A bias that occurs when the sample chosen for a study or survey is not representative of the population being studied, affecting the validity of the results. Important for ensuring the accuracy and reliability of research findings and avoiding skewed data.
Application Support Engineer (ASE) is a professional responsible for maintaining and supporting software applications, ensuring their availability and performance. Crucial for ensuring the reliability and user satisfaction of digital products through effective support and maintenance.
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 guided, interactive overlay that introduces users to features or tasks within an application. Crucial for onboarding new users and enhancing user understanding of complex features.
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.
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.
A simple sorting algorithm that repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. Important for understanding basic algorithmic principles and their applications.
Portfolio Management is the process of overseeing and coordinating an organization's collection of products to achieve strategic objectives. Crucial for balancing resources, maximizing ROI, and aligning products with business goals.
The process of identifying, assessing, and mitigating potential threats that could impact the success of a digital product, including usability issues, technical failures, and user data security. Essential for maintaining product reliability, user satisfaction, and data protection, while minimizing the impact of potential design and development challenges.
The process of predicting future customer demand using historical data and other information. Crucial for optimizing inventory levels, production schedules, and supply chain management.
The process by which consumers become aware of and learn about a brand. Important for establishing initial brand awareness and attracting potential customers.
A recommendation system technique that suggests items similar to those a user has shown interest in, based on item features. Important for providing personalized recommendations and improving user satisfaction.
The use of AI and advanced analytics to divide users into meaningful segments based on behavior and characteristics. Crucial for personalized marketing and improving user experience.
A short, time-boxed period used in Agile development to research a concept or explore a new technology. Important for reducing uncertainty and risk in development.
The planning, development, and management of content to meet business and user needs, ensuring consistency and effectiveness across all channels. Essential for creating cohesive and impactful content that aligns with business goals and user needs.
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.
Business Process Automation (BPA) refers to the use of technology to automate complex business processes. Essential for streamlining operations, reducing manual effort, and increasing efficiency in recurring tasks.
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.
The path taken by a user to complete a task on a website or application, including all the steps and interactions along the way. Essential for designing intuitive and efficient user experiences.
An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Essential for driving data-informed decision making, predicting trends, and uncovering valuable insights in digital product design and development.
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.
Data points that differ significantly from other observations and may indicate variability in a measurement, experimental errors, or novelty. Crucial for identifying anomalies and ensuring the accuracy and reliability of data in digital product design.
Decision-making strategies that use simple heuristics to make quick, efficient, and satisfactory choices with limited information. Important for designing user experiences that support quick and efficient decision-making.
AI as a Service (AIaaS) is a service model where AI tools and algorithms are provided over the internet by a third-party provider. Essential for making advanced AI capabilities accessible to businesses.
A design concept where digital interfaces incorporate elements that resemble their real-world counterparts to make them more intuitive and familiar to users. Important for creating intuitive and user-friendly interfaces by leveraging familiar real-world cues.
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 professional who designs, builds, and maintains systems for processing large-scale data sets. Essential for enabling data-driven decision-making and supporting advanced analytics in organizations.
A temporary increase in the frequency and intensity of a behavior when reinforcement is first removed. Useful for understanding user behavior changes in response to modifications in design or system features.
Integrated Development Environment (IDE) is a software suite that combines tools like code editors, debuggers, and compilers. Essential for improving developer productivity and ensuring efficient and error-free coding practices.
A skill set that combines deep knowledge in a single area (the vertical stroke) with a broad understanding across multiple disciplines (the horizontal stroke). Valuable for fostering versatility and collaboration within teams, enhancing problem-solving and innovation.
User interfaces that change in response to user behavior or preferences to improve usability and efficiency. Crucial for creating personalized and efficient user experiences.
The practice of dividing a customer base into distinct groups based on common characteristics. Crucial for targeting marketing efforts and personalizing customer interactions.
Extremely large data sets that can be analyzed computationally to reveal patterns, trends, and associations. Crucial for gaining insights and making data-driven decisions.
A recommendation system technique that makes predictions about user interests based on preferences from many users. Essential for personalizing user experiences and improving recommendation accuracy.
A navigation design pattern where users follow a specific order of steps or stages to complete a task, often used in forms, surveys, and instructional guides. Essential for guiding users through processes in a clear and structured manner, improving usability.
Net Promoter Score (NPS) is a metric used to measure customer loyalty and satisfaction based on their likelihood to recommend a product or service to others. Crucial for gauging overall customer sentiment and predicting business growth through customer advocacy.
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.
A research method that focuses on collecting and analyzing numerical data to identify patterns, relationships, and trends, often using surveys or experiments. Essential for making data-driven decisions and validating hypotheses with statistical evidence.
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.
A cognitive bias where people perceive past events as having been more predictable than they actually were. Important for understanding and mitigating biases in user feedback and decision-making.
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 marketing strategy that uses user behavior data to deliver personalized advertisements and content. Important for improving user engagement and conversion rates by providing relevant and timely information to users.
Enterprise Project Management (EPM) is a comprehensive approach to managing projects across an entire organization. Essential for coordinating complex, cross-functional projects and achieving organizational objectives.
Characteristics of big data defined as Volume, Velocity, Variety, Veracity, and Value. Important for understanding the complexities and potential of big data in driving business insights and innovation.
A comprehensive view of a customer that includes data from all interactions and touchpoints across the customer journey. Crucial for delivering personalized experiences and improving customer satisfaction.
A set of ten general principles for user interface design created by Jakob Nielsen to improve usability. Essential for evaluating and improving user interface designs.
The organizational structure and dynamics of teams within a company, designed to enhance collaboration and delivery. Important for optimizing team performance and project outcomes.
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.
Search Engine Marketing (SEM) is a digital marketing strategy used to increase a website's visibility in search engine results pages (SERPs) through paid advertising. Essential for driving targeted traffic and improving online presence.
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 psychological phenomenon where people remember uncompleted or interrupted tasks better than completed tasks. Crucial for designing engaging experiences that leverage task incompletion to maintain user interest.
The process of evaluating and categorizing potential customers based on their likelihood to purchase. Essential for prioritizing sales efforts and improving conversion rates.
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 cognitive bias where individuals underestimate their own abilities and performance relative to others, believing they are worse than average. Important for understanding self-perception biases among designers and designing systems that support accurate self-assessment.
A key aspect of Gestalt psychology where complex patterns arise out of relatively simple interactions. Crucial for understanding how users perceive complex designs and patterns.
The process of linking language to its real-world context in AI systems, ensuring accurate understanding and interpretation. Crucial for improving the relevance and accuracy of AI-generated responses.
A web-based interface that allows customers to find information and perform tasks without needing assistance from a customer service representative. Essential for improving customer experience and reducing support costs.
A design pattern that combines human and machine intelligence to enhance decision-making and problem-solving. Important for leveraging AI to support and amplify human capabilities.
A research process used to identify and understand the underlying needs of users to inform the design of products and services. Essential for creating user-centered designs that address real user needs.
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.