Expected Utility Theory
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 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.
The experience of noticing something for the first time and then frequently encountering it shortly after, also known as frequency illusion. Important for understanding user perception and cognitive biases in information processing.
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.
Product Strategy is a framework that outlines how a product will achieve its business goals and satisfy customer needs. Crucial for guiding product development, prioritizing features, and aligning the team around a clear vision.
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.
A cognitive bias where individuals evaluate the value of bundled items differently than they would if the items were evaluated separately. Important for understanding user behavior and designing effective product bundles and pricing strategies.
A framework for prioritizing product features based on their impact on customer satisfaction, classifying features into categories such as basic, performance, and delight. Crucial for understanding customer needs and prioritizing features that enhance satisfaction.
A psychological phenomenon where the desire for harmony and conformity in a group results in irrational or dysfunctional decision-making. Crucial for recognizing and mitigating the risks of poor decision-making in teams.
A concept in behavioral economics that describes how future benefits are perceived as less valuable than immediate ones. Important for understanding user preferences and designing experiences that account for time-based value perceptions.
A cognitive bias where people perceive an outcome as certain while it is actually uncertain, based on how information is presented. Crucial for understanding and mitigating biased user decision-making.
Critical Incident Technique (CIT) is a method used to gather and analyze specific incidents that significantly contribute to an activity or outcome. This method is important for identifying key factors that influence performance and user satisfaction.
An algorithm used by Google Search to rank web pages in their search engine results, based on the number and quality of links to a page. Essential for understanding search engine optimization and improving website visibility.
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 psychological state where individuals feel as though the success and well-being of a project or task is their personal responsibility, akin to having an "owner's mentality.". Essential for fostering accountability, motivation, and proactive engagement within a product design team.
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.
The phenomenon where higher-priced products are perceived to be of higher quality, regardless of the actual quality. Useful for understanding consumer perceptions and designing effective pricing strategies.
Mutually Exclusive, Collectively Exhaustive (MECE) is a problem-solving framework ensuring that categories are mutually exclusive and collectively exhaustive, avoiding overlaps and gaps. Essential for structured thinking and comprehensive analysis in problem-solving.
Customer Effort Score (CES) is a metric that measures how much effort customers have to put in to interact with a product or service. Crucial for identifying friction points and improving user experience in digital products.
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.
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.
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 principle that states tasks always take longer than expected, even when considering Hofstadter's Law itself. Important for setting realistic project timelines and managing expectations in digital product development.
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.
Representativeness is a heuristic in decision-making where individuals judge the probability of an event based on how much it resembles a typical case. Crucial for understanding biases in human judgment and improving decision-making processes.
Feature Driven Development (FDD) is an agile methodology focused on designing and building features based on client-valued functionality. Essential for delivering client-valued features efficiently and effectively.
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.
Goal-Question-Metrics (GQM) is a framework for defining and interpreting software metrics by identifying goals, formulating questions to determine if the goals are met, and applying metrics to answer those questions. This framework is essential for measuring and improving software quality and performance.
A cognitive bias where people see patterns in random data. Important for designers to improve data interpretation and avoid false conclusions based on perceived random patterns.
The process of maintaining, updating, and improving a product or system after its initial deployment to ensure its continued functionality, performance, and relevance to users. Crucial for ensuring long-term user satisfaction, product reliability, and adaptation to changing user needs and technological advancements.
Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) is an acronym for describing the challenging conditions of the modern world. Important for understanding and navigating dynamic and unpredictable environments.
The tendency to overvalue new innovations and technologies while undervaluing existing or traditional approaches. Important for balanced decision-making and avoiding unnecessary risks in adopting new technologies.
A test proposed by Alan Turing to determine if a machine's behavior is indistinguishable from that of a human. Important for evaluating the intelligence of AI systems.
Product Requirements is a document that outlines the essential features, functionalities, and constraints of a product. Crucial for guiding the development process and ensuring all stakeholders have a shared understanding of the product's goals.
Software Development Life Cycle (SDLC) is a process for planning, creating, testing, and deploying an information system. Essential for managing the complexities of software development and ensuring project success.
The application of neuroscience principles to marketing, aiming to understand consumer behavior and improve marketing strategies. Important for creating more effective and engaging marketing campaigns.
The process of combining multiple products or product lines into a single offering to streamline operations and reduce complexity. Useful for optimizing product portfolios and improving operational efficiency.
The tendency for people to defer purchasing decisions to a later time, often leading to procrastination. Important for understanding consumer behavior and optimizing sales strategies.
Strengths, Weaknesses, Opportunities, and Threats (SWOT) is a strategic planning tool that is applied to a business or project. Essential for strategic planning and decision-making.
Attention, Interest, Desire, Action (AIDA) is a marketing model that outlines the stages a consumer goes through from awareness to decision. Crucial for creating effective marketing strategies and campaigns.
The belief that abilities and intelligence can be developed through dedication and hard work. Important for fostering a culture of continuous learning and improvement.
Interactive Voice Response (IVR) is an automated telephony system that interacts with callers, gathers information, and routes calls to the appropriate recipient. It improves customer service and automates information retrieval.
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 four key elements of marketing: Product, Price, Place, and Promotion, used to develop marketing strategies. Important for creating comprehensive marketing strategies that effectively promote digital products.