A usability technique used to evaluate the findability and labeling of topics in a website's structure by having participants find specific items in a simplified text version of the site. Crucial for improving information architecture and ensuring users can navigate a website effectively.
A cognitive bias that occurs when conclusions are drawn from a non-representative sample, focusing only on successful cases and ignoring failures. Crucial for making accurate assessments and designing systems that consider both successes and failures.
The study of how people make choices about what and how much to do at various points in time, often involving trade-offs between costs and benefits occurring at different times. Crucial for designing systems that account for delayed gratification and long-term planning.
The tendency to perceive a greater quantity as a better value, regardless of the actual utility. Important for understanding consumer behavior and designing effective marketing strategies.
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.
A phenomenon where individuals' preferences between options change when the options are presented in different ways or contexts. Important for understanding and designing around inconsistencies in user choices.
A theory that suggests the depth of processing (shallow to deep) affects how well information is remembered. Important for designing educational content and user interfaces that enhance memory retention.
The behavior of seeking information or resources based on social interactions and cues. Important for understanding how users gather information in social contexts and designing systems that support collaborative information seeking.
A system where outputs are fed back into the process as inputs, allowing for continuous improvement based on user responses. Crucial for iterative development and continuous improvement in design and product management.
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.
Key Performance Indicators (KPIs) are quantifiable measures used to evaluate the success of an organization, employee, or project in meeting objectives for performance. Essential for tracking progress, making informed decisions, and aligning efforts with strategic goals across various business functions, including product design and development.
Measurements that track the effectiveness of each stage of the funnel, such as conversion rates and drop-off points. Crucial for identifying areas of improvement in the customer journey.
A cognitive bias where individuals' expectations influence their perceptions and judgments. Relevant for understanding how expectations skew perceptions and decisions among users.
A cognitive bias that causes people to believe they are less likely to experience negative events and more likely to experience positive events than others. Crucial for understanding user risk perception and designing systems that account for unrealistic optimism.
The tendency for individuals to continue a behavior or endeavor as a result of previously invested resources (time, money, or effort) rather than future potential benefits. Important for understanding decision-making biases and designing systems that help users avoid irrational persistence.
A framework that combines multiple theories to explain and predict behavior, focusing on intention, knowledge, skills, environmental constraints, and habits. Crucial for designing interventions that effectively change user behavior.
The change in opinions or behavior that occurs when individuals conform to the information provided by others. Important for understanding social dynamics and designing systems that leverage social proof and peer influence.
A principle often used in behavioral economics that suggests people evaluate options based on relative comparisons rather than absolute values. Important for understanding decision-making and designing choices that highlight beneficial comparisons.
A cognitive bias where people prefer a greater variety of options when making simultaneous choices compared to sequential choices. Important for designers to consider user preferences for variety when designing choice architectures and product offerings.
A cognitive architecture model that explains how humans can learn and adapt to new tasks. Useful for understanding user learning and behavior adaptation, informing better user experience design.
A usability testing method that measures the first click users make on a webpage to determine if they can successfully navigate to their goal. Essential for evaluating and improving the navigational structure of a website.
A method of comparing two versions of a webpage or app to see which performs better in terms of user engagement or conversions. Crucial for designers and product managers to test variations and optimize user experience and performance.
A psychological state where individuals lose their sense of self-awareness and personal responsibility in groups, often leading to atypical behavior. Crucial for understanding group dynamics and designing experiences that promote positive group interactions.
The process of tailoring a product or experience to meet the individual needs and preferences of users. Essential for enhancing user engagement and satisfaction by delivering relevant experiences.
A heuristic where individuals evenly distribute resources across all options, regardless of their specific needs or potential. Useful for understanding and designing around simplistic decision-making strategies.
The study of the principles that govern human behavior, including how people respond to stimuli and learn from their environment. Crucial for designing user experiences that anticipate and influence user behavior.
The practice of using data analytics and metrics to make informed decisions, focusing on measurable outcomes and efficiency rather than intuition or traditional methods. Important for optimizing design processes, improving product performance, and making data-driven decisions that enhance user experience and business success.
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.
The phenomenon where people continue a failing course of action due to the amount of resources already invested. Important for recognizing and mitigating biased decision-making.
