Obstacles to effective communication that arise from differences in understanding the meanings of words and symbols used by the communicators. Crucial for designing clear and effective communication systems and avoiding misunderstandings.
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.
The initial interaction a customer has with a brand. Important for understanding the beginning of the customer journey.
A unit of measure used in Agile project management to estimate the relative effort required to complete a user story or task. Crucial for planning and managing workload within Agile teams.
A large body of work that can be broken down into smaller tasks or user stories, used in agile project management to organize work. Essential for managing and organizing large projects in agile development.
The practice of dividing a customer base into distinct groups based on common characteristics. Crucial for targeting marketing efforts and personalizing customer interactions.
CSAT (Customer Satisfaction) measures how products or services provided by a company meet or exceed customer expectations. Essential for understanding customer needs and improving product offerings.
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 metric used to rank leads based on their engagement with a brand, indicating their readiness to purchase. Crucial for prioritizing leads and improving sales efficiency.
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.
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.
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
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 theory that explains how the amount of mental effort required to process information can impact user experience and task performance. Important for designing user interfaces that minimize unnecessary cognitive effort, enhancing usability and user satisfaction.
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.
Model-View-Controller (MVC) is an architectural pattern that separates an application into three main logical components: the Model (data), the View (user interface), and the Controller (processes that handle input). Essential for creating modular, maintainable, and scalable software applications by promoting separation of concerns.
A cognitive process that groups information into manageable units, making it easier to remember and process. Important for designing user interfaces that enhance usability and information retention.
Replacing one UI component with another, often used in adaptive or dynamic interfaces. Crucial for maintaining flexibility and adaptability in UI design.
Joint Application Development (JAD) is a collaborative approach to gathering requirements and designing solutions in software development projects. It facilitates rapid decision-making and consensus-building by bringing together key stakeholders, including users, developers, and project managers, in structured workshop sessions.
Knowledge Organization System (KOS) refers to a structured framework for organizing, managing, and retrieving information within a specific domain or across multiple domains. Essential for improving information findability, enhancing semantic interoperability, and supporting effective knowledge management in digital environments.
A prioritization framework used to assess and compare the value a feature will deliver to users against the complexity and cost of implementing it. Crucial for making informed decisions about feature prioritization and resource allocation.
The process by which search engines organize and store web content to facilitate fast and accurate information retrieval. Crucial for understanding how search engines work and ensuring that web content is accessible and searchable.
A stimulus that gains reinforcing properties through association with a primary reinforcer, such as money or tokens, which are associated with basic needs. Essential for understanding complex behavior reinforcement strategies and designing effective reward systems.
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 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.
Natural Language Processing (NLP) is a field of AI focused on the interaction between computers and humans using natural language. Essential for developing applications like chatbots, language translation, and sentiment analysis.
Know Your Customer (KYC) is a process used by businesses to verify the identity of their clients and assess potential risks of illegal intentions for the business relationship. Essential for preventing fraud, money laundering, and terrorist financing, particularly in financial services, while also ensuring compliance with regulatory requirements and building trust with customers.
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.
A phenomenon where people better understand and remember information when it is presented visually. Crucial for designing effective and engaging visual content.
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 systematic computational analysis of data or statistics to understand and improve business performance. Essential for data-driven decision making in design, product management, and marketing.
Proof of Concept (PoC) is a demonstration, usually in the form of a prototype or pilot project, to verify that a concept or theory has practical potential. Crucial for validating ideas, demonstrating feasibility, and securing support for further development in product design and innovation processes.
Artificial Intelligence of Things (AIoT) is the integration of AI with the Internet of Things (IoT) to create smart systems that can learn and adapt. Crucial for developing advanced, intelligent products that offer enhanced user experiences and operational efficiencies.
Software as a Service (SaaS) is a software distribution model where applications are hosted by a service provider and accessed over the Internet. Crucial for enabling scalable and cost-effective software solutions for users.
Large Language Model (LLM) is an advanced artificial intelligence system trained on vast amounts of text data to understand and generate human-like text. Essential for natural language processing tasks, content generation, and enhancing human-computer interactions across various applications in product design and development.
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.
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.
The process of encoding sensory input that has particular meaning or can be applied to a context, enabling deeper processing and memory retention. Important for understanding how information is processed and stored, enhancing design of educational content.
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.
The design of products, devices, services, or environments for people with disabilities or specific needs. Crucial for creating inclusive products that can be used by everyone, including those with disabilities.
The practice and science of classification, often used to organize content and information. Essential for improving findability and usability in information systems.
Also known as Expert Review, a method where experts assess a product or system against established criteria to identify usability issues and areas for improvement. Essential for leveraging expert insights to enhance product quality and usability.
AI systems designed to generate creative content, such as art, music, and literature. Important for exploring new forms of artistic expression and automating creative processes.
A bias that occurs when researchers' expectations influence the outcome of a study. Crucial for designing research methods that ensure objectivity and reliability.
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 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.
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.
A comprehensive analysis of a website to assess its performance in search engine rankings and identify areas for improvement. Essential for diagnosing and enhancing a website's SEO performance.
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.
A structured routine for continuous improvement based on a scientific approach to problem-solving and process optimization. Crucial for fostering a culture of continuous improvement and innovation within product design teams.
Crit (Design Critique) is a structured feedback session where designers present their work and receive constructive feedback from peers. Essential for refining design quality through collaborative input.
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.
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 process of optimizing content and website structure to improve visibility and ranking in voice search results. Important for adapting to the growing use of voice search and ensuring content is accessible to voice queries.
A reusable solution to common design problems that provides a standard way of addressing recurring issues in design. Essential for creating consistent and efficient design solutions.
The extent to which individuals or organizations plan for and consider the long-term consequences of their actions. Crucial for designing strategies and products that are sustainable and adaptable over time.
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.
Search Engine Optimization (SEO) is the process of improving a website's visibility and ranking in organic search engine results. Essential for attracting more traffic and enhancing the online presence of a website.
A marketing strategy that uses multiple channels to reach and engage customers, such as email, social media, and websites. Crucial for maximizing customer reach and engagement by leveraging diverse communication platforms in digital products.
The preferred version of a web page that search engines should index, used to avoid duplicate content issues and improve SEO. Essential for managing SEO and ensuring the correct indexing of web pages.