaction.
A metric that measures how engaged users are with a product, often based on usage frequency, feature adoption, and user feedback. Crucial for assessing user satisfaction and identifying areas for improvement in the product experience.
The practice of optimizing individual web pages to rank higher and earn more relevant traffic in search engines, focusing on both the content and HTML source code. Crucial for improving the visibility and relevance of web content in search engine results.
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.