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Improving Interactive User Experience With Microinteractions: an Application of Biometric and Affect Detection Systems on Landing Pages

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2019-11-06

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Reyneke, Rupert. 2019. Improving Interactive User Experience With Microinteractions: an Application of Biometric and Affect Detection Systems on Landing Pages. Master's thesis, Harvard Extension School.

Abstract

The essence of User Experience (UX) is to improve the quality of the user’s interaction with and perception of the product or service offered. Measuring user perception of these interactions has been subjective and challenging to quantify in objective terms. Biometric sensors provide real time inferences of the user’s emotional affect. Facial recognition software provides an additional data layer to infer the emotional affect during each interaction. Answers to subjective questions such as: How the user feels about this interaction? What interaction caused the user frustration? And what interactions resulted in enjoyable experiences? Can be ascertained and provide deeper insights into improving the user experience. Data from biometric sensors can infer and validate whether the UX strategy is meeting the intended goals and objectives. Decision makers can use these insights to quickly improve and gain a deeper understanding of the user’s preferences and perceptions, thereby increasing profitability and user loyalty. These insights will be measured by: time spent on tasks, interactions, and emotional affect throughout the session on digital media assets.

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AFFDEX, Affectiva, emotions, emotion classification, facial micro-expressions, microinteractions, FACS, facial expression, feedback loop, user experience, iMotions, Tobi, user experience, UX/UI.

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