The endowment effect explains why users value things more once they feel ownership. In UX, we can design for this effect to increase engagement and user retention.
Product-centric design does not leverage design’s potential for creating long-term business value and profitability. Journey-centric design can activate this potential and optimize customer experiences.
There are five steps to run the Wizard of Oz Method, a moderated research method in which a user interacts with an interface that appears to be automated but is actually controlled to some degree by a person.
Users’ willingness to share data and their interactions with cookie permission box options vary quite drastically, falling into these five common user types: The Denier, The Skeptic, The Tech-Savvy, The Impatient, and The Enthusiast.
Most calculator and quiz tools provide at least one or more of the following services: converting inputs, predicting the future, or providing recommendations.
Calculators and quizzes provide personalized information. Users approach these tools with an exploratory mindset and appreciate them while making decisions.
Smartwatches are for more than just receiving notifications and tracking steps. They afford at least 6 different types of interactions that users find useful.
Prospective university students are selective when applying to schools. They share many of the same questions and expect communications to be personalized.
Addressing these 3 fundamental psychological needs in our products increases user motivation and well-being. Users will be more engaged and more likely to use our designs.
Shortcuts— unseen by the novice user — speed up the interaction for the expert users such that the system can cater to both inexperienced and experienced users.
In a study of people interacting with systems using machine-learning algorithms for recommendations and personalization, users had weak mental models and difficulties making the UI do what they want.
Encourage engagement with recommendations by presenting them prominently, segmenting suggestions into clear categories, and providing methods for users to give feedback.
Users appreciate personalized content suggestions and are willing to give up some of their privacy for quality recommendations, while accepting some inaccurate recommendations.
