Certainty Effect
A cognitive bias where people give greater weight to outcomes that are certain compared to those that are merely probable. Important for designers to consider how users weigh certain outcomes more heavily in their decision-making.
A cognitive bias where people give greater weight to outcomes that are certain compared to those that are merely probable. Important for designers to consider how users weigh certain outcomes more heavily in their decision-making.
Emotional states where individuals are calm and rational, often contrasted with hot states where emotions run high. Important for understanding decision-making processes and designing experiences that accommodate both states.
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.
The study of the interplay between individuals and their surroundings, including built environments and natural settings. Essential for designing spaces that enhance well-being and productivity.
A framework that explores the structure and function of stories and how they influence human cognition and behavior. Important for creating compelling and meaningful user experiences through storytelling.
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 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.
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.
The study of dynamic systems that are highly sensitive to initial conditions, leading to unpredictable behavior. Important for recognizing and managing unpredictable elements in design and development processes.
The tendency for people to value products more highly if they have put effort into assembling them. Important for understanding user satisfaction and product attachment.
A mode of thinking, derived from Dual Process Theory, that is fast, automatic, and intuitive, often relying on heuristics and immediate impressions. Important for understanding how users make quick decisions and respond to design elements instinctively, aiding in the creation of intuitive and user-friendly interfaces.
A design approach that uses data, algorithms, and predictive analytics to anticipate user needs and behaviors, creating more personalized and effective experiences. Crucial for enhancing user experience through anticipation and personalization.
A research approach that starts with observations and develops broader generalizations or theories from them. Useful for discovering patterns and generating new theories from data.
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 dark pattern where a process is made more difficult than it needs to be to discourage certain behavior. Recognizing the harm of this practice is important to design straightforward user processes.
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 common pattern of eye movement where users scan web content in an "F" shape, focusing on the top and left side of the page. Crucial for designing web content that aligns with natural reading patterns to improve engagement.
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.
Quantitative data that provides broad, numerical insights but often lacks the contextual depth that thick data provides. Useful for capturing high-level trends and patterns, but should be complemented with thick data to gain a deeper understanding of user behavior and motivations.
The collection of all the backlinks (inbound links) pointing to a website, used to assess its authority and influence in search engine rankings. Essential for understanding and improving SEO strategies.
A user-centered design process that involves understanding users' needs and workflows through field research and applying these insights to design. Essential for creating designs that are deeply informed by user contexts and behaviors.
The SEO value or authority passed from one website to another through hyperlinks, influencing the search engine ranking of the linked site. Important for understanding and leveraging the impact of links on SEO performance.
A psychological phenomenon where repeated exposure to a stimulus leads to an increased preference for it. Useful for designing marketing and user engagement strategies that increase familiarity and preference.
Research aimed at exploring and identifying new opportunities, needs, and ideas to inform the design process. Essential for discovering user insights and guiding innovative design solutions.
An approach that places the user's needs, preferences, and behaviors at the forefront of all design and development activities. Important for fostering a design culture that prioritizes user satisfaction and engagement.
A reading pattern where users scan a page in horizontal stripes, focusing on headings and subheadings. Important for structuring content in a way that facilitates quick scanning and information retrieval.
Conversion Rate Optimization (CRO) is the systematic process of increasing the percentage of website visitors who take a desired action, such as making a purchase or filling out a form. Crucial for improving user engagement and achieving business goals.
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 perception of a brand in the minds of consumers, shaped by interactions and experiences with the brand. Crucial for understanding consumer perceptions and guiding brand strategy.
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.
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.
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.
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.
Principle of Least Astonishment (POLA) is a design guideline stating that interfaces should behave in a way that users expect to avoid confusion. Crucial for enhancing user experience and reducing the learning curve in digital products.
A statistical measure that quantifies the amount of variation or dispersion of a set of data values. Essential for understanding data spread and variability, which helps in making informed decisions in product design and analysis.
A technique that visualizes the process users go through to achieve a goal with a product or service. Essential for identifying pain points and optimizing user interactions to improve overall experience.
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.
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 people ignore general statistical information in favor of specific information. Critical for designers to use general statistical information to improve decision-making accuracy and avoid bias.
New Product Development (NPD) is the complete process of bringing a new product to market, from idea generation to commercialization. Essential for companies to innovate, stay competitive, and meet evolving customer needs through a structured approach to creating and launching new offerings.
A design technique that overrides the default scrolling behavior, often to create a more controlled or immersive experience. Controversial; can enhance or hinder user experience depending on implementation.
A statistical distribution where most occurrences take place near the mean, and fewer occurrences happen as you move further from the mean, forming a bell curve. Crucial for data analysis and understanding variability in user behavior and responses.
The tendency to perceive and interpret information based on prior experiences and expectations, influencing how different users perceive design differently. Important for designing interfaces that meet user expectations, improving usability and intuitive navigation.
User Experience (UX) refers to the overall experience of a person using a product, system, or service, encompassing all aspects of the end-user's interaction. Crucial for creating products that are not only functional but also enjoyable, efficient, and satisfying to use.
AI systems that can dynamically adjust their behavior based on new data or changes in the environment. Important for developing systems that can respond to real-time changes and improve over time.
The psychological phenomenon where people prefer options that are not too extreme, but just right. Crucial for designing products and experiences that cater to the majority preference.
The percentage of users who take a specific action that signifies they are engaging with a product or service. Important for measuring user engagement and the effectiveness of onboarding processes.
The cues and hints that users follow to find information online, based on perceived relevance and usefulness. Important for designing intuitive navigation and content structures that align with user expectations.
Numeronym for the word "Personalization" (P + 13 letters + N), tailoring a product, service, or experience to meet the individual preferences, needs, or behaviors of each user. Important for enhancing user satisfaction and engagement.
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.
A specific form of banner blindness where users ignore content placed in the right-hand rail of a web page. Important for optimizing web page layouts and placing critical information where it will be seen.
A graphical representation of the distribution of numerical data, typically showing the frequency of data points in successive intervals. Important for analyzing and interpreting data distributions, aiding in decision-making and optimization in product design.
The process by which a measure or metric comes to replace the underlying objective it is intended to represent, leading to distorted decision-making. Important for ensuring that metrics accurately reflect true objectives and designing systems that prevent metric manipulation.
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 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.
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.
Specific roles assigned to HTML elements to define their purpose and behavior in an accessible manner. Crucial for improving the accessibility and usability of web applications.
The use of statistical techniques and algorithms to analyze historical data and make predictions about future outcomes. Important for optimizing marketing strategies and anticipating customer needs.
A semi-fictional representation of an ideal customer based on market research and real data about existing customers. Essential for targeting design and marketing efforts to meet the needs and preferences of specific user groups.
A phenomenon where users perceive greater value in a service or product if they believe more effort was involved in its creation or delivery. Important for enhancing perceived value and user satisfaction.