Enterprise Resource Planning (ERP) are integrated software systems that manage business processes across various departments, such as finance, HR, and supply chain. Essential for improving operational efficiency and providing a unified view of business operations.
A component in neural networks that allows the model to focus on specific parts of the input, improving performance. Essential for developing advanced AI models, particularly in natural language processing.
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 principle that the more a metric is used to make decisions, the more it will be subject to corruption and distort the processes it is intended to monitor. Important for understanding the limitations and potential distortions of metrics in design and evaluation.
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 process of generating a broad set of ideas on a given topic, with no attempt to judge or evaluate them initially. Crucial for creative problem-solving and developing innovative solutions in product design and development.
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.
A range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter. Essential for making inferences about population parameters and understanding the precision of estimates in product design analysis.
The process of tracking and managing potential customers from initial contact through to sale. Important for ensuring that leads are properly engaged and converted.
The risk of loss resulting from inadequate or failed internal processes, people, and systems. Important for identifying and mitigating potential operational threats.
A machine learning-based search engine algorithm used by Google to help process search queries and provide more relevant results. Important for understanding modern SEO practices and how search engines interpret and rank web content.
The study of how new ideas, products, and processes are developed and brought to market. Essential for fostering creativity and ensuring the continuous improvement and relevance of products.
A tool used to organize ideas and data into groups based on their natural relationships. Essential for designers and product managers to synthesize information and generate insights.
The practice of protecting systems, networks, and programs from digital attacks, unauthorized access, and data breaches. Essential for safeguarding sensitive information, maintaining user trust, and ensuring the integrity and functionality of digital products and services.
3-Tiered Architecture is a software design pattern that separates an application into three layers: presentation, logic, and data. Crucial for improving scalability, maintainability, and flexibility in software development.
The practice of comparing one's performance, processes, or practices to those of peers or competitors to identify areas for improvement. Important for understanding relative performance and identifying best practices for improvement.
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 iterative design process that uses algorithms and computational tools to generate a wide range of design solutions based on defined constraints and goals. Crucial for exploring innovative and optimized design solutions.
Plan-Do-Check-Act (PDCA) is an iterative four-step management method used for continuous improvement of processes and products. Essential for quality control and operational efficiency.
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.
The practice of quickly testing and iterating on ideas to validate assumptions and learn from user feedback in a short time frame. Essential for agile development and making data-driven decisions efficiently.
The process of setting short-term objectives and determining the actions needed to achieve them. Critical for aligning daily operations with strategic goals.
The ability to deliver products or services in the most cost-effective manner without sacrificing quality. Key to reducing costs and improving profitability.
A usability testing method where participants verbalize their thoughts while interacting with a product. Essential for understanding user thought processes and identifying usability issues.
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.
A problem-solving method that involves asking "why" five times to identify the root cause of a problem. Useful for designers and product managers to uncover underlying issues and improve processes and solutions.
Human-Centered Design (HCD) is an approach to problem-solving that involves the human perspective in all steps of the process. It ensures designs are user-friendly and meet actual user needs.
A visual representation of the stages a sales opportunity goes through, helping to track progress and forecast revenue. Important for managing sales processes and predicting future sales.
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.
The process of training an AI model on a large dataset before fine-tuning it for a specific task. Crucial for building robust AI models that perform well on various tasks.
The process of continuously improving a product's performance, usability, and value through data-driven decisions and iterative enhancements. Crucial for ensuring that a product remains competitive and meets evolving user needs.
A concept that humans make decisions within the limits of their knowledge, cognitive capacity, and available time, leading to satisficing rather than optimal solutions. Crucial for designing systems and processes that account for human cognitive limitations and decision-making processes.
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.
Quality Function Deployment (QFD) is a method used to transform customer needs into engineering characteristics for a product or service. Essential for ensuring that customer requirements are systematically incorporated into the design and development process.
Often referred to as "marketing funnel", a model that represents the user journey from awareness to purchase used to analyze and optimize conversion of prospects to customers. Essential for understanding and improving the customer journey and conversion process.
A phenomenon where people better understand and remember information when it is presented visually. Crucial for designing effective and engaging visual content.
The series of actions or operations involved in the acquisition, interpretation, storage, and retrieval of information. Crucial for understanding how users handle information and designing systems that align with cognitive processes.
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.
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.
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 mode of thinking, derived from Dual Process Theory, that is slow, deliberate, and analytical, requiring more cognitive effort and conscious reasoning. Crucial for designing complex tasks and interfaces that require thoughtful decision-making and problem-solving, ensuring they are clear and logical for users.
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 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.
The speed at which leads move through the sales funnel. Crucial for understanding and optimizing the sales process.
Application Programming Interface (API) is a set of tools and protocols that allow different software applications to communicate and interact with each other. Essential for integrating different systems and enabling functionality in digital products.
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments. Crucial for ensuring the reliability, scalability, and performance of AI systems throughout their lifecycle, bridging the gap between model development and operational implementation.
The process of turning potential customers into paying customers, often measured by the conversion rate. Essential for understanding and optimizing the customer journey.
Voice of the Customer (VOC) is a process for capturing customers' expectations, preferences, and aversions. Crucial for guiding product development and improving customer satisfaction.
The practice of comparing performance metrics to industry bests or best practices from other companies. Essential for identifying performance gaps and opportunities for improvement.
Measurements used to evaluate the success of an organization, employee, or process in meeting goals. Necessary for assessing performance and driving continuous improvement.
The process of gathering and analyzing information about competitors to inform business strategy and decision-making. Essential for understanding market positioning and developing effective competitive strategies.
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 systematic process for determining and addressing needs or gaps between current conditions and desired outcomes. Important for identifying user requirements and guiding the development of digital products that meet those needs.
The process of phasing out or retiring a product or feature that is no longer viable or needed. Important for managing the lifecycle of digital products and ensuring resources are allocated to more valuable initiatives.
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 process of making small, continuous improvements to products, services, or processes over time. Important for sustaining growth and maintaining competitiveness through ongoing improvements.
The process of systematically collecting, analyzing, and acting on feedback from users to improve products and services. Essential for ensuring that user insights are effectively integrated into the development process.
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 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.
The process of understanding user behaviors, needs, and motivations through various qualitative and quantitative methods. Essential for designing user-centered products and ensuring they meet actual user needs.