The error of making decisions based solely on quantitative observations and ignoring all other factors. Important for ensuring a holistic approach to decision-making.
Lifetime Value (LTV) is a metric that estimates the total revenue a business can expect from a single customer account throughout their relationship. Crucial for informing customer acquisition strategies, retention efforts, and overall business planning by providing insights into long-term customer profitability.
A cognitive bias where decision-making is affected by the lack of information or uncertainty. Important for understanding and mitigating user decision-making biases due to uncertainty or lack of information.
A tendency to avoid making decisions that might lead to regret, influencing risk-taking and decision-making behaviors. Crucial for understanding decision-making processes and designing systems that minimize regret.
The study of social relationships, structures, and processes. Important for understanding the impact of social dynamics on user behavior and designing for social interactions.
An established company or market leader that holds a significant market share and has a strong presence in the industry. Important for understanding the dynamics between established players and new entrants in a market.
A behavioral economic theory that describes how people choose between probabilistic alternatives that involve risk, where the probabilities of outcomes are known. Crucial for understanding decision-making under risk and designing systems that align with user behavior.
The perseverance and passion for long-term goals, often seen as a key trait for success. Important for understanding and fostering resilience and persistence in design and product development.
Marketing Qualified Lead (MQL) is a prospective customer who has shown interest in a company's product or service and meets specific criteria indicating a higher likelihood of becoming a customer. Essential for prioritizing leads and optimizing the efficiency of sales and marketing efforts by focusing resources on prospects most likely to convert.
Quantitative measures used to track and assess the performance and success of a product, such as usage rates, customer satisfaction, and revenue. Essential for making data-driven decisions to improve product performance and achieve business goals.
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.
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.
An economic theory that explains why some necessities, such as water, are less expensive than non-essentials, like diamonds, despite their greater utility. Useful for understanding consumer behavior and designing pricing strategies.
Moment of Truth (MoT) refers to any instance where a customer interacts with a brand, product, or service in a way that leaves a significant impression. Crucial for identifying key touchpoints in the customer journey and optimizing them to enhance overall user experience and brand perception.
The level of awareness or popularity a product or brand has among consumers. Essential for understanding brand perception and guiding marketing and product design strategies to enhance visibility and user adoption.
Data points that represent an individual's, team's, or company's performance in the sales process. Essential for tracking progress, identifying issues, and optimizing sales strategies.
A cognitive bias where people overestimate the importance of information that is readily available. Essential for designers to understand and mitigate how easily accessible information can disproportionately influence decisions.
Internet of Things (IoT) refers to a network of interconnected physical devices embedded with electronics, software, sensors, and network connectivity, enabling them to collect and exchange data. Essential for creating smart, responsive environments and improving efficiency across various industries by enabling real-time monitoring, analysis, and automation.
Systematic errors in AI models that arise from the data or algorithms used, leading to poor outcomes. Important for ensuring fairness and accuracy in AI systems.
A theoretical framework in economics that assumes individuals act rationally and seek to maximize utility, used to predict economic behavior and outcomes. Important for understanding traditional economic theories and designing systems that account for rational decision-making.
A decision-making paradox that shows people's preferences can violate the expected utility theory, highlighting irrational behavior. Important for understanding inconsistencies in user decision-making and designing better user experiences.
The underlying goal or motivation behind a user's search query, crucial for understanding and optimizing content to meet user needs and improve SEO. Essential for creating content that aligns with user needs and improving search engine rankings.
A statistical method that models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data. Essential for predicting outcomes and understanding relationships between variables in digital product design and analysis.
A cognitive bias where individuals better remember the most recent information they have encountered, influencing decision-making and memory recall. Important for designing user experiences that leverage or mitigate the impact of recent information.
The process of making small, continuous improvements to products, services, or processes over time. Important for sustaining growth and maintaining competitiveness through ongoing improvements.
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.
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.
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.
The practice of identifying and analyzing search terms that users enter into search engines, used to inform content strategy and SEO. Essential for understanding user intent and optimizing content to meet search demand.
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.
The ability to identify and interpret patterns in data, often used in machine learning and cognitive psychology. Crucial for designing systems that leverage pattern recognition for predictive analytics and user interactions.