Approaches to Improve User Experience in Product Development: UX Goals, Long-Term Evaluations and Usage Data Logging

Abstract

Companies that develop digital products are increasingly interested in designing products and services that provide positive experiences for users. User-centered approaches can support product development teams in creating products that are more likely to offer the intended user experience (UX) to the customers. Instructions and guidance based on empirical studies in reallife contexts can provide valuable information for product development teams, including UX designers and other UX experts working in the industry. User-centered design and evaluation methods are used widely. However, there is a lack of specific guidance on how to achieve and evaluate the desired UX during the product development process of digital products.<br/><br/>This thesis explores three different approaches for supporting product development activities towards the desired user experience: setting UX goals, long-term UX evaluations, and utilizing usage data logging. This research work was motivated by the lack of empirical studies regarding the utilization of UX goals and long-term UX evaluation methods in product development of digital products. In addition, little is known about how product development teams perceive the utilization of usage data logging, especially in manufacturing industry. This thesis is based on research work conducted in five case studies and published in six scientific publications. Four of the studies were conducted in collaboration with product development practitioners from companies and included real or potential end-users (e.g., customers or company employees). Three of the studies evaluated UX of real products on the market. In total, during all the case studies, data from 185 survey responses and 20 interviews were analyzed, while log data were collected and analyzed from 61 participants.<br/><br/>First, the elicitation process of UX goals is explored as a part of the experience design process, where the intended experiences are set as a starting point of the design. Findings from nine design cases are synthesized as characteristics of a good UX goal, instructions for defining UX goals and as a theoretical Experience Goal Elicitation Process. Second, the benefits and challenges of specific, long-term UX evaluation methods are summarized. The perceptions of product development practitioners reveal that long-term UX evaluations can 1) help in understanding change in UX over time, 2) confirm expectations based on other data sources, 3) support updating of current products, and 4) support the conceptualization and development of future products. Third, the expected benefits by practitioners for usage data logging include the following: 1) the data show what users really do; 2) data can be collected without disturbing users; 3) findings from the data can inform user interface design decisions and 4) justify more qualitative user studies. Furthermore, 5) logged usage data can provide new business opportunities for supplier companies in the manufacturing industry. The utilization of usage data logging can be supported through collaborative development of visual data analytics tools between researchers from academia and practitioners from industry. Guidelines to support such collaborative processes are provided.<br/><br/>This research work provides theoretical contributions in the form of the Experience Goal Elicitation Process. Methodological contributions include a new understanding of benefits and challenges of long-term UX evaluation methods. Furthermore, the case study descriptions and the instructions for defining UX goals contribute to product development activities on a practical level. These results can support product development teams and especially UX designers investigating the feasibility of UX goals and long-term evaluation methods for their product design and evaluation activities. The expected benefits of long-term UX evaluations and usage data logging can inform UX designers and managers when considering how to utilize these approaches. The guidelines for developing visual data analytics tools can support analytics tool developers in academia and industry. Future studies should develop the studied approaches further by investigating their utilization in different consumer and business-to-business contexts.