The goal of user experience design in industry is to improve customer satisfaction and loyalty through the utility, ease of use, and pleasure provided in the interaction with a product. So far, user experience studies have mostly focused on short-term evaluations and consequently on aspects relating to the initial adoption of new product designs. Nevertheless, the relationship between the user and the product evolves over long periods of time and the relevance of prolonged use for market success has been recently highlighted. In this paper, we argue for the cost-effective elicitation of longitudinal user experience data. We propose a method called the “UX Curve” which aims at assisting users in retrospectively reporting how and why their experience with a product has changed over time. The usefulness of the UX Curve method was assessed in a qualitative study with 20 mobile phone users. In particular, we investigated how users’ specific memories of their experiences with their mobile phones guide their behavior and their willingness to recommend the product to others. The results suggest that the UX Curve method enables users and researchers to determine the quality of long-term user experience and the influences that improve user experience over time or cause it to deteriorate. The method provided rich qualitative data and we found that an improving trend of perceived attractiveness of mobile phones was related to user satisfaction and willingness to recommend their phone to friends. This highlights that sustaining perceived attractiveness can be a differentiating factor in the user acceptance of personal interactive products such as mobile phones. The study suggests that the proposed method can be used as a straightforward tool for understanding the reasons why user experience improves or worsens in long-term product use and how these reasons relate to customer loyalty.Peer reviewe

We report on a 10-month in-the-wild study of the adoption, engagement and discontinuation of an activity tracker called Habito, by a sample of 256 users who installed the tracker on their own volition. We found 'readiness' to behavior change to be a strong predictor of adoption (which ranged from 56% to 20%). Among adopters, only a third updated their daily goal, which in turn impacted their physical activity levels. The use of the tracker was dominated by glances -- brief, 5-sec sessions where users called the app to check their current activity levels with no further interaction, while users displayed true lack of interest in historical data. Textual feedback proved highly effective in fueling further engagement with the tracker as well as inducing physical activity. We propose three directions for design: designing for different levels of 'readiness', designing for multilayered and playful goal setting, and designing for sustained engagement.