Recommendation Engine
A system that suggests products, services, or content to users based on their preferences and behavior. Essential for personalizing user experiences and increasing engagement and conversion rates.
A system that suggests products, services, or content to users based on their preferences and behavior. Essential for personalizing user experiences and increasing engagement and conversion rates.
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 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 data, algorithms, and machine learning to recommend actions that can achieve desired outcomes. Essential for optimizing decision-making and implementing effective strategies.
A cognitive bias where people rely too heavily on their own perspective and experiences when making decisions. Important for designers to recognize and mitigate their own perspectives influencing design decisions.
A marketing strategy that delivers targeted advertising and content based on the context of the user, such as their behavior or environment. Crucial for improving user engagement and relevance of marketing efforts in digital products.
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.
The practice of selling additional products or services to an existing customer. Essential for increasing revenue and enhancing customer value.
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.
A marketing strategy that leverages satisfied customers to promote products through word-of-mouth and personal endorsements. Important for product managers and marketers to enhance brand loyalty and customer engagement.
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.
A psychological phenomenon where people follow the actions of others in an attempt to reflect correct behavior for a given situation. Essential for designing interfaces and experiences that leverage social influence to guide user behavior and increase trust and engagement.
The phenomenon where having too many options leads to anxiety and difficulty making a decision, reducing overall satisfaction. Important for designing user experiences that balance choice and simplicity to enhance 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.
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.
A state of overthinking and indecision that prevents making a choice, often due to too many options or uncertainty. Important for designing interfaces that simplify decision-making processes for users.
The deteriorating quality of decisions made by an individual after a long session of decision making, due to mental exhaustion. Important for designing interfaces that minimize cognitive load and simplify decision processes.
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 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.